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Engineering (PhD)

2024-25 (also available for 2023-24, 2025-26)

This course is eligible for Doctoral loan funding. Find out more.

Start date

1 October 2024

13 January 2025

14 April 2025

Duration

The maximum duration for a PhD is 3 years (36 months) full-time or 6 years (72 months) part-time with an optional submission pending (writing-up) period of 12 months.

Sometimes it may be possible to mix periods of both full-time and part-time study.

If studying on a part-time basis, you must establish close links with the University and spend normally not less than an average of 10 working days per year in the university, excluding participation in activities associated with enrolment, re-registration and progression monitoring. You are also expected to dedicate 17.5 hours per week to the research.

Application deadlines

For September/October 2024

07 June 2024 for International and Scholarship students

28 June 2024 for Home students

For January 2025

18 October 2024 for International and Scholarship students

15 November 2024 for Home students

For April 2025

24 January 2025 for International and Scholarship students

21 February 2025 for Home students

About the research degree

A PhD is the highest academic award for which a student can be registered. This programme allows you to explore and pursue a research project built around a substantial piece of work, which has to show evidence of original contribution to knowledge.

Completing a PhD can give you a great sense of personal achievement and help you develop a high level of transferable skills which will be useful in your subsequent career, as well as contributing to the development of knowledge in your chosen field.

Our research degrees are available as full-time, part-time and some are offered distance learning.

You are expected to work to an approved programme of work including appropriate programmes of postgraduate study (which may be drawn from parts of existing postgraduate courses, final year degree programmes, conferences, seminars, masterclasses, guided reading or a combination of study methods).

This programme of research culminates in the production of a large-scale piece of written work in the form of a research thesis that should not normally exceed 80,000 words.

You will be appointed a main supervisor who will normally be part of a supervisory team, comprising of up to three members to advise and support you on your project.

Entry requirements

The normal level of attainment required for entry is:

  • A Master’s degree or an honours degree (2:1 or above) or equivalent, normally with a classification of merit or distinction, in a discipline appropriate to the proposed programme to be followed, or appropriate research or professional experience at postgraduate level, which has resulted in published work, written reports or other appropriate evidence of accomplishment.

If your first language is not English, you will need to meet the minimum requirements of an English Language qualification. The minimum for IELTS is 6.0 overall with no element lower than 5.5, or equivalent. Read more about the University’s entry requirements for students outside of the UK on our Where are you from information pages.

Why choose Huddersfield?


There are many reasons to choose the University of Huddersfield and here are just five of them:

  1. We were named University of the Year by Times Higher Education in 2013.
  2. Huddersfield is the only University where 100% of permanent teaching staff are Fellows of the Higher Education Authority.
  3. Our courses have been accredited by 41 professional bodies.
  4. 94.6% of our postgraduate students go on to work and/or further study within six months of graduating.
  5. We have world-leading applied research groups in Biomedical Sciences, Engineering and Physical Sciences, Social Sciences and Arts and Humanities.

What can I research?

There are several research topics available for this degree. See below examples of research areas including an outline of the topics, the supervisor, funding information and eligibility criteria:

Outline

The project looks at using inverse problem approach to develop turbo-machines such as compressors, turbines and pumps for better efficiency, operation and reliability. State of the art numerical, analytical and experimental techniques will be used for such purposes.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

Crime scene reconstruction is a forensic science discipline in which one gains explicit knowledge of the series of events that surround the commission of a crime using deductive and inductive reasoning physical evidence scientific methods and their interrelationships. This programme aims at investigating innovative forensic imaging techniques for producing accurate reproduction of a crime scene or an accident scene for the benefit of a court or to aid in an investigation. The programme will start from reviewing the state-of-the-art of 3D imaging techniques such as Augmented Reality and stereoscopy for creating or enhancing the illusion of depth in an image. The research will then propose innovative 3D imaging approaches based on photogrammetry theories and recent developments in remote sensing technologies for the acquisition and understanding of accurate and reliable measurements of a diverse range of natural and manmade structures including underground disturbances. The research encompasses scientific disciplines including image networks and sequences vision metrology laser scanning and range imaging as well as 3D modelling and interactive visualisation. The research output is anticipated to benefit forensic applications such as stockpile monitoring and underground abnormality detection.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

This research project will seek to explore and redefine the state of the art in intelligent audio monitoring for both fault detection and fault prediction in and out of the smart home environment. Research will be undertaken that will explore and extend the current methods of audio capture with a view to enabling low cost, non-intrusive real-time 3D sound field analysis and modelling.

Audio event classification often works very well if presented with audio similar to the training sets provided but tend to underperform in less-than-ideal listening environments. AI will play a crucial role in improving performance and will feature heavily in the research project.

Noise ingress and sound source monitoring/detection within the smart home environment will enable optimisations to be made with respect to build mechanisms and usage. Services (Gas, Water, etc.) and appliance audio monitoring solutions will be explored which will result in a complete audio / time signature of the home to be created, both in terms of energy usage, fault prediction and detection.

The project will focus on methods in which audio can be captured, in particular on low cost / low power distributed and connected methods. Cloud utilisation will enable the exploration of condition monitoring and control remotely. The project will look to extend the methods explored to wider use, for example, remote monitoring and fault diagnosis of plant systems.

The advent of low power but highly optimised processing devices now enables edge-based processing of audio to be performed. This greatly reduces throughput of data, offers much better price/performance, and offers greater accessibility at lower cost. This combined with the ability to connect smart audio devices remotely allows for huge potential in their usage to support and predict service usage, appliance usage and potential faults.

Current 3D mapping of acoustic spaces is generally performed with specialist and expensive equipment. The proliferation of low power transducers combined with the rise in edge-based technology opens up the possibility of more intelligent solutions that offer greater depth of data to the end user.

Conducting this study in the Smart Home facility will be essential to ensure the ecological validity of the result from the study. Real world data with respect to audio capture, response, processing would all be possible in a controlled but relevant scenario.

The Huddersfield Smart House Research Facility is being developed as a collaborative hub for industry, academia and government organisations. It is being developed to accelerate research and development for smart products and services to be used in the building environment with an aim to bring transformational improvements in key performance indicators corresponding to 21st century houses and living conditions. For this purpose, a well instrumented two storey dwelling is being constructed that will provide facilities for a range of novel and innovative investigations to be carried out.

Smart technologies can help us in reducing carbon footprints as well as having positive energy balance through improved energy performance of homes and buildings. We can achieve greater energy efficiency, cut carbon emissions and support more intelligent and flexible management of energy supply and demand. By incorporating use of smart technologies, the health and wellbeing can be significantly improved through better management of internal environments, safety and security. Smart technologies have potential to offer significant improvements in wellbeing of the occupants by allowing control through voice and mobile apps as well as using automation and artificial intelligence to support and predict our changing needs.

HSHRF aims to bring researchers, practitioners, industries and government organisations together to design, develop and implement holistic solutions to current and future societal challenges associated with building environment and its use.

Funding

Please see our Scholarships page to find out about funding or studentship options available.

Deadline

Supervisors

How to apply

Outline

The project will develop an artificial intelligent (AI) monitoring approach based on Convolutional Neural Network(CNN). Rather than conventional vibroacoutic data, remote thermal images will be used as the main input to map to the CFD analysis results, such a model can be more generic as the data more robust to various uncertainties such as the noise and signal paths in vibration measurements. Once the CNN model is calibrated with both experimental and CFD datasets under various operating conditions of a machine, it can be implemented online for abnormal detection, and then aided by CFD analysis to identify the fault sources and severity offline, thus leading to engineering interoperations of the AI results and wide generalisation and advancements of AI algorithms in the fields of condition monitoring. Pumps and compressors, which are of main equipment in different process industries, will be based on to develop such AI based digital twin monitoring system.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

The increasing concern over global climate change and local environmental pollution necessitates the development of fossil-free transportation solutions. Hydrogen fuel cell electric vehicles (FCEVs), known for their fast refuelling time and zero emissions, have emerged as a viable solution for achieving Net Zero. In the FCEV traction system, the fuel cell pack supplies DC power, which is converted to AC power by a power electronic inverter to drive the traction machine. Each fuel cell typically produces less than one volt of electricity; thus, hundreds of cells are connected in series to produce the required output voltage (400V – 700V) for the traction machines in current FCEVs. However, this series connection of fuel cells often results in balance issues. If one stack underperforms, the current in that branch is affected, leading to reduced power. Moreover, voltage imbalances in fuel cells can cause overvoltage or undervoltage conditions, potentially damaging the cells.

Therefore, the project aims to develop a novel permanent magnet machine with salient pole shoe rotors designed for a low voltage supply (300V or less) without compromising overall performance. The innovative salient pole shoe rotor design enhances the field weakening capability of the machine, reducing the voltage requirement. Consequently, the number of series-connected fuel cells can be significantly reduced, mitigating balance issues.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

Conventional measurements such as shaft encoder based instantaneous angular speed (IAS), contact accelerometer based translational vibrations often suffer from poor signal to noise ratio and high cost for deployment. Recent advancement in high speed cameras offer opportunities to visualise the dynamic behaviours of rotors in both rotational and translational directions, leading to a wealthy of information for diagnostics with more cost-effectiveness. The project will focus on developing techniques to extract relative diagnostic information of a rotor based on images from high speed cameras. Both a first law model and an artificial intelligent (AI) model will be investigated to gain the dynamic behaviours of images under various common faults for both linear and nonlinear rotors. The model residuals between the two models will be used as the references for online fault detection and diagnostics.

Low speed Wind turbine, marine power trains, cranes, and compressors in different process industries will be the targeted applications in terms of the digital twin monitoring system.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

Wind farm efficiency is somewhat determined by turbine efficiency, which in tum depends upon wake effects. Turbines situated wholly or partially in the wake of leading turbines are severely restricted in their efficiency, according to size, wind speed and direction and spacing between turbines. The aim of the project is to create a semi-analytical model of air flow behind a horizontal axis wind turbine, principally for use by wind farm designers in the industry. Current models are either too crude to be of certain value or too sophisticated (or time­ consuming) to be incorporated into iterative turbine placement design schemes or software. The most common and crudest model still in use was devised in 1983. Applicants will need a sound Mechanical or Energy Engineering background and a good understanding of the near field aerodynamics of a horizontal axis wind turbine. The project requires a very numerate approach and a good background in applications of mathematics would also be required. For calibration and validation of the model a number of simulations using Computational Fluid Dynamics will be necessary and applicants should be well versed in this type of work, preferably using ANSYS Fluent or similar software.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

The project will investigate the intelligence for the diagnosis of the abnormal machinery in different processing industries such as petrochemical and steel production lines, which are often of a large-scale with multiple machines and high risk environments.

A robot with airborne acoustic arrays will be developed to build a cost effect monitoring platform for such scenarios. Specifically, the arrays will be automatically tuned for different purposes. When the robot patrols in a defined route the array will be configured automatically with large dimensions to scan large area for abnormal sounds. Once an abnormal sound is detected the array will be reconfigured based on sound directions and spectrum so that the acoustic information can not only direct the robot to move closer to the abnormal sources but also adaptively refine the information to identify the root and cause of the faults detected. The key technologies will be researched in the directions of sound beam forming, wavelet based denoising, cross modulation spectrum analysis and intelligent algorithms along with the new advances in the topic of indoor robot positioning.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

The research project is to develop ultra-precision manufacturing with embedded on-machine measurement system to the fabrication of functional surfaces. The machining technologies can be developed based on one of the following methods including single point diamond turning , fast-tool-servo, fly cutting and micro milling. The functional surfaces to be machined are free from and/or structured surface with various applications in optics. A typical case study will be focused on the fabrication of optical lenses. Simulation work will also be carried out in this project to find the optimised processing parameters. The selected PhD student will be trained to operate machine tools and other related measurement equipment.

The application must have MSc research degree on mechanical engineering/informatics or will receive his/her MSc degree before they start the PhD study in September. The applicant should have education background/working experience on metal cutting or control system and have publications (conferences/journals, paper/books chapter) in this research area.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

Temperature measurement plays a vital role in many manufacturing and industrial applications. Most temperature monitoring is done through contact temperature sensors mounted on the surface of the object or thermopiles monitoring the surface of the part non-contact. As part of the EPSRC-funded Future Metrology Hub, The Centre for Precision Technologies (CPT) has developed an accurate method of measuring core temperature of metal during manufacturing using acoustic thermometry. It uses the principle of time-of-flight and/or phase-shift by reflecting soundwaves from discontinuities (the edge) of a workpiece. This method gives a measurement value representing the average internal temperature of the part and has been proven for a monolithic cuboid. However, in some situations the absolute temperature of a region, rather than the entire workpiece, is of interest. Furthermore, workpiece geometry will change during machining operations or through additive layer deposition. The initial assumption of path length, used in the existing method, may therefore not be sufficiently accurate.

This project will build upon the successful proof-of-concept to enhance the instrumentation hardware to be able to focus measurement on one or more regions of interest within the part being manufactured. It will also develop and validate the necessary data processing tools to obtain temperature for varying geometries and further to calculate the resultant change in geometry due to thermal expansion.

Although targeted at measurement of metallic parts being manufactured, the method created within this project can in the future be used in many different applications where the internal temperature is of interest for other manufacturing methods, such as forming, or condition monitoring.

The project is supported as part of a centre of excellence working on metrology (the science of measurement) for manufacturing, with opportunities both to bench-test and to validate on industrial CNC machine tools.

The core temperature measurement method to be developed will enhance the accuracy of the manufacturing process thereby reducing the cost of manufacturing by reducing scrappage and time lost to rework.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

Through previous collaborative research a novel electron beam, powder bed Additive Manufacturing (AM) process has been developed. The new process has significant commercial (mass of material processed per hour) and technical (very broad process window allowing material microstructure control and in-process monitoring for quality assurance) benefits over current e-beam and laser based powder bed systems available on the market today. The new technology patented as NeuBeam is capable of neutralizing the charge accumulation that tends to occur with other electron beam technologies such as electron beam melting (EBM). This results in potentially a wider range of viable print parameters when compared to other electron beam or laser-based PBF technologies. The NeuBeam Technology is new and its full potential for processing Ti alloys has yet to be established. In order for it to become accepted in the market, material studies are needed to validate the claims and explore the boundaries and capabilities of this exciting technology. This validation work will be a core part of the proposed PhD. The novelty of the work lies in the application of the new processing technology to Ti structures with complex geometries and lattice structures as well as the prospect of manipulation of the AM part microstructure. End users (in the aerospace and medical implant fields) are very interested but need to see validation of the technology in terms of material properties.

The program of work will cover exploring the optimum process parameters of the NeuBeam technology to: 1. Optimise NeuBeam processing rates for Ti alloys 2. Optimising NeuBeamTi part density as assessed using X-ray Computer Tomography 3. Controlling part surface topography 4. Demonstrating control of Ti part microstructure and minimising thermal cracking using NeuBeam techniques 5. Investigate the mechanical properties of part obtained by NeuBeam AM 6. Exploring the production of fine lattice structures beyond the scope of conventional E-Beam AM using NeuBeam methods.

This project is a partnership between the EPSRC Future Metrology Hub and Wayland Additive Ltd. Wayland Additive is a very young start-up company that has formed from seed R&D carried out by Reliance Precision Limited. Significant periods of study will be spent at the sponsoring company which is less than 5km from the University The company will provide an additional top up to any bursary associated with the project to the tune of £1000 pa.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

The development of co-simulation procedures has led to the development of sophisticated numerical dynamic analysis tools. These are able to couple two different simulations or more, running alongside each other. Such methods allow for the study of more complex systems by coupling different sub-systems or coupling different phenomena in the same system. The aim of this work involves the study and investigation of co-simulation methodologies and its application in numerical dynamic analysis tools. Different approaches are to be implemented and tested under a series or different case scenarios and benchmarks. The final objective of this work includes the development and implementation of a new co-simulation framework on a state-of-the-art Pantograph-catenary dynamic analysis tool. This is able to handle the numerical analyses of pantograph-catenary interaction, where the pantograph is modelled as a multibody system in interaction with finite element OLE model.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

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Outline

In the domain of Electronic Dance Music (EDM), spatial audio technologies have found extensive utilization within mainstream pop and rock genres. However, their incorporation into EDM, particularly within prevalent and commercial subgenres such as tech house, trance, techno, progressive house, and drum and bass, remains at an incipient stage of development. Recent advancements in spatialization tools and technologies have ignited considerable interest within the music industry, promising an elevated and immersive auditory experience. This research project positions itself at the forefront of addressing this differential adoption, with the objective of making substantive contributions to the advancement of music production and performance practices within the EDM genre.

The study will involve the following work: 1. Content analysis of existing professional tracks to identify prevalent techniques and trends in mainstream and commercial styles of EDM. 2. Conducting interviews with professional producers to gather first-hand insights into the evolving landscape of spatial EDM. 3. A practice-based exploration phase where the researcher will experiment with spatial audio technologies in EDM production. 4. Development and execution of experimental research to gather robust data on spatial audio production in EDM. 5. Creation and evaluation of artefacts demonstrating the potentials of spatial audio in EDM.

The supervisory team is comprised of members from the CAPE research centre, including experts from a leading research area in spatial audio research. One of the team members also has a background in EDM production and maintains professional links in the industry. The project will build upon the experiments of CAPE and apply them in ecologically valid scenarios within EDM music production. The candidate will have access to state-of-the-art music production facilities equipped with spatial audio speaker configurations and a designated spatial audio critical listening space adhering to ITU standards.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

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Outline

The focus of the project is associated with the advancement of distance-based health and wound care monitoring systems. The project aims to explore, exploit, and produce new/emerging technologies, particularly those identified as having the potential for being used in health care (wound/condition) monitoring and to combine these with novel and intelligent application. Thus, increasing the health and well-being and QoL of patients, whilst also aiming to reduce cost in the health-care sectors.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

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Outline

Pantograph-OLE Interaction plays a fundamental role in the traction of electric railway vehicles. The sliding contact between the overhead line and the pantograph contact strips must be as smooth as possible and uninterrupted. The study of this interaction under aerodynamic loads has become a key factor on the development of new overhead lines and current collection systems. The employment of numerical dynamic analyses tools to study pantograph-OLE interaction is now being accepted by the industry, as these types of software are becoming more reliable and accurate. Though, added model complexity is sought after in order that more complex problems can be analysed. One of these aspects is the inclusion of aerodynamic effects in these types of numerical studies, which today have an impact in the design of new pantographs and overhead line systems. This work aims to study the aerodynamic effects on the pantograph and the overhead line, and the development of a modelling methodology to include them in pantograph-OLE interaction numerical analyses. These methodologies are to be incorporated in a state-of-the-art dynamic analysis tool already developed, so its capabilities are augmented.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

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Outline

The provision of cost-effective systems for meeting the distributed electricity generation needs is one of the research and innovation challenges. Here, one of the key requirements is the development of systems that would work for prolonged periods of time without the need of frequent maintenance, and ideally would utilise renewable energy sources such as solar energy. One of the possible technical solutions is the application of the novel emerging technology, with a significant future potential, referred to as “Thermoacoustic Technology”. This offers efficient energy conversion mechanisms without the need for any moving parts. This project will investigate the provision of distributed electricity generation for either industrial or domestic applications by using the coupling between a solar power driven “thermoacoustic engine” (which produces high density acoustic energy out of a solar-thermal input) and an energy converter referred to as a "linear alternator" for producing electrical power from an acoustic input. In general, the underlying thermoacoustic effect relies on the energy transfer between a compressible fluid and a solid material in the presence of an acoustic wave, and produces energy conversion mechanisms similar to those present in Stirling cycles. However, a thermoacoustic cycle is realised without expensive hardware associated with classical Stirling devices. The project will utilise an existing experimental apparatus to demonstrate the application of solar energy input for producing the electrical output in realistic working conditions.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

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Supervisors

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Outline

Forensic investigation is underpinned by Locard’s exchange principle: ‘every contact leaves a trace’. In the case of toolmark investigation, this contact results in a plastic deformation of the substrate material which is used to determine the likelihood of a certain tool having been used in a crime. Current examination of toolmarks relies on either greyscale imaging comparison techniques or comparison of 2D profiles gained using areal measurement techniques. There has been no published research regarding the use of the entire surface topography for the comparison/ correlation of toolmarks. The project would focus on: • Determining the characteristics of toolmarks and the best practice for measurement of the topography • Exploring casting techniques used when the toolmark cannot be transported to the lab (i.e. doorframes) and the effect of casting on the fidelity of the replica • Applying correlation techniques to the areal surface • Analysing possible error rates in investigation

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

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Supervisors

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Outline

Techniques exist for automated measurement of wheel wear and diameter reduction, and have been used in previous research to support wheelset maintenance decisions. However, other types of wheel damage (such as rolling contact fatigue or sub-surface cracking) still relies on manual or visual inspection. Information on the severity of these other types of damage mechanisms would allow improved optimisation of wheelset maintenance. This research will review existing technology used to detect these damage mechanisms and how they can be applied in railway environment.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

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Supervisors

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Outline

Accurate portrayal of optimal system behaviours and identification of fault characteristic behaviours form the basis of process control through condition monitoring. Anomalies identified at onset may be controlled without catastrophic interference to process quality and production interruptions may be reduced or completely avoided. Continuous on-line monitoring of processes replacing scheduled time-based maintenance routines. Multivariate modelling of system behaviour during normal healthy operation and with induced abnormalities affords tolerance setting for early detection of deviations. Pattern recognition technologies give insight into operational behaviours from which rule based models are determined. The aim of this project is to develop robust methodologies for online measurement and assessment of system health and operational capabilities.

Funding

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Deadline

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Supervisors

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Outline

The proposed research aims at investigating the properties of heterogeneous mixtures which are common in many industries including chemical, oil and gas, pharmaceutical, minerals, food, biotechnology and others. Characterisation of such mixtures is crucial for controlling the industrial processes as well as ensuring high product quality. During the research, suitable non-invasive and on-line measurement techniques, based on the combination of electrical impedance spectroscopy and ultrasonic transmission, will be developed. In the first stage, design and laboratory studies leading to construction of robust sensors to facilitate measurements in a selection of industrially relevant situations will be conducted. The measurements will be validated using independent techniques. The second stage will focus on modelling the propagation of the sensing fields which interrogate the mixtures and their interaction with the dispersions. The modelling will be conducted using a commercial package, FEMLAB, and will lead to construction of mathematical models predicting the sensor behaviour. (Industrial relevance: chemical, bio-technology, process, petroleum, chemical, food and drink)

Funding

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Deadline

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Supervisors

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Outline

A prilling tower is an integral part of any fertilizer plant. A hot fluid (normally urea) is sprayed from a nozzle at the top of the tower forming droplets of urea. These droplets fall under the action of gravity, releasing their energy content, and hence, forming solid prills of urea, which is extensively used as a fertilizer. It is often seen that a lot of the prills formed at the base of the tower doesn't have enough strength to remain in the form of a prill; hence, they disintegrate into powder, wasting an excessive amount of the product. This happens because of ineffective cooling in the tower. The current research work will look into the dynamic of vortex rings for effective cooling purposes within a prilling tower. Vortex rings are inherent in nature and have been a topic of interest for almost a millennium. The urge to utilise vortex rings for multi-purpose applications, such as in cooling of urea droplets in a prilling tower, has led to the development of various types of vortex rings. However, in-depth analysis of the flow phenomena associated with vortex rings is still very little known. This study will investigate the dynamics of a vortex ring's generation, propagation and its ultimate dissipation within a prilling tower. The effect of the geometrical, flow and fluid parameters on the rolling-up of the fluid's shear layers will be analysed using a number of analytical, experimental and numerical techniques. It is expected that this study will result into a practical device that can be installed on the top of the prilling tower, which can enhance the cooling process, hence substantially reducing the waste powder.

Funding

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Deadline

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Supervisors

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Outline

Biochar is a charcoal-like material derived through controlled pyrolysis, a process involving the combustion of organic materials like forest waste (biomass) and agricultural residues. It manifests as a black, finely-grained, highly porous, and lightweight substance, characterized by a substantial surface area, primarily consisting of 70% carbon. Additionally, biochar incorporates nitrogen (N), hydrogen (H), oxygen (O), calcium (Ca), potassium (K), and various other elements. The extensive surface area and the presence of diverse polar and nonpolar groups enhance its attraction to inorganic ions, including heavy metal ions, phosphate, and nitrate. Biochar serves various purposes, including its capacity to retain water and nutrients in the upper layers of soil for extended periods, providing agricultural benefits by minimizing nutrient leaching from the crop root zone. This has the potential to enhance crop yields and decrease the need for fertilizers. The utilization of biochar is estimated to annually capture a substantial amount of greenhouse gases, approaching a gigaton, and applying biomass and biochar for carbon neutrality could potentially reduce global emissions by nearly 10%. With a heterogeneous char structure and the presence of catalytically active inorganic species, biochar becomes a valuable component in thermal conversion processes and qualifies as a low-rank fuel. Moreover, biochar can function as an effective adsorbent for eliminating diverse pollutants in water and wastewater. This discussion predominantly focuses on its application in removing heavy metals, organic contaminants, nitrogen, and phosphorus. The chemical makeup of biochar is influenced by factors such as the feedstocks employed, the pyrolysis technique, and the production temperature. As the pyrolysis temperature rises from 300 to 800 °C, there is an augmentation in carbon content. Conversely, this temperature increase results in a decline in other elemental contents, notably nitrogen (N) and hydrogen (H) This project aims to characterize the composition of biochar produced from various feedstocks to match suitable feedstock with specific biochar applications. Subsequently, the focus includes improving feedstock and adjusting pyrolysis conditions to control biochar composition, ultimately enhancing the quality of biochar based on its intended applications. For example, the surface area of biochar varies widely, influencing its potential applications. Factors like feedstock type, pretreatment, process conditions, ash presence, and activation method impact porosity. Analysing post-pyrolysis samples is crucial to determine surface area and pore size distribution, revealing the optimal application for the sample. Another aspect of the project will concentrate on employing biochar as the feedstock for a gasifier unit and assessing the resulting gas to determine its viability as an energy source.

Funding

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Deadline

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Supervisors

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Outline

The micro-climate surrounding wounds can influence the healing rate, in chronic wounds and hard to heal wounds, managing fluids surround the area is critical to improvements in healing and skin integrity. Computational modelling techniques such as Lattice Boltzmann method can offer insight into the meso-scale multiphase dynamics in porous media which could be used to manage fluids at the wound site. The project will involve working with a multidisciplinary team of engineering and clinical academics to provide novel solutions to optimise wound dressings and other medical devices for wound healing. This would have a positive impact on health related outcomes for people with hard to heal, chronic or complex wounds.

Funding

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Deadline

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Supervisors

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Outline

Areal surface texture parameters can be used to comprehensively, and quantitatively characterise surfaces and surface interactions. These techniques are used in a variety of industries as a predictor of function and performance for engineering surfaces, as a measure of quality and also as a forensic tool to analyse wear and failure of engineering components.

With advanced filtering and characterisation techniques, it is possible to characterise surfaces such that the exact manufacturing operation used to create them can be determined. Using similar techniques, the aim of this project is to develop a model to determine the type of interaction causing skin damage for forensic investigation.

The key objectives of the project are to: • Optimise measurement methodologies for areal surface characterisation of skin and skin damage. • Develop an experimental methodology to simulate skin damage through controlled interaction with a range of media. • Using data extraction techniques, determine the relationship between media interaction and resulting skin damage. • Provide a tool for characterisation skin damage with a view to pinpointing the source of damage.

The provision of a non-contact, rapid methodology for measurement and characterisation which enables forensic scientists to determine skin interaction during incidents resulting in injury could be beneficial in investigations and contribute to more secure safer societies.

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In recorded and mixed form, the history of metal music has involved a broad focus on achieving greater heaviness (Berger & Fales 2005). Importantly though, there is a broad lack of detailed understanding of what heaviness actually is. Changes in performance approaches (especially performance speed), levels of down-tuning - and aspects such as design developments in guitar and bass amplifiers - have impacted our perceptions of heaviness. However, regardless of how these characteristics might or might not inform a given production, a valuable parameter of effective heaviness is clarity. “Sonic clarity can enhance the energy, intensity and impact of each and every sound in a metal production, collectively strengthening the power and drive of the music’s rhythm structures.” Mynett, 2016. With this in mind, by focussing on the mix stage of the music production process, this project sets out to gain a detailed understanding of the correlation between heaviness and clarity.

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The aim of this project is to research the efficiency of FPGA computing compared to CPU/GPU computing, using a novel approach in the form of cross-platform implementation using OpenCL.

OpenCL aims to remove the difficulties that lie within cross-platform programming by using a framework that allows a single design to be implemented on either CPU, GPU, DSP or FPGA. It also encourages the use of heterogeneous systems (for example CPU+FPGA) to improve development time and performances.

The proposed approach is to investigate the efficiency of the CPU, GPU and FPGA platforms through the use of typical distributed computing applications within the fields of engineering and science, with emphasis on computation time, overall development time and energy consumption.

In this project resources available in the School of Computing and Engineering will be used: QGG Campus grid, CPU and GPU clusters, and FPGA hardware, with possible access to Hartree centre - Maxeler FPGA equipment.

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A hardware security primitives is a physical computing device that provides hardened, tamper-resistant hardware-based cryptographic security. True Random numbers find applications in a variety of fields, including cryptography, to provide security in modern systems for confidentiality, authentication, electronic commerce, etc. This work will explore the development of a digital system to generate random numbers that are synthesized and implemented on an FPGA device using stochastic algorithms. The student needs to design algorithms for generating random numbers. The algorithm needs to be neural network-based, designed using hardware description language (HDL), and implemented on the FPGA. The generated random numbers need to be collected back to the computer for analysis. NIST statistical tests need to be used to prove of the quality of randomness.

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According to Darwin’s Origin of Species, it is not the strongest of the species that survives, nor the most intelligent that survives, it is the one that is most adaptable to change. Various species have developed special skin (surface) textures in order to survive. For example, setae on geckos’ toe-pads help them stick to walls (adhesion), the rough structure on lotus leaves keeps them dry and clean (superhydrophobicity), scales covered on shark skin allow them to swim faster and more efficiently (drag reduction), etc. Functional structured surfaces have also been applied in novel products across multiple industrial sectors, including bio-medical, energy, sports, etc. The superior functionalities brought by structured surfaces will play an important role in the next generation of high-value-added functional products.

The design of bio-inspired functional structured surfaces is still driven by imitation currently. The performance of the designed surface is affected by many factors, such as the shape, size, orientation, and distribution of features. However, there is a lack of understanding of how these properties will affect the functionality of a structured surface. Both experimental tests, such as measurement of friction coefficient, contact angle, etc., and simulation, such as computational fluid dynamics (CFD), are essential methods to optimise the design.

Many production methods, such as fast-tool-servo (FTS), micro-milling, micro-grinding, ultra-short pulse laser and roll-to-roll, etc. have been developed for the fabrication of functional structured surfaces. The choice of the production method is highly dependent on the surface design, material and desired accuracy. However, the mass production of structured surfaces is still hindered by the high fabrication cost. The combination of multiple processes can be a promising solution.

The proposed PhD project will investigate the design and fabrication of ultra-precision structured surfaces with required functionalities for novel products with high-value-added functional products that are used across multiple industrial sectors, including bio-medical, energy, sports, etc. The objectives of this project include: • Explore the optimal design of structured surfaces for a particular functionality with consideration of manufacturability. • Develop optimized fabrication methods for the designed surface. • Test and validate the designed surface.

The Ultra-precision Manufacturing Lab at the University of Huddersfield has state-of-the-art facilities to advance this exciting research, such as the world’s most advanced ultra-precision diamond turning machines (capable of FTS, micro-milling, micro-grinding), and high-performance workstations. The researcher will also have access to various metrology instruments, including surface profilometer, XCT, CMM, SEM, etc.

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Ultra-precision diamond machining including turning, milling and various tool servo-based machining processes enables the adventurous design and fabrication of freeform surfaces of nearly arbitrary complexity. To achieve this, it requires the accurate transformation of optical functions to surface geometrical specifications, and the dynamic conditions encountered in machining process must be predicated and well controlled.

The aim of this PhD research project is to broaden the knowledge of design and manufacture of freeform surfaces in novel optical materials. A systematic research work will be conducted on freeform manufacturing such as optical function design, machining process modelling and optimisation, surface integrity and quality control. In particular, to overcome the limitations of conventional CAD&CAM packages on freeform optics, an analytical strategy will be developed for optical functional design, toolpath generation, pre-process error mapping and compensation of tool servo-based machining operation errors. Case studies will be designed and carried out to demonstrate the capability of developed machining technologies, for example the manufacturing and functional test of several freeform optics such as focus tunable lenses (e.g. Alvarez lens pair) and multiple freeform optics (e.g. the primary and tertiary mirrors of an imaging spectrometer).

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This project addresses fundamental challenges of designing and optimising heat exchangers to be applied in the oscillatory flow conditions. These types of conditions are common in devices such as Stirling engines/coolers or thermoacoustic engines/refrigerators or air conditioning systems. The former is often found in cryogenics applications, the latter could be used as low-cost and low-maintenance technology for solar-driven power generation or air conditioning in the Middle-East. A common feature of such applications is a cyclic flow reversal and the associated hydrodynamic energy transfer, which is an integral part of the underlying thermodynamic cycle. In the classic heat exchanger analysis, the heat transfer correlations are derived for steady flows, but unfortunately these correlations do not work for oscillatory flows and so there is a gap in understanding the heat transfer (and fluid flow) processes and lack of reliable design guidelines. This project will focus on a mixture of experimental and modelling approaches to tackle these issues.

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This project is in the area of Thermoacoustic Technologies that deal with designing engines and refrigerators (heat pumps) with no moving parts. In refrigerators, an acoustic wave present in a thermoacoustic stack (or regenerator), which can be imagined as a series of narrow passages, imposes pressure and velocity oscillations, with a relative phase difference, enabling the compressible fluid to undergo a thermodynamic cycle similar to the Stirling cycle. This, coupled with appropriately phased heat absorption and release, enables “pumping” heat from the cooler to the hotter end of the stack (or regenerator) with no need for cranks, sliding seals or excess weight normally associated with conventional Stirling machines. A reverse process of establishing an acoustic wave due to the strong temperature gradients in the stack (regenerator) forms a basis for the operation of “thermoacoustic engines” – the useful acoustic power being extracted by the appropriate linear alternators. The aim of this project is to utilise the thermoacoustic principles described above in the design of a miniature thermoacoustic coolers that would be used for localised cooling of electronic components, such as for example computer processors.

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Additive manufacturing (AM), moving from a prototype and pilot technology into a mature manufacturing technology, has the potential to change the paradigm for manufacturing. AM will play a significant role in shaping the future of manufacturing towards a flexible and on-demand approach and accelerate the transformation from the conventional manufacturing industry to Industry 4.0. Despite continuous enhancements of AM systems, the lack of process repeatability and stability still represents a serious barrier to industrial breakthroughs. Consequently, various disruptions (e.g., layer warping, and weak infill) occur during and propagate through layer building, exerting detrimental impacts on the building process and product quality. In-situ measurement techniques and closed-loop control have been identified as vital factors for robust control of AM processes. However, their major limitations are: (1) measurement sensors are insufficient in meeting the requirements of the in-situ measurement of AM layers; (2) data analysis methods are not robust and/or accurate enough to extract all existing layer anomalies; and (3) lack of advanced closed-loop control that could take the monitoring information to handle layer building disruptions. The main goal of this project is to create an intelligent metrology platform to enable a resilient AM system with the capability of process self-optimisation. The specific research objectives are (1) construction of in-situ multi-sensors (optical camera, infrared camera, laser scanner) that are capable of capturing layer build information with high precision; (2) investigation of machine learning based data analytics that can detect, classify and quantify critical layer defects quickly and accurately; and (3) exploration of a digital twin based control framework that can respond to and learn from the detected defects and allow process self-optimisation actions to be taken.

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Applications are invited from suitably qualified graduates for a fully funded PhD studentship (3 years) for Renishaw/Royal Academy Research Program within the EPSRC Future Manufacturing HUB for Advanced Metrology. The EPSRC HUB sets out to create ground breaking embedded metrology and universal metrology informatics systems to be applied throughout the manufacturing value chain as an essential tool to achieve significant growth and productivity gains in UK manufacturing.

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The project involves development of an integrated numerical model of the various processes taking place during the additive manufacturing (AM) process such as melting and solidification, fluid flow, heat transfer, vaporization, radiation and wetting. Currently several aspects of AM process require repeated trial and error operations to meet stringent quality control requirements in sever service applications resulting in wastage of time and effort. Development of an accurate numerical model will enable parametric investigation to be carried-out enabling reducing trial runs significantly. In addition the numerical model will enable establishment of quantitative dependence of the build quality with manufacturing process parameters.

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Infrastructure systems consist of a number of sub-systems carrying a wide variety of solid-liquid-gaseous materials. Failure of one of the sub-systems may result in release of these materials in an uncontrolled manner. Risk mitigation strategies need to be designed keeping variety of leak scenarios. Furthermore, an array of sensors is needed to provide dispersion characteristics through a well-developed formulation. The information provided through such methods is limited in scope and accuracy in the present work a CFD based solution algorithm will be developed that integrates pre-developed flow scenarios with sensor array information to provide qualitative and quantitative pollutant dispersion characteristics. The developed system will be capable of informing real time pollution dispersion characteristics and will help in developing risk mitigation strategies.

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Device related pressure ulcers can occur when there is physical interaction between the body and a surface which exerts pressure on an area of the skin. The resulting damage and loss of integrity in the skin gives rise to at best pain and discomfort for the patient but also the possibility of infection and further damage, in extreme cases this can result in serious illness or death.

There are a range of common instances where this may be an issue, interaction with medical devices such as oxygen delivery systems, cannulas and other critical therapeutic technologies is a particular issue where the therapeutic is preserving or supporting life. It can also occur due to the use of monitoring equipment which comes into contact with the body, either due to its function or as a result of its placement and environment. In order to better understand the mechanicals of device related pressure ulcer development and generate a body of knowledge allowing avoidable device related pressure ulcers to be eliminated, this project seeks to use numerical modelling (e.g. finite element analysis) and mechanical testing to develop a tool to simulate the mechanics of device related pressure ulcers.

The key objectives of the project are to: • Develop a greater understanding of the properties of skin and underlying tissue. • Investigate the nature of contact contributing to device related injury • Develop a computational model to simulate the pressure, shear and friction which occurs during device/skin contact. • Develop an understanding of the influence of device design and material on the risk factors for pressure ulcer development.

The provision of a working simulation will enable device developers to have a better understanding of how to ensure devices minimise the risk of pressure ulcer development and also provide enhanced guidance to healthcare professionals in the use and placement of devices. This could have a significant positive impact on the quality of life of patients through improved care. It would also impact on KPI’s for healthcare providers in minimising the prevalence of avoidable device related pressure injuries and the associated complications.

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Optical coherence tomography (OCT) is currently recognised as the gold standard for identifying structural retinal abnormalities in ophthalmology. Due to its ability to acquire fast, highly sensitive in vivo cross-sectional images of the histologic layers of the retina, OCT is an excellent screening tool to use to detect retinal pathology.

As a functional extension of OCT, polarisation-sensitive OCT (PS-OCT) can improve the image contrast of OCT by imaging birefringence of ocular fibrous tissues and has been used to segment and observe retinal pigment epitheliums along with some unique feature of retinal diseases. However, the cost of commercial PS-OCT systems (up to £12k) has limited access to this technology to mostly large eye centres and laboratories in the developed world. We will choose and integrate the latest cost reduction approaches developed for OCT technology to pursue a low-cost PS-OCT system to increase patient access, particularly in low-cost settings.

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Pressure Ulcers (PU) occur when skin is subjected to pressure shear and friction in certain conditions. These pressure ulcers can occur when there is contact between any surface and an area of skin, usually, but not always a bony prominence. Pressure ulcers are skin damage which cause a loss of integrity at the skin interface and can give rise to serious complications such as necrosis and infection. This project seeks to provide a fundamental understanding of interactions at device skin interfaces to provide a tool for development of interventions and therapeutics.

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3D-helical fibres are among the most interesting and innovative structures in nature, representing an emerging group of materials with distinct unique spiral geometry and multiple excellent functionalities. As a result, there is a growing interest in developing bioinspired helical structures for mimicking tissues such as blood vessels. However, their fabrication at the micro-scale with precise control of size remains a challenge.

Microfluidics has been used to prepare complex fibrous structures via mechanisms not well understood. However, these fibres are typically formed from lithographic microfluidics or assembly of glass capillaries, which are neither scalable nor adaptable, limits their wider adoption.

The aim of this project is to develop an in-depth understanding about the formation of complex architecture and their properties based on 3D-printed microfluidics. The new insights gained will lead the development of novel complex structures for use in tissue engineering and bio-catalysis. The work will include development of microfluidics using Material Extrusion Additive Manufacturing (MEAM) technology coupled with CONtinously Varied Extrusion (CONVEX) design approach which has demonstrated unmatched level of control [1,2]. The candidate is expected to optimise the manufacturing workflow via design, simulate, fabricate and validate workflow to enhance the reproducibility and scalability of 3D-printed devices. The candidate is expected to visualise and measure the concurrent fluid flows through microfluidic channel to develop algorithm regarding the effect of design parameter on microfluidic performance. The fabrication of microfibres is characterised using a range of different analytical techniques including optical microscopy, brightfield, µ-CT and SEM. Furthermore, real-time monitoring of fluid flow through the channel will shed light on complex interactions Newtonian and non-Newtonian materials. References: [1] Moetazedian A et al. Additive Manufacturing 2021:37;101576 [2] Moetazedian A et al. Engineering Archive 2022: 1-37

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The research project is to develop an abrasive machining method to the surface structuring of novel technical materials. The technical materials to be machined are 3D printed alloys or the hard-to-machine materials like Si, SiC etc. A typical case study will be focused on the surface structuring of SiC plate using special designed grinding wheels. Simulation work will also be carried out in this project to study the material removal mechanism and find the optimised processing parameters.

The selected PhD student will be trained to operate machine tools and other related measurement equipment.

The applicant should have Msc research degree on mechanical engineering/informatics or will receive his/her Msc degree before they start the PhD study in September. The applicant who has publications (conference/journal paper/book chapter) in this research area will have high priority.

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To develop a broadband optical interferometer for measuring surface roughness, to be deployable on a robot. The research should focus on the following areas: Compactness of design. Sensitivity to vibration. Time to capture height data for a 2d region of a surface. Robustness to different surface geometry and materials. Surface roughness in the range of Ra = 0.5 – 5µm.

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Current communications systems operate in half-duplex mode as it is generally believed that it is not possible to transmit and receive at the same time in wireless networks due to the strong self-interference created by the transmitter at its own receiver. Recent research has shown that the strong self-interference can be completely cancelled using analog and digital interference cancellation techniques to enable full-duplex communication. The immediate benefit of full-duplex communication is the doubling of spectral efficiency that makes a significant part of radio spectrum available for new applications and services. While the feasibility of full-duplex radios has recently been demonstrated for standalone wireless links, the challenges in the implementation of full-duplexing in 5G communication networks are many folds. Firstly, 5G communication networks involve multi-user communication in infrastructure or ad hoc mode. Secondly, multi-antenna communication is intimately linked to the ability to increase the spectral efficiency of a link without increasing the total transmission power, as shown by the advent of MIMO (Multiple Input Multiple Output) systems. This project will investigate full-duplexing techniques in multi-user, multi-antenna communication set up in 5G communication networks.

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In the oil-gas fields, slurry flow, gas-in-water two phase flows, and oil-gas-water three phase flows are frequently encountered. Generally, the measurement of volumetric flow rate for each phase is of most interest, especially in subsea oil-gas production applications, where it is essential to obtain oil, water and gas flow rates in inclined oil wells. The problem of how to accurately measure these flow parameters for such complicated flow phenomena, without using expensive test separators and intrusive technique, is a major challenge for the industry. Most conventional multiphase flow meters have severe limitations regarding types of flow and their measurement reliability. Some useful techniques containing radioactive sources are available but they are expensive and potential harmful to humans. Thus, the new developed system will be capable of measuring the local volume fraction local distribution and local velocity distributions of each phase based on tomographic techniques that does not contain a radioactive source.

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Switches and crossings are the most complex part of the railway track network and they contribute a disproportionate amount to track renewal and maintenance expenditure. Concerning crossings, Network Rail identified in its challenges statements that the estimated annual costs for cast crossing replacements and their attributed delay penalties equate to over £24M per year. Root causes are multiple, relating to support conditions (poor ballast quality, stiffness variation, pad conditions, load amplification) and fundamental design of the wheel-rail interface leading to dip angle and impact load. However, this is exacerbated by poor data management with regards to the evolution of the asset: lack of remote conditions monitoring solutions, incomplete knowledge of asset and lack of degradation history. With the development of accurate and sophisticated physics-based models capturing the performance of these assets, the increasing availability and deployment of sensors as well as the digitalisation agenda of the railway industry, there is scope to make these complex assets more intelligent to better tailor their maintenance needs.

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In the late 1668 Sir Isaac Newton built one of the earliest known functional reflecting telescopes out of metal alloy, the diameter of the primary mirror is about 33 mm. The recently launched James Webb Space Telescope (JWST)’s primary mirror consists of 18 hexagonal mirror segments with a diameter of 1.32 meters. The ever-increasing demand for the form accuracy and surface finish of large metal mirrors poses a great challenge to the fabrication process.

Off-axis aspheric mirrors are widely used in optical engineering, such as Augmented Reality (AR), Virtual Reality (VR), laser and space applications. Diamond turning has been an efficient way to fabricate this kind of mirror. However, with the increasing mirror sizes, the machined form accuracy becomes more difficult to control. The machine kinematic errors will be amplified when the workpiece diameter increases. The larger surface amplitude will also contribute to motion errors of the feeding axes. With the advent of on-machine surface measurement (OMSM), the closed-loop machining of large metal mirror becomes possible. Because the OMSM can keep the datum and avoids the re-alignment error caused by the off-machine metrology process. Optical point-based probe is an ideal choice for OMSM due to its compact size, high measurement frequency and resilience to machine vibration. However, the data processing of OMSM data becomes a challenge due to the scanning path being a non-uniform spiral path rather than a uniform mesh grid. Conventional surface filtration and analysis algorithms cannot be applied directly.

This research project aims to explore and investigate the optimised fabrication process of half-meter scale ultra-precision mirrors with nanometre surface finish and sub-micrometre form accuracy using diamond turning. The on-machine surface measurement is used to compensate for errors and evaluate surface finish. The objectives of this project include: • Measure machine kinematics errors. • Generate machining tool path with compensation of machine kinematics errors. • Develop an optimised machining strategy for the large mirror. • Realize the closed-loop machining of the large mirror with OMSM. • Develop surface characterisation algorithms for OMSM data.

The Ultra-precision Manufacturing Lab at the University of Huddersfield has state-of-the-art facilities to advance this exciting research, such as the world’s most advanced 5-axis ultra-precision diamond turning machine. The research can also enjoy the easy access to various metrology instruments, including surface profilometer, XCT, CMM, SEM, etc.

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The UK Government's Made Smarter review (2017) observed, "The automation of manufacturing processes, coupled with real-time process monitoring and re-engineering, can result in radical improvements in cost, efficiency and accuracy, allowing work to move back to the UK". This project is a direct response, and should prepare the successful candidate for a productive and stimulating career in what promises to be one of the fastest-evolving areas of automation and advanced manufacturing.

The studentship will be based at Huddersfield's Laboratory for Ultra Precision Surfaces, in a new building at one of the Government's major research labs - the SciTech Daresbury campus near Warrington. The student will be immersed in a highly stimulating environment, as part of a growing strategic-partnership between the two organisations and other collaborators. Supervision will be provided by Huddersfield's process-expert (Walker) based at Daresbury, and Al-expert (McCluskey) on-campus at Huddersfield.

The project will utilise advanced robotic equipment and measuring instruments for processing ultraprecision surfaces. At these extreme precisions, processes fall short of perfect-predictability, demanding repeated process measurement cycles to converge on specification, which drives manufacturing risk, cost and time. It also requires highly-skilled operators to make process decisions, who are in declining supply worldwide. The core objective is thus to enhance process-predictability. Surfaces are inaccessible for measurement during processing, so indirect diagnostic-data related to removing material will be monitored. Opportunities abound for the student to contribute to data-harvesting hardware & software, and process-trials, depending on personal skills and interest.

In principle, it should be possible to derive instantaneous removal-rates from real-time data. If so, integrating these rates could give estimates of accumulating removal-depth over the surface, throughout each process-step. At the end of a step, predicted-removal could be compared with direct surface-measurements, giving information to refine the prediction. In reality, the underlying relationships are highly complex, due to interplay of physical and chemical mechanisms at atomic scales. The project's approach will be to amass comprehensive real-time data, alongside post-process measurements, with Al techniques developed to seek meaningful relationships underlying the data. Once established, the project will investigate how the real-time data can be used to make decisions 'on the fly' to keep processing on-track, improving convergence, reducing defects, and decreasing manufacturing time and cost.

Beyond this, the data will undoubtedly reveal new insights into fundamental mechanisms of processes and why variability occurs - which could prove a fertile research-area in its own right.

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‘Industry 4.0′, or the fourth industrial revolution, includes the Internet of things, and cyber-physical systems (CPS) as key components. The function of CPS has been identified as monitoring physical processes and creating a virtual copy of the physical world, to support decentralized decision-making. Digital twin has been identified as the enabling technology for CPS.

In the current manufacturing environment, machining cells that included industrial robots could provide a low-cost alternative to machining centres and routers for secondary part operations and could eliminate the work-envelope constraints of those machines when dealing with large components. The major challenges for sophisticated robotic machining system are commonly addressed as low rigidity and poor accuracy. The articulated arms of robots are very agile and flexible with good accessibility, which in turn will cause the loss of dynamic accuracy when used for machining. The vibration and chatter of the robot arms will lead to unacceptable machining quality. The current research is mainly focusing on compensation based on additional sensing and actuation, offline programming etc. The solutions are generally applicable only to a robot or a robot type.

In this research, a digital twin of the robotic manufacturing system will be proposed to investigate the development of a comprehensive twin, covering process planning, monitoring, integration and interoperability with other manufacturing systems.

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This research aims at tackling the current challenges in AM by introducing novel in-process optical sensing tools for dynamic surface measurement, and real-time data analysis methods for surface assessment. A fast 3D fringe projection system with the ability to achieve simultaneous 3D shape acquisition, reconstruction and display in real time will be developed and implemented for in-process AM process. These innovations could advance fundamental understanding of AM processes, and ultimately lead to systematic tools to control the end-product performance of AM.

The main objectives of this proposed research are: 1) develop dynamic optical sensing system that acquires 3D topography for in-process AM. 2) achieve real-time 3D reconstruction by developing novel computational methods including using advanced graphics-processing unit (GPU). 3) develop novel methods for system calibration and surface reconstruction methods to achieve desired measurement accuracy. 4) develop real-time surface quality assessment method for AM process surface characterization. 5) system verification, validation and experimental study.

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Most of the real-world systems experience changes in their dynamic properties in different conditions due to the change in their mass, length, stiffness,... such as bridges under a moving load or wind turbine blade with a variable span or chord. The dynamic behaviour of such systems are time dependent, but in most of the cases simplistic conditions are assumed to make the analysis easier. However, sometimes these assumptions might result to inaccurate results specially for systems that the rate of change is high. These systems are generally called as time varying systems (TV systems). Currently, one of the main methods that is used to determine the stability of time varying systems is to use the Lyapunov method, which in most of the cases it is difficult to find the Lyapunov function specially for complicated systems. Also, Floquet theory can be used to study the stability of TV systems, but it is only applicable to periodic systems. Although there are a few other methods introduced in the literature to analyse the stability of time varying systems, but this research area has received very little attention and needs a through investigation. Therefore, this project aims to develop a novel method/s for stability analysis of time-variant dynamic systems, and shed light for analysing of such dynamic systems more accurately and addressing the challenges and critical technical problems.

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Objectives

· Understand the influence of dielectric permittivity on surface wave propagation in composites.

· Understand the influence of geometric features on surface wave propagation in composites.

· Develop a predictive model for surface wave propagation in complex shaped composite structures.

Approach

· Carry out a literature review on the effect of dielectric permittivity on electromagnetic surface wave propagation in non-metallic materials and the influence of geometric features.

· Design and carry out experiments, including design of experiments approach, and set-up.

· Develop a method for evaluating the dielectric permittivity in anisotropic materials.

· Explore the effect of the dielectric permittivity on the signal propagation.

· Explore the effect of the geometric features on the signal propagation.

· Develop a numerical model for electromagnetic surface wave propagation through geometric features.

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This PhD project is ambitious to develop infrastructure to enable the dynamic information flows in manufacturing, using the developed syntax and semantics of CSL at the fundamental level as its foundation. Objectives of the project will include: • Develop smart and efficient algorithms to discover any potential or intended higher-level (functors and beyond) structures in an automatically way; • Develop efficient and effective algorithms to enable conceptual query and both deductive and abductive reasoning; • Develop modules for functor levels in the CSL editor, namely CatLab; • Using a set of manufacturing case studies to evaluate and validate the developed functor modules and query language. This exciting research project is of great scientific and industrially interest and therefore will offer the candidate the possibility to establish successful industrial and academic collaborations. The applicants should have strong background in mathematics, applied mathematics, computer science, or a related discipline. The applicants are expected with advanced level of programming, basic understanding of discrete mathematics, including set theory, algebraic topology, and theoretical computer science. A entry level of category theory is also desirable. The applicants should also work well within a team and have good communication skills, written and verbal.

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The increasing global demand for sustainable and efficient energy solutions has fuelled the exploration of innovative technologies in the field of power generation. Among these, the Organic Rankine Cycle (ORC) stands out as a promising technology known for its ability to convert low-temperature heat sources into valuable electricity. The ORC is a thermodynamic process that utilises organic working fluids to generate power from low to medium temperature heat sources. Unlike the conventional Rankine cycle, which uses water as the working fluid, the ORC system is designed to operate with organic fluids that have lower boiling points and better heat transfer properties at lower temperatures. Traditional ORC systems have demonstrated significant efficacy, yet there is a compelling need to further optimise their efficiency. This research proposal aims to contribute to the evolution of ORC systems by reduction of exergy destruction in the individual components of the ORC system through the optimization of their performance. The relevance of this research is underscored by the imperative to enhance the performance of ORC systems, especially in the context of waste heat recovery across diverse industries.

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  1. Introduction

Modern high-speed trains (HSTs) are equipped with sophisticated braking systems that employ both mechanical and regenerative braking techniques. Mechanical braking involves the use of braking disks or pads to convert kinetic energy into heat, thereby slowing down the train. In contrast, regenerative braking harnesses the train's engine as a generator to convert kinetic energy into electricity, offering an energy-efficient alternative. One critical aspect of High-speed trains (HSTs) performance is braking, which involves a complex interplay of mechanical and regenerative braking systems. This research aims to optimize the overall braking performance of HSTs by developing advanced Multi-Input Multi-Output (MIMO) control strategies, ensuring efficient utilization of both mechanical and regenerative braking mechanisms. Existing control systems lack the intelligence to distribute braking forces efficiently across axles or bogies. By developing intelligent MIMO control strategies that consider various factors, such as load, wheel conditions, and driver input, to achieve optimal braking performance. By optimizing braking force distribution, enhancing safety features, and ensuring adaptability to varying conditions, the proposed system will pave the way for safer, more efficient, and sustainable high-speed rail transportation.

  1. Objectives • To analyse the existing braking mechanisms: Understand the dynamics of mechanical and regenerative braking in HSTs, identifying limitations and areas for improvement. • To design intelligent MIMO control algorithms: Develop advanced control algorithms that integrate multiple inputs and outputs, ensuring optimal distribution of braking forces based on real-time data from wheel sets. • To enhance safety features: Implement intelligent functions, including anti-blockage braking systems, driver awareness monitoring, and remote-controlled emergency braking, to enhance overall safety during braking events.

  2. Methodology 3.1. Data Collection and Analysis • Gather real-time data from HSTs, including wheel conditions, load information, and braking force distributions under various scenarios. • Analyse the collected data to identify patterns, limitations, and areas requiring improvement in the existing braking systems. 3.2. Development of MIMO Control Algorithms • Utilize machine learning techniques and control theory to design intelligent MIMO algorithms capable of optimizing braking force distribution. • Integrate inputs such as load conditions, wheel status, and driver input to dynamically adjust braking forces for each axle or bogie. 3.3. Implementation and Testing • Implement the developed MIMO control algorithms in a simulated environment and conduct extensive testing under different operating conditions. • Evaluate the performance of the control system, focusing on braking efficiency, safety margins, and adaptability to varying situations.

  3. Candidate specification For a Ph.D. candidate undertaking this project, a combination of educational background, technical skills, and personal qualities is crucial to ensuring the successful completion of the research. A candidate should hold a master’s degree in a relevant field such as Mechanical Engineering, Electrical Engineering, Control Systems, Transportation Engineering, or a related discipline. Proficiency in control theory and experience with designing and implementing control algorithms, Strong programming skills in languages (such as MATLAB, Simulink, or Python) are necessary for simulation, modelling. Knowledge of the principles of railway systems, including braking mechanisms, regenerative braking, and high-speed train dynamics are desirable.

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Maintenance tasks in complex industrial environments often require a high level of expertise and precision. The integration of robotic arms and augmented reality can transform these tasks by offering dynamic, interactive, and context-aware guidance to technicians. By leveraging AR interfaces, technicians can access vital information, such as schematics, component specifications, and procedural instructions, overlaid onto the physical equipment they are working on. This research proposal aims to develop an innovative system that combines the precision of robotic arms with the intuitive guidance of AR interfaces. By providing real-time instructions, visual overlays, and additional information, this technology will empower technicians to diagnose and repair equipment with unprecedented accuracy and efficiency. The research methodology involves a multi-phase approach, including literature review, system design and development, integration of AR interface with robotic arm platforms, machine learning implementation for context-awareness, user studies, and industry-specific customization. Prototyping and iterative testing will be conducted to refine the system and ensure its effectiveness in real-world maintenance scenarios.

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This project relates to the physics of multiphase flows, which are a common occurrence in many industries such as nuclear, chemical, petroleum, minerals or food (some of the examples being gas/oil flows in crude oil extraction processes or steam/water flow in helical heat exchangers). On the fundamental level, the project will attempt to study various flow regimes present in gas-liquid system, in a purpose built flow rig, with particular attention to flows in inclined pipelines. These are still not very well understood as most of the existing work relates to vertical and horizontal configurations. The techniques used to interrogate the flow may include high-speed video, pressure drop measurements, optical (LDA, PIV), electrical (capacitance/resistance) or ultrasonics. It is hoped that this will provide a detailed classification of the flow patterns associated with various flow conditions, fluid properties and pipeline inclinations. On the engineering level, the project will aim at developing criterial correlations, which could be used in future in the design process of industrial installations. In its basic form, the project will suit either mechanical, chemical/process/petroleum or nuclear engineering graduates, that is those who had exposure to thermo-fluids and measurement problems during their undergraduate studies. The problem may be suitably modified to accommodate also IT, signal processing and instrumentation engineers, by taking the focus off the flow itself, and instead contributing to the development of methodologies for flow pattern recognition, measurement and signal processing. (Industrial relevance: petroleum, energy sector, chemical)

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The employment of finite element methods in engineering plays a large role in the analysis of structures. With the advancements in computer resources, dynamic analysis applications based on this method are able to analyse large and complex systems. This work aims on the development and implementation of novel finite element modelling methodologies, able to handle the dynamic interaction between the overhead line and the pantograph in railway systems. Focusing on the construction of finite element models of the overhead systems and its dynamic analysis. The newly developed modelling methods are to be incorporated in a state-of-the-art dynamic analysis tool already developed, so its capabilities are augmented. The new methodologies are to be validated using experimental line tests in collaboration with industrial partners of the railway sector.

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In this project the use of aerodynamic bearings to support the rotor shaft in automotive turbochargers will be investigated. The proposed bearing is supported by a metal foil structure when the shaft rotation is insufficient to generate the aerodynamic forces required to make the bearing self-supporting. The project will include:

• Investigation of the operational requirements for automotive turbocharger rotor bearings comprising load, stiffness and damping characteristics, operating conditions including temperature, shaft speed, gas and inertial loading and importantly, bearing and shaft sizes.

•Development of the multi-physics numerical models required to simulate the aerodynamic effect, the interaction of the generated air film with the metal foil support structure and the damping characteristics provided by friction between the components of the foil support structure.

•Generation of experimental data to validate the numerical models including the design and manufacture of a bearing test rig.

•Production of characteristic load, stiffness and damping curves for foil backed aerodynamic bearings using the validated numerical model.

•Use of a constrained optimization approach to identify the range of feasible bearing designs for automotive applications.

•Modification of an existing hydrodynamic turbocharger bearing housing to use an example aerodynamic bearing and demonstrate the bearing’s feasibility on an engine test bed.

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The objective of this project is to develop AI/ML-based GoB and non-GoB BF solutions for ORAN that satisfy multiple requirements. Depending upon the bandwidth requirements real-time (RT) and non-RT solutions will be proposed for below 6GHz and mmWave spectrum. The proposed BF solutions will utilize different parameters such as quality of synchronization and signal block (SSB), channel state information (CSI), targeted KPIs such as (latency, estimation accuracy, mobility and handover targets, etc.) number of beams available, beamwidth allowed as constrained by the network and seamless mobility.

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Nowadays, functional surfaces play an increasingly important role in optics and electronics, biomedicine, and the energy field due to their novel properties. Different from conventional surfaces with a rotational invariance axis, the freeform surfaces are usually with arbitrary macro shapes, varying curvature at different surface locations or intensive microstructures. These features make the functional surfaces have many novel properties such as super-hydrophobic, optical tuning, antifouling and drag reduction. The freeform surfaces can be classified as (1) discontinuous/conjunct surfaces with steps, edges and facets like Fresnel lens, (2) tessellated surfaces with a repeated structure like pyramid array, and (3) smooth surfaces rely purely on the global geometry. Grinding with laser profiled wheels is a promising method to efficiently generate micro and macro features on brittle materials. However, the difficulties in precisely texturing the diamond grinding wheels and easily wear of the grinding wheel impose challenges on grinding functional surfaces in a long working time.

This research project aims to explore and investigate the optimised fabrication process of discontinuous or smooth functional surfaces on difficult-to-cut materials using multi-energy field compound grinding. The objectives of this project include: • Develop a profiling strategy for preciously texturing the superabrasive grinding wheels. • Integrate an energy field (e.g., laser field and ultrasonic field) assistant grinding platform. • Optimise the machining parameters for energy field assistant grinding on difficult-to-cut materials. • Test the performance of ground functional surfaces.

The Ultra-precision Manufacturing Lab at the University of Huddersfield has state-of-the-art facilities to advance this exciting research, such as the world’s most advanced 5-axis ultra-precision diamond turning machine. The research can also enjoy the easy access to various metrology instruments, including surface profilometer, XCT, CMM, SEM, etc.

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Hardware-In-the-Loop (HiL) is a novel simulation technique where a physical system interacts within a simulation in realtime. This technique is employed in the development and testing of complex systems. It allows mechanical systems to be tested, avoiding real tests which would otherwise be costly or unfeasible. There are challenges in setting up these types of simulation frameworks. The simulation program is required to be efficient and able to be evaluated in real-time. A robust control system is also necessary to acquire sensor data and control the response of all actuators accordingly. The development of this work is set on the development of a HiL framework for pantograph testing, in interaction with a numerical model of the overhead line. A fully equipped, world class, £ 3.5M pantograph test bench is available to procced with this works. Industrial partners in the transport and railway sector are to be involved in this work.

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The Institute of Railway Research is developing a full-scale railway bogie hybrid drivetrain test facility. The rolling-rail based test rig (similar to a rolling road in the automotive sector) will enable the study of hybrid drivetrains through combined simulation and testing of both the OEM bogie traction package and regenerative braking system, together with simulation models of batteries or other storage technologies. To facilitate this work, a simulation and testing environment is required which will allow the duty cycles of typical commuter train routes to be represented, together with a model of the traction and energy systems that make up a hybrid rail vehicle. The candidate will require skills in electrical and mechanical engineering and the ability to develop mathematical models within the MATLAB/SIMULINK environment. Practical skills would also be of a benefit as the work will also involve laboratory testing.

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The project aims at conducting a fundamental study of fluid mechanical and heat transfer processes occurring in stacks/regenerators and heat exchangers of thermoacoustic devices. In thermoacoustic devices, a standing/travelling acoustic wave causes the compressible fluid to undergo a thermodynamic cycle very similar to the Stirling cycle. This can potentially be utilised in constructing the next generation of reliable and energy efficient prime movers, refrigerators or heat pumps, without moving parts and using environmentally friendly inert gasses as working fluids. Unfortunately, the correct analysis of the thermoacoustic devices is hindered by the lack of understanding of the fluid mechanics and heat transfer processes which are profoundly affected by the transient and three-dimensional nature of the oscillating compressible flow and its interactions with physical boundaries. The proposed research will focus on investigating these complex phenomena in a purpose-built experimental apparatus, using a range of measurement techniques including Particle Image Velocimetry (PIV), Laser Induced Fluorescence (LIF), Laser Doppler Anemometry (LDA) and hot and cold-wire measurements, in order to determine the flow characteristics inside representative components of a thermoacoustic device. This work will be complemented by numerical studies where the transport coefficients obtained from experiments can be used to enhance the numerical models of the fluid behaviour to benefit future design procedures. (Industrial relevance: power generation, heat ventilation and air conditioning, refrigeration, manufacturing)

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Due to the high demand on reducing pollutant emission from using fossil fuel in transportation, researching on electrification transportation is highly attracting. In electric traction application, control development of traction machine is highly essential for maximizing exploitation of battery pack. And for traction application, PM traction machine is often employed. Thus, a high-performance control technique with maximum efficiency achievement of PM traction machine is essential. In practice, current control with indirect torque control is often employed for PM traction machine. However, as the traction application is often operated under torque mode control, direct torque control considering AI for traction application could provide advantages over current control and this is the target of this PhD study.

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Variable-capacitance machines are a type of electrostatic generators that use a rotating capacitor to produce high-voltage direct current (HVDC) power. They have potential applications in ion propulsion, electrostatic precipitation, particle accelerators and other fields that require high-voltage power sources. However, one of the major challenges of variable-capacitance machines is discharge between electrodes due to a breakdown of the dielectric medium. This discharge causes can cause damage to the electrodes, reducing the output power and efficiency and creates electromagnetic interference.

The aim of this project is to investigate the causes and effects of discharge events in variable-capacitance machines. A prototype rig with adjustable parameters will be designed, built, and placed under variable vacuum to test the performance, to quantify the factors which influence discharge and to identify methods and materials which can be used to reduce discharge whilst increasing machine power density.

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Most successful studies of machining stability and tool wear condition modelling are based on the appropriate collection of high-value information. This is set of special signal features that appear when the CNC system loses stability. The collection of this information is challenging both for general research and for industrial application because of uncertain factors such as the environmental temperature variation, work piece material quality and unknown/unobserved system errors. To solve this problem, this project aims to develop an effective and intelligent algorithms to identify and classify the high-value information for traditional milling processes. The core tasks include: advanced signal processing and stability analysis; tool wear analysis and tool status identification; feature signal identification and classification by Artificial Intelligence (AI) methods. Advanced signal processing technologies , deep learning and machining modelling methods will be combined to achieve this goal . Through this project, the PhD candidate will gain an in-depth understanding of machining motion, machining dynamic characteristics and machining mechanisms. In-depth understanding of material mechanics and thermal conduction will be essential. They candidate with a mechanical engineering, physics or applied mathematical background.

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This PhD project will be focused on developing hybrid coastal defence solutions for flood mitigation. Coastal structures such as sea dikes and seawalls are being exposed to severe and frequent sea storms, due to rise in sea level and increase in extreme wave climates. The current estimated damage due to coastal flooding in the UK alone is £540 million/year, which will rapidly increase in future, as the UK is expected to face at least 1m of sea level rise by 2100. Several coastal regions have benefitted from hard engineering structures acting as barriers from extreme waves, whereas in other regions (mostly low-lying areas) the coastal wetlands have been recognised as potential buffers against storm impacts, serving as a Nature-based Solution (NbS) for flood mitigation. It has been observed that the hard engineering structures are expensive to maintain and repair which often calls for NbS as a favoured option over building hard defences, however NbS often pose risk of major land grabs, and impact urban tourism. NbS designing also demands high computational costs of running coastal simulators multiple times over with a diverse and distinct set of parameters and prohibits a thorough exploration of the parameters that control the efficacy of NbS. Therefore, in this project a hybrid solution will be delivered for exploiting the dual benefits of hard and soft/NbS engineering structures in shallow water, by adopting Artificial Intelligence (AI) tools along with state-of-the-art numerical simulations. The PhD student will be significantly benefited from the Co-Supervision by Dr Piyali Chowdhury from the Centre for Environment Fisheries & Aquaculture Science (CEFAS).

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Scarcity of fossil fuels and rapid escalation in the energy prices around the world is affecting efficiency of established modes of cargo transport within transportation industry. Extensive research is being carried out on improving efficiency of existing modes of cargo transport, as well as to develop alternative means of transporting goods. One such alternative method can be through the use of energy contained within fluid flowing in pipelines in order to transfer goods from one place to another. Although the concept of using fluid pipelines for transportation purposes has been in practice for more than a millennium now, but the detailed knowledge of the flow behaviour in such pipelines is still a subject of active research. This is due to the fact that most of the studies conducted on transporting goods in pipelines are based on experimental measurements of global flow parameters, and only a rough approximation of the local flow behaviour within these pipelines has been reported. With the emergence of sophisticated analytical tools and the use of high performance computing facilities being installed throughout the globe, it is now possible to simulate the flow conditions within these pipelines and get better understanding of the underlying flow phenomena

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This ambitious, multidisciplinary project will aim to develop a novel “Internet of Acoustic Things (IoAT)” technology for smart houses, which can transform an existing room within a house into an acoustically enhanced or different virtual environment with a reduced perceived annoyance from noise. Benefiting from the supervisory team’s expertise in virtual acoustics, embedded DSP, active noise control, condition monitoring as well as health research, this project will conduct world-first research into IoAT sensing and reproduction techniques, user motion tracking for adaptive acoustic processing, edge-based signal processing for active de-noise, de-reverberation and virtual acoustic rendering, and subjective quality of experience and biometric reactions. The project will deliver a step-change in the way people perceive indoor soundscape and help enhance their quality of life.

Examples of possible applications of the project outcomes include (i) transforming a kitchen with a high level of reverberation, which could significantly increase noise-induced stress, into a pleasant-sounding virtual park, (ii) turning a bed room into a concert hall where the user can practice singing as if s(he) is physically in that space, and (iii) reducing external noise level perceived in a living room adaptive to the user’s position.

Soundscape approaches for reducing noise-induced annoyance and improving citizen’s wellbeing are currently one of the most discussed topics among numerous government bodies and at the international standard organisation. Traditionally, noise problems within a house would have to be address by acoustic design and treatment, which have many practical constraints due to cost, existing room structure, etc. The proposed project, however, will provide an innovative solution that can not only reduce noise, but also acoustically transform an existing room into a different virtual environment for reducing stress and enhancing people’s quality of life in home environments.

This will be the world-first project to investigate IoAT-based de-reverberation and de-noise within an acoustic space in the context of health and quality of life. The outcomes of the project will have high potential to be published in top-quality REFable journals. The methods can also be exploited for developing new commercial products (e.g. IoAT sensor/speaker/media device), producing significant economic and societal impacts.

The Huddersfield Smart House Research Facility is being developed as a collaborative hub for industry, academia and government organisations. It is being developed to accelerate research and development for smart products and services to be used in the building environment with an aim to bring transformational improvements in key performance indicators corresponding to 21st century houses and living conditions. For this purpose, a well instrumented two storey dwelling is being constructed that will provide facilities for a range of novel and innovative investigations to be carried out.

Smart technologies can help us in reducing carbon footprints as well as having positive energy balance through improved energy performance of homes and buildings. We can achieve greater energy efficiency, cut carbon emissions and support more intelligent and flexible management of energy supply and demand. By incorporating use of smart technologies, the health and wellbeing can be significantly improved through better management of internal environments, safety and security. Smart technologies have potential to offer significant improvements in wellbeing of the occupants by allowing control through voice and mobile apps as well as using automation and artificial intelligence to support and predict our changing needs.

HSHRF aims to bring researchers, practitioners, industries and government organisations together to design, develop and implement holistic solutions to current and future societal challenges associated with building environment and its use.

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As the Industrial Internet of Things gains interest and traction in modern manufacturing industries, there has been a significant growth in the number of sensors embedded in machinery which follows with data transfer, storage and analysis. In metrology, it is crucial to perform calibration on instruments and sensors to achieve traceability across international engineering and scientific projects. Temperature is one of the most prevalent measurands and while bench top solutions and laboratories can calibrate such sensors, these could not be applied to sensors permanently installed in machinery. This project will look at new materials/combinations of materials that provide anisotropic or ultra-stable properties that may be combined in a mechatronic system performing, for example, reversal measurements, to perform in-situ calibration. The opportunity is suitable for a material scientist or a mechanical engineer wanting to work on a multidisciplinary project using materials to solve a metrology problem. The candidate will apply logical thinking and critical appraisal of materials, with a robust design of experiments to validate the proposed solution.

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Three-dimensional (3D) sensing for specular objects is required in many applications in research and industry. And most of the surfaces are high precision, inconvenient to measure. A practical method to measure specular surfaces is phase measurement deflectometry. Traditional deflectometry has been used as a 3D object reconstruction method for surfaces with weak (i.e., large radius of curvature) convex or concave surfaces. A full aperture optical surface test of a general convex surface has not been achieved.The proposed research project aims to develop an infinitive multi-sensor deflectometry system for general convex or freeform specular surface measurement. The proposed project will be able to measure the full aperture of convex surfaces. You are expected to develop new calibration methods and algorithms as well as the phase calculation algorithms for the infinitive multi-sensor deflectometry.

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Recent developments in rail steel composition and manufacturing techniques have increased the hardness of the available steels to over 400HB. Whilst this helps to reduce the wear rate, under some operating conditions rapid fracture of initiated rolling contact fatigue cracks has occurred resulting in broken rails. Initial investigations have shown the influence of the operating conditions (e.g., rolling stock traction/braking, rail deflection), deformation layer and crack angle on the likelihood of fast facture. However, further fundamental research is required to quantify the contribution of these parameters and support the optimisation of the rail steel hardness and composition to the operating conditions.

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Large data analysis presents major computational challenges and novel methods of alleviating computational burdens are sought. Restricting input volume of explanatory variables is beneficial as an aid to timely convergence of algorithms and in de-noising signal information. Pre assessment of input variable quality is required to ensure convergence of predictive computational algorithms. Reducing input parameter volume by restricting both the number of variables incorporated in the model and refining the detail of input variables proffers a solutions. Compression of incorporated variables also forms a useful means of trimming input signals. This project seeks to investigate the potential offered by volume reduction methodologies on classification precision.

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This aim of this project is to develop fundamental concepts behind a ‘self-aware’ sensor that can holistically evaluate the full gamut of information contained within an acquired signal in order to determine not only the primary information e.g. height/distance but also to track changes in other secondary parameters such as alignment, calibration status, environmental/measurand variation. The initial work will develop analytical techniques for broadband interferometry e.g. wavelength scanning interferometry (WSI) in order to establish methods for separating secondary parameters from the primary measurement. Once the ability to effectively separate secondary parameters has been established, signal processing techniques will be expanded be adaptive based on the nature of secondary parameter variation. The possibility of adapting input parameters to the system will also be considered at this stage.

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The cost of maintaining rail vehicles can be up to 40% of the life cycle and is estimated to cost over £700m per year to maintain the GB mainline fleet (made up of over 14,000 vehicles, maintained at 96 depots). Train operators are also under increasing pressure to reduce costs, particularly during the post-COVID recovery. A key enabler to improving the efficiency of rolling stock maintenance is the use of ‘smart technologies’ to optimise and automate maintenance activities. This research will aim to build on existing work being undertaken within IRR to apply robotics technologies to rolling stock maintenance through the integration of artificial intelligence (AI) planning and control techniques.

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This ambitious, multidisciplinary PhD project aims to develop novel and wearable assistive technologies. which can transform the lives and well-being of an individual. Benefiting from the supervisory team’s expertise in virtual acoustics, embedded DSP, and interfacing techniques, the PhD project will explore and help to redefine what is possible in user motion tracking, adaptive acoustic sonification, intelligent scene and setting identification and edge-based signal processing for improving the QoL (quality-of-life) experience for users and helping to promote well-being. The project will deliver a step-change in offering the potential for ‘accessible to all’ systems.

The project aims to explore emerging technologies, particularly those identified as having the potential for being assistive and connected (IoT), and to combine these with novel and intelligent application to increase the well-being and foster independent living to its users.

Examples of applications of the project outcomes include (i) Indoor and outdoor navigation solutions for blind/partly sighted individuals, (ii) Intelligent ‘assistive narration’ systems to enable independent living (iii) QoL improvement to social care systems through the integration of intelligent visual systems and early intervention technology.

We live in a society that cherishes independent living but with increased life expectancy, and with sectors of society that suffer from certain health conditions (including, amongst other things, sight loss and low mobility) there is more demand that ever to push research in these assistive technology areas. The project will help to provide better health and care systems.

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Measurement and control of temperature is a common requirement for engineering and process industries. Control in machine tools is achieved by making positional adjustments to compensate for the resultant positional displacement. This project will develop a microcontroller-based closed loop system to control temperature fluctuations in machine tool structure by thermal management (heat input) to remain within specific positional tolerance limits and rate-of-change. The controller will have the capability of self-optimisations such as decision making on adapting to temperature changes and gradients.

The candidate should have a good understanding of metrology, concepts of measurement, temperature uncertainty and principles of control. The student should also have a thorough understanding of software architecture and appreciation of programming of microcontrollers. An appreciation of manufacturing and measurement is desirable to assist with the proposed test domain.

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Design is one of the most important activities in laser powder bed fusion (LPBF) product realisation process. Current LPBF design still follows a manual series route: A specific LPBF system, based on sequential material selection, structure design and process planning, is tailored to build components and realise performance. This material-structure-process route, in which the three tasks are handled empirically and separately, requires repeated trial and error to obtain the expected performance. This creates a challenge for the LPBF technology, deemed to be mature and reliable, for broader industrial applications. To cope with the challenge, an intelligent decision methodology for all influencing variables of part performance is of great necessity and importance to enable concurrent design of material, structure and process and emphasise their mutual compatibility. The aim of this project is to develop an intelligent concurrent approach, going considerably beyond the state-of-the-art, for design of LPBF additive manufacturing. Its objectives and corresponding novelties are outlined as follows: • To construct a model to synthesise a large amount of data from a small amount of experimental data. Training an accurate prediction model of LPBF part performance indicators requires vast amounts of data, which is impractical to obtain via actual experiments or simulations. The model will enable automatic generation of enough training data and thus would address this issue. • To build a model to predict LPBF part performance indicators. Most of the actual LPBF part builds use certain sets of optimised process variables empirically developed by the original equipment manufacturers of LPBF systems. Because there are infinite possibilities for part design, it is not possible to provide complete sets of optimised process variables. This means that using the recommended process conditions could produce a product that cannot meet the quality requirements. The model will enable simultaneous, accurate and quick prediction of performance indicators under an arbitrary LPBF design. • To design a method to optimise the influencing variables of LPBF part performance. LPBF is widely known for its high machine, material and processing costs. This necessitates an optimisation model that can flexibly deal with the cost of replacement of improper solutions. In addition, the optimisation objectives of an LPBF design are usually not independent of each other, but interrelated and contradictory. This requires effective handling of the conflicts when synthesising the optimisation objectives. The method will address these needs well. • To develop a decision support system (DSS) for intelligent concurrent design for LPBF. The DSS will make a step change in design for LPBF from a manual series route that has the cumbersome trial-and-error limitation to an intelligent concurrent route without this limitation. It will be possible for the first time to have a software for material-structure-process-performance integrated LPBF.

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Inkjet printers are now seen as a potential approach for the manufacture of electronic devices. The ability to precisely and repeatably deposit material on a wide variety of substrates enables a wide range of novel technology, including flexible and wearable electronic devices and organic light emitting diode displays. This project aims to use inverse design methods, to develop an optimally designed surface which results in a uniform particle deposit of an evaporating droplet with suspended material. These surfaces typically have a combination of chemical and topographical features, which can be varied for uniformity of the deposits.

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The inspiration for many functional surfaces has been derived from biological entities such as shark skin etc. Various functional surfaces can be created by adjusting physio-chemical properties of materials with aligned micro and nanostructures. Many heat transfer regulating organisms employ functional surfaces that control near-wall flow characteristics thus affecting their global flow performance. This study focuses on the inverse design of functional surfaces for targeted global flow related effects primarily for heat transfer. At its core, the discussed methodology embeds reduced order models for surface and corresponding flow events. Desired geometrical parameters are iteratively solved to achieve target flow characteristics.

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The project looks at using inverse problem approach to design various electro-mechanical components used in industrial applications such as wind turbines with generators, marine turbines with power units, wave energy systems with power units for better efficiency, operation and reliability. State of the art numerical, analytical and experimental techniques will be used for such purposes.

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This project looks at using inverse problem approach to develop renewable energy systems such as wind turbines, marine turbines, wave energy systems, thermosyphons for better efficiency, operation and reliability. State of the art numerical, analytical and experimental techniques will be used for such purposes.

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This project will deliver a code for inverse design of blade surface for different climatic conditions. The wind turbine systems incorporating these blades will be expected to be effective in extreme weather conditions. The main benefit of this work will be to increase the efficiency of operation of wind turbines in cold regions which will also contribute to the improvement of turbine safety and lifetime.

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Inkjet printers are now seen as a potential approach for the manufacture of electronic devices. The ability to precisely and repeatably deposit material on a wide variety of substrates enables a wide range of novel technology, including flexible and wearable electronic devices and organic light emitting diode displays. This project aims to use experimental methods to investigate the evaporation dynamics of inkjet printed droplets on surfaces which have been prefabricated to aid in the controlled position of droplets. These surfaces have a combination of chemical and topographical features, which effect evaporating behaviour.

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In virtual reality (VR) applications, the quality of experience (QoE) perceived by the user is likely to be determined by interaction between audio and visual cues presented simultaneously rather than just the audio or visual alone. Although Audio-Visual Interaction (AVI) has been researched in many contexts, (e.g., speech recognition, visual realism, environmental noise perception, etc.), to date there has been no exclusive study conducted on the influence of AVI on the subjective audio and video qualities in relation to various objective quality degradation parameters. From this background, this PhD project will aim to provide answers to the following research questions. • If and how the perception of audio (video) quality is influenced by the presence of video (audio), and how much the video (audio) quality matters for this? • What are the perceptually relevant audio quality degradation parameters in various AVI scenarios? • What is the optimal perceptual weighting between the audio and video qualities in terms of maintaining high QoE in multimedia and VR applications? Theoretical findings from this project will have important implications for efficient and effective audio-visual processing. the applicant will need good knowledge in psychoacoustics and be proficient in MATLAB and C++ programming languages.

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In the era of the fourth industrial revolution (Industry 4.0), data generation will become enormous, and data analytics are becoming increasingly important towards decision making. Manufacturing stores more data than any other sectors. From big data to useful knowledge, the manufacturing industry will benefit greatly via knowledge-based decision making. In CNC manufacturing, a successful piece of part program is the result of combined effort of process planners, shop floor engineers via iterative endeavour of calculation, simulation and tests, which contains valuable process knowledge and know-how. The valuable Knowledge contained in part programs is not included in the loop of knowledge management. Researchers have sought to maximize the utilization of part programs. The early effort was to reuse these part programs directly on different CNC machines, without separate knowledge from product data, which was proven not effective.

Focusing on the big data of Computer Numerical Control (CNC) machines on the shop floor, this PhD project will investigate the mechanism of knowledge capture from CNC part programs used in production and the method to reuse the knowledge to support new product development. Deep learning approaches will be employed to capture knowledge, realise knowledge fusion and innovation in digital manufacturing. An automatic knowledge feedback will be achieved from the shop floor to feedback to the process planning stage to form a closed knowledge loop. This proposed deep learning approach will enable manufacturing companies to capture and accumulate process knowledge, maintain product quality and consistency, reduce the leading time for new products and boost innovation to gain competitive advantages.

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As fossil sources of energy are starting to reduce constantly, the search for alternative energy solutions has become vital. Among diverse energy resources, solar energy is by far the largest exploitable resource. The increase in the global energy demand and high depletion rate of conventional energy sources, in addition to the untapped solar energy’s full potential, significantly encouraged solar power generation technologies to grow faster than any other renewable technology. One of these technologies that offer a promising option for electricity generation are parabolic trough concentrating solar power (CSP) systems. Parabolic trough collectors concentrate the direct solar radiation onto a cavity receiver mounted at the focal point by its huge reflecting concave surface. The highly polished surface of parabolic troughs reflects most of the solar irradiation without any significant increase in the trough’s temperature. The working fluid transfers the absorbed solar radiation from the cavity receiver to the power generation system. The cost of parabolic trough collectors has a significant influence on the cost of energy from the concentrating solar power plant. To address this issue there is a need for new innovative parabolic trough designs that can reduce the parabolic troughs’ cost without affecting its tracking performance. One way of reducing this cost is by utilizing lightweight composite materials in the design of the parabolic trough structure, minimizing the need for “heavy duty” drives. However, there are some challenges in implementing such systems, particularly with respect to wind loads.

The project’s main objective is to investigate the employment of composite materials in developing a stiff, lightweight parabolic trough structure that is capable of withstanding severe environmental forces and loads such as winds. This will be achieved by carrying out a comprehensive Fluid-structure Interaction (FSI) analysis (combined computational fluid dynamics (CFD) and finite element analysis (FEA)) of the structural integrity and optical accuracy of the proposed system.

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The increasing global energy demand and high depletion rate of conventional energy sources, in addition to the untapped solar energy’s full potential, significantly encouraged solar power generation technologies to grow faster than any other renewable technology. One of these technologies that offer a promising option for electricity generation are parabolic trough concentrating solar power (CSP) systems. Parabolic trough collectors concentrate the direct solar radiation onto a cavity receiver mounted at the focal point by its huge reflecting concave surface. The highly polished surface of parabolic troughs reflects most of the solar irradiation without any significant increase in the trough’s temperature. The working fluid transfers the absorbed solar radiation from the cavity receiver to the power generation system. While having better and superior efficiencies over the remaining CSP systems, the parabolic trough collectors’ cost still remains very high, which is a barrier to its widespread use, and influencing the cost of energy from the CSP plant. To address this issue there is a need for new innovative parabolic trough designs that can reduce the parabolic troughs’ cost without affecting its tracking performance. One way of reducing this cost is by utilizing lightweight composite materials in the design of the parabolic trough structure, minimizing the need for “heavy duty” drives. However, one of the challenges faced in implementing such systems is ensuring that they are able to cope with the environmental conditions and aerodynamic forces imposed upon them during operation. The project’s main objective is to investigate the employment of composite materials in developing stiff, lightweight parabolic trough collectors that is capable of withstanding severe environmental forces and loads such as winds. Specific objectives: 1- Deliver an understanding on the impact of wind incidence, turbulence intensity and multiple geometrical parameters (i.e., reflector thickness, pedestal height, receiver diameter, etc.) on the aerodynamic loadings of the parabolic trough collector. [Package: SolidWorks; ANSYS/Fluent; MATLAB] 2- Carry out a comprehensive Fluid-structure Interaction (FSI) analysis of the proposed system using combined computational fluid dynamics (CFD) and finite element analysis (FEA). [Package: ANSYS/Fluent-static/transient structural] 3- Carry out a detailed ray-tracing analysis to evaluate the optical accuracy of the proposed system. [Package: ANSYS; Tonatiuh] 4- Optimize the composite parabolic trough structure design to achieve a balance between structural integrity and optical accuracy using artificial intelligence and nature-inspired optimization techniques. [Package: ANSYS; MATLAB/Artificial Intelligence-Optimization ]. 5- Develop a Flexible/time-efficient user-friendly platform for parabolic trough collector designers to predict and optimize the structural performance and optical accuracy of those systems as per desired requirements (i.e., chosen site’s maximum design wind velocity, optical and material failure limits)

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Single and dual-axis PV tracking systems are less popular choices for solar PV installations compared to fixed-tilt PV systems, even among large, utility-scale projects. While having better and superior efficiencies over fixed-tilt PV systems, the added expenses for the single and dual-axis PV tracking systems could not be neglected. Amongst the major components of tracking-based system, the drive element has the greatest effect on production costs. For large-area systems, the tracking mechanism requires heavyweight mechanical support structure and expensive drives with high torque capabilities to rotate the PV panels according to the sun’s position. Consequently, the gain from single and dual-axis tracking PV systems over fixed-tilt PV systems would have to surpass the additional expenses whereby the single and dual-axis PV tracking systems’ profitability and sustainability particularly in large scale solar power plant are guaranteed.

To address these issues and in order for the cost of energy from tracking-based Photovoltaic power plants to be competitive with that of fossil fuels, and more importantly fixed-mounted PV farms, there is a need for innovative Photovoltaic system designs that can reduce the photovoltaic systems’ cost without affecting its tracking performance. One way of reducing this cost is by utilizing lightweight composite materials in the design of the photovoltaic system support structure, reducing the need for “heavy duty” drives for tilting and orienting the conventional PV system’s heavyweight back-support structure that is usually constructed from steel. However, one of the challenges faced in implementing such systems is ensuring that they are able to cope with the environmental conditions and aerodynamic forces imposed upon them during operation.

The project’s main objective is to investigate the utilization of composite materials in developing stiff, lightweight tracking Photovoltaic systems that are capable of withstanding severe environmental conditions and forces such as winds. This will be achieved by carrying out a comprehensive Fluid-structure Interaction (FSI) analysis (combined computational fluid dynamics (CFD) and finite element analysis (FEA)) of the structural integrity and optical accuracy of the proposed system.

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The project will investigate modulation signal spectrum (MSB) analysis for the demodulation of cyclo-stationary effects at different high frequency resonance modes for monitoring the conditions of bearing and blades inside machine houses. Such bearings often operating at high temperatures such as gas turbines and large diesel engines, which is very challenge to be monitored. The research will investigate the broadband shift behaviours due to tribological effects between the sliding of bearing components. Then corresponding tri-axial responses measured by MEMS sensors at the free end of the rotors will be mapped to ones with low order stationarity and followed by MSB based noise suppression and nonlinear feature enhancements. Based on the behaviour of axial and radial responses, the modal response behaviours are characterised and subsequently based on for diagnosing the lubricity of defects of the internal bearings.

The techniques will be achieved with low cost MEMS accelerometers and can be deployed to monitor wide range of machines such as motors, aircraft engines, pumps, compressors and so on.

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The proposed PhD project aims to investigate the heat transfer characteristics of 3D printed metal surfaces using a coupled molecular dynamics-computational fluid dynamics (MD-CFD) simulation approach. With the increasing use of 3D printing in industry, it is important to understand how these surfaces behave under different thermal conditions.

The research will involve developing realistic 3D printed metal surface models that will be simulated using both MD and CFD simulations to understand their thermal behavior on a molecular and micro scale. The surface morphology will be characterized with state-of-the-art equipment at the school and implemented in the model. The two simulations will be coupled using appropriate numerical algorithms, and the results will be analyzed using advanced data analytics techniques. Open-sourced MD code, e.g., LAMMPS, and CFD software, e.g., OpenFOAM, will be used. Simulation results of heat transfer coefficients on different metal surfaces will be validated with experimental data.

The outcomes of this project will have significant implications for the design and optimization of 3D printed metal components. By understanding the heat transfer characteristics of these surfaces, it will be possible to optimize their thermal performance, efficiency, and durability. Potential applications include aerospace, biomedical, and energy systems, where 3D printed metal components are increasingly being used.

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A major challenge of additive manufacturing (AM) technology is that AM processes are not robust enough and AM production machines lack sufficient process control, which consequently brings various defects that are commonly seen in AM products, such as dimensional inaccuracy, rough surface texture, porosity, cracks, and entrapped powders. X-ray Computed Tomography (XCT) is often employed to non-destructively inspect internal defects of AM components, which does not have the light-of-sight restriction of conventional tactile and optical measurement techniques. However, current XCT data processing is insufficient to capture these internal defects in terms of accuracy and computation speed. This research project aims to develop a machine learning based approach to enable fast and accurate detection of internal defects of AM components. The deep learning techniques will be employed to enable the instance segmentation of XCT images containing various defect features. A hybrid approach comprising physical and simulated XCT scanning will be employed to generate the database for training the machine learning model. Virtual samples with intentionally seeded defects will be developed to facilitate XCT simulation. The project will be based on the Future Metrology Hub, the Centre for Precision Technologies, the University of Huddersfield. The selected student will be provided with training in XCT and simulation software and mentoring on machine learning.

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Modern manufacturing requires a high-performance, stable platform. Online verification, including surface-finish inspection is perceived as a huge benefit. With industrial sensor technology growing, and interest in the “industrial internet of things” (IIOT) the potential for sensor networks with massive data output is becoming a reality for many industries. This project is looking for a cost-effect solution to implement online surface prediction and stability monitoring based on IIOT and edge computing with traditional Digital Signal Processing (DSP). By the end of the project, a novel sensing network will be constructed which can sufficiently provide system dynamic information for predicting the surface finish of manufactured parts. In addition, a reliable data fusion method will be developed to interpret collected signals as a function of deviation between predicted and measured surface information. Finally, the project will propose a prototype control strategy based on the feedback of this surface examination.

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This is a fully funded research opportunity with a full EPSRC standard bursary payable

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Embedded sensors are prevalent in many industries, either as part of the function of a machine or for conditioning monitoring or quality control purposes. There is a need to simplify their integration by moving from wired to wireless sensing solutions. This also enables retrofit or ‘add-on’ systems that can be installed on older equipment to extend their usable life. This project will research new thermoelectric materials for energy harvesting, capable of high efficiency with ultra-low temperature differentials and incorporating novel surface characteristics to provide useable power for embedded wireless sensors in modern manufacturing industry. Current technology typically exploits the dynamic nature of machinery through piezoelectrics, hot processes through Pyroelectrics or some other method such as photovoltaics depending on the application. Within the Factory of the Future concept, part of the vision of Industry 4, extensive sensorisation is required on machines with inert structures having low waste energy under normal operating conditions. The research challenge includes the combination of high thermoelectric efficiency, novel cooling and intelligent power management combined in a novel mechatronic solution. The candidate should have an interest in materials science or a physicist with an interest in cross-disciplinary research to facilitate the mechanical, control and material aspects of the work.

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This research will incorporate a literature review to assess the current state of the art in surface technology. The ability to map sound pressure levels across 2D and 3D surfaces allows the user to assess any anomalies within a space resulting from poor architectural design and/or unwanted sound sources. The project will also aim to incorporate the design of a working prototype that will offer a faster and more accurate method of surface measurement through the use of a distributed parallel measurement system.

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Material at high temperature suffers creep damage resulting in the failure of its structural integrity. The main cause for such failure is due to cavitation at grain boundary for most of the engineering alloys, but the current research and knowledge is primarily empirical and phenomenological lack of the scientific understanding. This project will work on the development of the methodology and its application to creep cavitation damage model at grain boundary, for high Cr alloy. The result will provide a more accurate presentation and modelling of the cavitation damage. * https://pure.hud.ac.uk/en/publications/development-of-the-fe-in-house-procedure-for-creep-damage-simulat

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This PhD will be carried out within the wider project ‘Next Generation Metrology Driven by Nanophotonics’, https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/T02643X/1, which brings together researchers from the University of Huddersfield’s Centre for Precision Technologies and the University of Southampton’s ORC, to translate the latest advances in nanophotonics, plasmonics and metamaterials research into metrological applications (metrology being the science of measurement). Such approaches will allow us to overcome existing problems and to implement new methods and techniques that these new approaches make possible.

Lenses are a staple of optical instruments, but their size and weight are a real barrier to miniaturization of the instrument. However, by looking to replace traditional lenses with metalens alternatives real progress could be made. This project will look to develop lenses suitable for use in real world applications and whose performance is closely matched with, and optimized for, the requirements of several optical techniques (such a confocal, phase shifting interferometry and focus variation).

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Model-Based System Engineering (MBSE) is a solution that targets the increase of productivity, improvement of product quality and risk management throughout the life cycle, based on the application of Uniform Modelling Language (UML), conceptual graphic model and informatics exchange techniques. For modern machining processes, the analysis of surface formation needs to consider vibration and thermal impacts simultaneously. An effective MBSE is an ideal solution for quickly identifying and adjusting machining plans based on the complete analysis of system stability from collectable information of the CNC. The target of this project is to design a 3D graphic MBSE which is suitable for precision metal-cutting tasks. The new MBSE needs to satisfy the following requirements: • An explicit and efficient information exchange system integrated with the 3D virtual CNC model • The basic data storage and management function • The basic signal processing and physical modelling of machining process • The machining strategy planning and self-optimization module The candidate should have a good background in computer programming, databases and mathematical modelling. A logical approach and an interest in manufacturing applications are essential.

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Precise and timely notice of abnormal behavioural patterns in mechanical processes is vital to ensure continued output quality and avoid unplanned interruptions or deviation from optimal operation. On-line monitoring of systems is now commonplace with a plethora of data available for analysis. Charting process behaviours and so identifying fault blueprints at the earliest possible onset is an essential modelling procedure. This project aims theoretically and experimentally to establish fault classifiers for monitoring mechanical processes. Thus sound theoretical models are first established then demonstrated and evaluated by application in an experimental setting.

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The vibration characteristics of rotors supported by bearings will be significantly affected by bearing clearances which are often arisen due to inevitable light wear during services along with thermal effects. Such clearance induced vibration often leads to pre-matured faults to various rotor systems such as wind turbines, gas turbines and aircrafts.

The clearance in bearings will introduce non-smooth and discontinuous nonlinearities in the system which makes it difficult to predict the dynamics of the rotor and develop effective fault diagnostic approaches. The aim of this project is to establish the analysis model of such systems and to solve the nonlinear dynamics using appropriate methodologies. Experimental test rig will be designed to validate the theoretical observations and nonlinear uncertainties due to incipient changes in the clearances and misalignments. It will lead to accurate signal processing tools to monitor the fault of clearance.

The project will require a good background of mechanical engineering. Vibration and dynamics are more suitable. Good theoretical background and implementation skills of numerical simulations using Matlab/Simulink and other software packages will be appreciated.

Wind turbine, aircraft engines, marine power trains, and compressors in different process industries will be the targeted applications in terms of the digital twin monitoring system.

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Material at high temperature suffers creep damage resulting in the failure of its structural integrity. The main cause for such failure is due to cavitation at grain boundary for most of the engineering alloys, but the current research and knowledge is primarily empirical and phenomenological lack of the scientific understanding. This project will continue and expand the recent breakthrough in modelling of creep cavitation and creep rupture led by Dr Qiang Xu. It aims to develop further the mathematics method for and apply to more accurately on the cavitation process with further improved accuracy. It is anticipated to produce international excellence/leading quality output. The experimental data to be utilized will be taken from primarily from X-ray Synchrotron measurement such as from Spring-8 (Japan) or ESRF (EC), et al. https://www.tandfonline.com/doi/full/10.1080/09603409.2017.1388603 & https://pure.hud.ac.uk/en/publications/modelling-of-creep-deformation-and-fracture

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Cracks develop after repeat contact passes between rolling elements. Contact between rolling elements are an extremely importance engineering application including the rail-wheel interface, bearings and gears. Modelling the rate of growth of the cracks accurately will allow better designs and maintenance planning, but the modelling of crack growth under these loading conditions poses some unique challenges as well a regular remeshing as the crack both increases in size and changes direction. This project aims to develop a scaled boundary finite element formulation suitable for rolling contact fatigue cracks and implement this within an existing finite element code (Abaqus or ANSYS) or via a bespoke code. Scaled boundary finite elements are a relatively new finite element method making use of polygonal (in 2D) shape elements, which can accurately describe the complex stresses around the crack tip. Further, these elements allow for easy and localised remeshing around the new crack tip while this grows.

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This PhD will be carried out within the wider project ‘Next Generation Metrology Driven by Nanophotonics’, https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/T02643X/1, which brings together researchers from the University of Huddersfield’s Centre for Precision Technologies and the University of Southampton’s ORC, to translate the latest advances in nanophotonics, plasmonics and metamaterials research into metrological applications (metrology being the science of measurement). Such approaches will allow us to overcome existing problems and to implement new methods and techniques that these new approaches make possible.

Metasurfaces (surfaces patterned with arrays of subwavelength elements) offer a way to achieve the exquisite control light, and this can be used to reproduce the effects of traditional optical elements, for instance a metalens will focus light in the same way as a refractive lens. There is no reason though that metasurfaces need to mimic the effect of existing optical components, and if a single metasurface can change a wavefront in a manner that would traditionally need multiple optical elements all the better, there is then no need to align the different elements and make sure this is maintained. This will lead to the development of ultra-compact optical instrumentation, and allow the new possibilities that such control of light open up to be explored.

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Polishing is an essential operation in the manufacturing process of many engineering components. These components include those made of glass, metals, alloys, and fibre reinforced polymeric composites etc. Conventional continuum based CFD modelling of micro-sized solid-liquid mixtures used for polishing provides limited information due to the different length scales involved. However, coupling continuum based CFD with Molecular Dynamics allows for a parallel hybrid system, where the strengths of each approach could be utilised. In this proposal, the polishing process, would be modelled by applying CFD at the macroscale length scale while Molecular Dynamic would be used to solve Microscale length size phenomenon.

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Developing a multi-scale model, with computational fluid dynamics and molecular dynamics for mechanical polishing simulations. Polishing is an essential operation in the manufacturing process of many engineering

components. These components include those made of glass, metals, alloys, and fibre reinforced polymeric composites etc. Conventional macroscopic CFD based modelling of the small solid particles used for polishing is challenging, due to the different length and time scales involved. However, coupling macroscopic CFD with MD allows for an efficient parallel hybrid system, where the strengths of each approach can be utilised. For this research, conventional CFD techniques would be used to solve the macroscale length scale phenomena, while MD would be used to solve microscale interactions.

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Additive manufacturing (AM) is expected to have a profound impact on the way manufacturers make almost any product. It has already made transformation improvements to productivity and opportunity exists to go further. Surfaces generated by AM methods are normally complex and high dynamic in terms of surface reflection and diffusion. Currently 3D vision, photogrammetry, fringe projection and deflectometry are widely used for surface shape measurement. However due to complex of the AM processed surfaces none of the above mentioned method can satisfy the demand of the AM processed surface measurement. A multi-sensor intelligent measurement system for 3D high dynamic complex surface measurement is proposed. The system combines fringe projection, photogrammetry and deflectometry system to tackle the difficult of high dynamic and complex surface shape measurement. You are expected to: 1) develop the calibration methods for the system 2) develop artificial intelligent methods to select the best measurement system according the surface under test
3) develop data fusion algorithms to combine the data sets from multi sensors 4) verification of the measurement results and the multi-sensor measurement system

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Multibody dynamics methods have established the grounds for advanced dynamic analysis applications, able to simulate mechanical systems. Multibody models are generally composed by a set of interconnected, rigid or flexible, bodies which undergo large translational and rotational displacements. Hence, large and complex mechanical systems are able to be analysed and studied in a computer-aided environment. The aim of this work involves the development and employment of multibody methodologies to produce realistic and accurate railway pantograph models. The pantograph is today a critical mechanical system in the operation of electric traction trains, both at conventional and hight speeds. The models developed are to be validated with experimental data obtained from line tests and/or test bench tests. The work here developed will allow to produce more accurate, realistic, and robust pantograph models, and better understand its mechanical behaviour when interacting the electrified overhead line.

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Chemo-mechanical damage in energy materials alters their performance. The damage is initiated at the surfaces and interfaces, which are the most affected by the conditions of the environment, and the mechanical corrosion and erosion. We propose a multiscale modelling framework to unravel the coupling of this damage and the properties of the material. Linking atomistic and continuum modelling will deliver a description of the origin of the chemo-mechanical damage at different length and time scales. This will provide design and engineering rules for damage-resistant materials.

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This project will develop a multiscale modelling framework to provide models for materials interfaces and analyse their performance. Thus, it fits the Energy theme (priority area of materials for energy applications) and the Engineering theme (materials engineering, and fluid dynamics and aerodynamics). The project therefore fits the strategic priority of “21st Century Products” for developing multi-functional materials, and Productive Nation for advancing materials engineering and future technologies.

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Over 1-billion people live in regions where water is scarce and are unable to afford fresh water for their daily basic needs. Because of this, goal six of the United Nations’ Agenda 2030 considers water accessibility as paramount to reaching its sustainable development goals. As a result of freshwater resources depletion, numerous methods have been developed to generate fresh water from non-potable sources. However, most of these technologies, such as reverse-osmosis systems, are implemented where abundant conventional energy resources are available. Furthermore, such technologies often require large amounts of energy to operate and face economic challenges when being scaled down. This makes solar distillation one of the most practical solutions to the production of fresh water particularly in regions endowed with high solar energy potential.

Despite their relative simplicity, double slope solar stills remain one of the most viable solutions to the production of freshwater from saline and non-potable water sources. Natural convection inside double slope solar still enclosures is influenced by the cavity’s geometrical parameters. Though, the several existing correlations that have been established for solar stills led to several recommendations relating to the geometry of stills having developed that do not appear to have a sufficient evidentiary basis. Furthermore, over the years, numerous researchers have attempted to improve the yield of double slope solar stills through changes to their geometry and the use of various design modifications. Despite this long history of research, one modification that has not been fully explored is the use of passive baffles to alter the natural convection inside them. Though baffles have frequently been used to suppress natural convection in enclosures, there may also be the opportunity to use them to enhance natural convection. This judicious placement of baffles to enhance the natural convection could potentially improve the yield from single slope solar stills, however it has not been well explored in the literature.

To address this issue, this work will thoroughly examine natural convection in double slope solar stills and investigate the effect of geometrical parameters and passive baffles on the natural convection inside the double slope solar still geometry. Computational fluid dynamics (CFD) simulations and experimental PIV and water collection validation will be conducted to explore the effect of multiple parameters including aspect ratio, cover angle, baffle length and position on stills. Finally, the work will lead to the development of a generalized relationship to describe the effect of geometrical parameters and baffles on natural convection, that it is hoped will aid designers of double slope solar stills in the future.

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Background
The UK manufacturing industry stands on the threshold of a technological revolution and a digital transformation, and precision metrology is generally considered a key component and foundation for the development of advanced manufacturing. For example, deep ultraviolet mask aligner contains more than 70,000 optical components, of which more than 80% are at the precision and ultra-precision level, requiring more than 700 professional precision and ultra-precision measuring instruments to control manufacturing accuracy. Techniques based on structured light (e.g., phase measuring deflectometry, and fringe projection profilometry) are the most popular optical methods for surface form metrology due to their wide measurement filed, non-destructive measurement, high resolution, and fast response. However, most optical systems are still reliant on bulk glass and metal elements to control the light. This places fundamental limits on our ability to produce more compact versions that can be better integrated into production lines for the purposes of improving manufacturing metrology and supporting Industry 4.0 and beyond.

Aim and Objectives
The project aims at researching and developing the underlying science and technology for the creation of an on-chip integrated structured-light metrology system, the first of this kind in the world, that can meet the increasing needs of digitalisation of engineering and the development of smart manufacturing with extremely shrinking system volume (up to three orders of magnitude). The principal objectives of the project are to investigate and create: 1) novel structured-light generation and imaging techniques based on metasurfaces to replace conventional bulk optical elements for creating the desired optical functions on a planar device; 2) novel optical path design methods, system calibration/alignment methods, and data fusion methods for the structured-light metrology system; 3) artificial intelligence (AI) algorithm for accelerating metasurfaces’ overall design and optimization and for smart shifting of laser channels according to materials and roughness of the measured surface to improve productivity and measurement accuracy; 4) integration technique with precise alignment of metasurface-based elements for generating an on-chip structured-light system.

Methodology The project will develop the next-generation structured-light metrology system based on metasurfaces. Metasurfaces-based structured-light generation and imaging techniques will be investigated by combining the existing knowledge in the CPT to replace bulk optical elements, such as projector, screen, and optical lenses. New methods with the support of AI algorithm will be applied to accelerate metasurfaces’ overall design and optimization. Precise alignment of metasurface-based elements and overall integration technique will be studied for generating an on-chip structured-light system. Configuration, system calibration/alignment method, and data fusion method will be investigated for generating the new metrology system. Prototypes developed based on the metasurface-based system will all be tested in in-line manufacturing system and will be transferred to commercial device under the support of company partners.

Research environment The University of Huddersfield has an unrivalled track record of internationally leading research in the field of surface metrology and applications, mathematics for metrology and machine tool metrology. CPT and the Future Metrology Hub has undertaken leadership of several EU and EPSRC projects, which are equipped with state-of-the-art ultra precision machines and surface metrology equipment. CPT and the Future Metrology Hub will provide strong support to the proposed project in experiment space, and precision equipment such as optical platform, visible laser devices, precise mobile platform, imaging devices, etc.

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To explore multivariate statistical modelling processes such as principal component analysis (PCA) to facilitate detection of abnormalities in process performance and condition. Whilst many variables may exhibit strong linear correlations many more do not and do not possess feasible transformation properties. Mappings may be one to many or possess enclosed domains so require higher dimensional kernel functions. Wavelet transforms may also be necessary to unlock salient trends and de-noise signals under consideration. PCA extensions, such as Kernel and Multiscale PCA offer potential solutions. The higher the degree of accuracy in modelling data dynamics the greater the predictive potential of subsequent models. The research aims to provide a novel strategy for detecting and diagnosing deviant events in mechanical processes by extending existing PCA practice and conjoining with current wavelet decomposition methodologies.

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Inkjet printers are now seen as a potential approach for the manufacture of electronic devices. The ability to precisely and repeatably deposit material on a wide variety of substrates enables a wide range of novel technology, including flexible and wearable electronic devices and organic light emitting diode displays. This project aims to use numerical methods, specifically, the lattice Boltzmann method, to investigate the evaporation dynamics of inkjet printed droplets on surfaces which have been prefabricated to aid in the controlled position of droplets. These surfaces have a combination of chemical and topographical features, which effect evaporating behaviour.

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Biogas is a well-known technology for generating renewable energy and the end product of any anaerobic digestion (AD) process. The gas produced by AD contains hydrocarbons (methane), CO2 and H2. We are fortunate to have a well-designed AD unit on campus (MyGug) that was delivered in March 2023. The unit has been designed to convert household and business waste food to gas energy and additionally produces a digestate that can be used as a high quality fertilizer. There have been several studies on the effect of the feedstock on the AD process and products. However, there are still very important and essential parameters that need to be consider and there is a lack of research in this area; The fact that some AD units are designed for household and business, questions the use and study of separate and single feedstocks. In the domestic usage case, the feedstock is usually a mixture of waste food and separating it by the user is not practical. Although AD units already have significant environmental and waste control benefits, the efficiency of them and rate of gas production is not financially beneficial for the target users. The goal of this project is to combine the academic knowledge and a real-life problem and to optimize the AD process and products in order to make it financially and environmentally beneficial for household and business users. To improve the energy balance, different fields need to be studied such as; - Characterization of the products after each iteration of feedstock change. - Addition of different organic and environmentally friendly chemical agents to the feedstock to increase the gas production rate and amount of methane in the gas product. - Finding suitable bacteria for different types of feedstock. - Mechanically modifying the individual parts of the unit if necessary.

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The powertrain including fuel-cell, battery pack and e-machine requires a high-level energy management system (EMS) to maximize performance efficiency and minimize system loss. In practice, due to its characteristics, the battery energy capacity relies on its state-of-charge (SoC) and state-of-health (SoH) as well as battery temperature. The PEM fuel-cell performance highly depends on PEM temperature and could not swiftly react to a transient load demand. On the other hand, the battery pack allows short-period overload performance. During the tractor operation, mode changes between push/pull, driving, PTO, and auxiliary load such as lifting are often required. Therefore, based on operation conditions and monitored information of battery pack and PEM fuel-cell system, the power split between the battery and the PEM fuel-cell must be well controlled by the EMS to maintain the demanded load with minimizing of hydrogen consumption.

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In recent years, robotics have revolutionized manufacturing and production processes, significantly improving efficiency and productivity. However, the integration of robotics into maintenance activities poses a unique set of challenges. One technical challenges is that the objects are not quite clean and worn in maintenance environment. Thus there is a big challenge for traditional vision system to distinguish the objects for the robot, particularly in fields like rolling stock maintenance. Therefore, the aim of this research is the development an embedded sensors combining with machine learning techniques to help robot doing his task in complex environment like rolling stock maintenance task. The research methodology involves a systematic approach, including sensor selection and integration, data pre-processing and fusion, machine learning model development and training, and real-time implementation on robotic platforms. Prototyping and iterative testing will be conducted to refine the algorithms and ensure their effectiveness in real-world scenarios.

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This project is offered by the Institute of Railway Research (IRR) at the University of Huddersfield using the newly developed HAROLD 2.0 full-scale bogie test rig.

Effective control of friction between the wheel and rail on railways can yield various advantages, including improved safety, increased asset life and reduced environment impact (i.e. reduced fuel consumption, particulate emissions and noise emissions). To control friction, a variety of "Friction Management" solutions are utilised, including "Gauge Corner Lubrication" and "Top-of-Rail Friction Modifiers". During development, the performance of Friction Management products is usually assessed on small-scale test rigs, most commonly, "Twin-Disc" test rigs.

To date, research into the scalability of results is typically performed using real vehicles on test tracks (a difficult to control/measure environment), or on a full-scale test rig, but at much lower speeds. The use of HAROLD 2.0 represents an opportunity to investigate the performance of Friction Management products using a full-scale bogie operated at realistic speeds in a controlled laboratory environment.

HAROLD allows a full-scale bogie to be run on a 2m diameter roller representing the rail. The roller operates at up to 200kph, and the position of the bogie can be manipulated to simulate curving. A recent upgrade (HAROLD 2.0) now allows the bogie to apply traction and control creepage between the wheel and rail.

This project is likely to utilise other IRR test rigs, such as our own "Twin-Disc" test rig. There may also be opportunities for collaboration with other research groups and industry suppliers with an interest in wheel-rail friction management.

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Dielectric materials constitute critical components in devices ranging in scale from the field effect transistors in cutting edge solid state electronics to high voltage super-grid transformers and, as such, the reliability of all of these is directly linked to the reliability of the dielectrics on which they rely. As the demand on electrical power is continuously increasing, advanced dielectric materials are required to enable power transmission at higher voltages. This has motivated many research groups worldwide to explore the potentials of improving the electrical performance of the currently employed polymeric insulation materials by filling them with inorganic nanoparticles (i.e. forming nanocomposites). This project will investigate the electrical properties of nanocomposites and the mechanisms that control the electrical behaviour of these systems. Specifically, the project will focus on the impact of the surface structure of nanoparticles and the presence of specific functional groups on the electrical properties of nanocomposites.

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Classification of categorical events using advanced statistical models to detect and identify component faults and deviations from normal healthy operation in mechanical processes is fundamental to modern process monitoring. Variability of operating conditions may be revealed through analysis of output signals recorded at strategic points of a process, vibration signals for example. Subsequently, tolerable degrees of imperfection in specific components can be established. Hence, predictive models are developed and inform process condition including quality and safety aspects. Experimental data generated from mechanical rigs with and without seeded faults is to be collected and analysed. Comparison of ‘normal’ behaviour with deviant behaviour offers a means of investigating signal patterns which indicate performance quality. Rules are thus established to identify operational problems and predictive classification models may be formed.

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Future generations of nuclear reactors will require advanced materials which can withstand the extreme conditions anticipated in such systems. These include elevated temperatures, high neutron fluxes and corrosive environments. Such materials are being developed around the world but need testing to assess their suitability and require investigating to understand the nature and driving mechanisms behind the micro-structural changes they will experience whilst in-service.

One way to rapidly-test candidate materials is to use ion beams which do not incur the hazards, costs and delays associated with neutron irradiation. Transmission electron microscopy allows the internal micro-structure of materials to be explored as changes on this scale determine the performance of materials at the macroscopic level of nuclear reactor components. The Microscopes and Ion Accelerators for Materials Investigations (MIAMI) facility at the University of Huddersfield combines these two techniques to allow the real-time observation of the dynamic evolution of radiation damage in materials under simulated nuclear reactor conditions. Being one of only a dozen such facilities globally which are able to perform such experiments provides unique opportunities for scientific discovery.

This PhD project offers the opportunity to use the unique capabilities of MIAMI to undertake research into novel nuclear materials produced in-house at the University of Huddersfield and also developed by our global network of academic and industrial partners.

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Radiation damage in nanostructures is an area of intense scientific research with applications in many areas. For example: the response of semiconductor nanowires to irradiation used to engineer such structures as well as to that experienced when in-service in extreme conditions; the design of radiation-hard nanoporous nuclear materials which derive their resistance from their high surface-to-volume ratios; and the understanding of radiation effects in nanoparticles exposed to extra-terrestrial environments to explore the evolution of the cosmos.

The processes behind radiation damage in materials are both complex and dynamic. Therefore, to gain fundamental insights into these phenomena and the mechanisms which drive them, it is invaluable to be able to observe the changes in real-time at the nanoscale at which they occur. The Electron Microscopy and Materials Analysis (EMMA) Research Group at the University of Huddersfield specialises in the investigation of radiation damage in materials using transmission electron microscopy with in situ ion irradiation which allows exactly this type of experiment to be performed.

The successful applicant will have the opportunity to use the Microscopes and Ion Accelerators for Materials Investigations (MIAMI-1 and MIAMI-2) facilities at the University of Huddersfield which combine transmission electron microscopes with ion beam systems to allow in situ studies of radiation damage effects at the nanoscale. MIAMI-1 has a track record of research in nanostructures including graphene, gold nanorods, nanodiamonds and semiconductor nanowires. The new MIAMI-2 has recently been completed with £3.5M funding from the United Kingdom’s Engineering and Physical Sciences Research Council (EPSRC) and is a state-of-the-art facility with world-leading experimental capabilities. The PhD candidate appointed to this fully-funded studentship will have the opportunity to work alongside colleagues on existing projects on nanostructures to develop their skills and knowledge before choosing the specific area in which they are most interested in pursuing for their own research.

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In all FSI problems, a structure subsystem and a fluid based subsystem are coupled together and the resultant characteristics of the combined coupled system are different from each individual subsystem. Sometimes, in numerical simulation of FSI problems, the system is broken down into a fluid simulation subsystem and a structural dynamic subsystem, and the coupling between these two subsystems is maintained by a feedback/feedforward communication algorithm. There are several limitations of numerical simulation of either subsystems in FSI problems, and hence sometimes it is necessary to carry on experiments. However, setting up a complete FSI test platform is expensive or sometimes is impossible due to the size/equipment limitations or nonlinearities involved in either subsystems. Therefore, it is possible to use hybrid testing to overcome the difficulties of a full FSI test or to reduce the cost of testing. In this project a simple real-time FSI problem is considered as a combination of a vibrating structure with a fluid flow affecting the structure response. The interaction between these two subsystems will be maintained using properly located actuators. The project aims to address the challenges and critical technical problems of a real-time hybrid FSI testing, and shed light for designing a novel real-time hybrid testing platform for flexible structures.

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Advanced materials such as Ni-based superalloys, SiC, and Fiber-Reinforced Plastics (FRP) composites have found increasing applications in aerospace, semiconductor, biomedical engineering, and other critical industries due to their exceptional performance characteristics. Nonetheless, the challenges of severe tool wear and low productivity pose significant obstacles in the realm of high-precision machining of these materials.

To address these challenges and enhance manufacturing quality, there is a pressing need to develop a physics-based multiscale simulation approach. This approach would involve the integration of cutting-edge simulation theories, notably discrete dislocation dynamics and crystal plasticity. The simulation results derived from this method would then be validated through experimental tests, with further utilization in the design and optimization of these experiments.

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There has been an increasing demand for high-precision components or structures at sub-micro/micro scales because of their wide applications in various industries, like telecommunications and biomedical engineering, optics, etc. In the past few decades, micro-cutting has become a key technology to produce complex structured micro-components/products owing to its high flexibility and high accuracy.

The micro-cutting can be taken as a scaling-down version of the conventional cutting process, but the decrease of machined component size or feature size will lead to many materials-related issues. The depth of cut in micro cutting is usually in the same order or even less than the material grain size. Every single crystal has its crystallographic orientation, and thus it is important to take into consideration the material anisotropy in the micro-cutting process. Hence, the plastic deformation behaviour of materials at sub-micro/micro scales is important to understand the material removal process during micro-cutting.

To reveal the underlying micro-cutting mechanism and hence to improve the manufacturing quality, it is necessary to develop a physics-based multiscale simulation method by coupling advanced simulation theories, like discrete dislocation dynamics and crystal plasticity. Compared to experimental tests, computational simulations can provide more real-time information during machining and are easier to perform. A multiscale simulation method, which couples two or more different scaled simulation methods, can both provide a detailed description of microstructure evolution and efficiently deal with the complex boundary conditions during the machining process.

This research project aims to reveal the machining mechanism of brittle materials during micro-cutting by developing physics-based multiscale simulation methods. The simulation results need to be verified by performing experiments, and further are used to design and optimize the experiments. The objectives of this project include: • Develop multiscale physics-based models with internal state variables. • Verify the developed model by comparing it with the experiment results. • Reveal the micro-cutting mechanism of brittle materials with the developed model. • Optimise the micro-cutting parameters to improve the efficient machining of brittle materials.

The Ultra-precision Manufacturing Lab at the University of Huddersfield has state-of-the-art facilities to advance this exciting research, such as the high-quality simulation workstation, and the world’s most advanced 5-axis ultra-precision diamond turning machine. The researcher can also enjoy easy access to various metrology instruments, including surface profilometer, XCT, CMM, SEM, etc

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This project will address the following hardware constraints of 5G mm-Wave system:

• The mm-Wave band allows us to pack more antennas in the same place which reduces the antenna aperture, resulting in less power captured by the receiver. • The wider bandwidth makes the multipath profile sparse, resulting in a large number of resolvable multipath at the receiver. The complexity of the receiver will be extreme if all these multipaths are resolved. • This wider bandwidth requires an analogue to digital converters (ADC) of higher resolution resulting in a large amount of energy dissipated.

The project will tackle the above issues by designing new signal processing algorithms.

• Proposed signal to noise ratio (SNR) algorithms and the 30 channel will allow rejecting the nearby interferers by the help of angle of arrival (AoA) and angle of departure (AoD) improving the power captured by the receiver. • New techniques will be proposed where multipaths with higher energy are selected and resolved, resulting in reduced complexity and similar performance. • ADCs will be designed that will not operate at the Nyquist rate resulting in less power dissipated.

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The aim of the research work is to develop an inverse design methodology to develop a unique surface profile for a required functional performance (flow behaviour) and hence it will involve development of an algorithm to generate surface profiles from geometrical parameters characterising the surface as well as develop molecular flow model for flow near the wall surface having artificially created roughness and establish quantitative dependence of surface parameters with flow features very close to the wall. Furthermore development of computational fluid dynamic simulations (continuum based) for flow over wall surface and establish quantitative dependence of surface roughness parameters with flow features away from the wall will be an essential part of this project.

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CPT has developed leading technology in advanced on-machine interferometry systems for use in manufacturing environments, evidenced by the vibration-compensated wavelength scanning interferometer (commercialised by IBS Precision Engineering in Netherlands), high-speed dispersive reference interferometer (transferred to Renishaw), and single-shot dispersive interferometer (demonstrated in a pilot test cell at CPI). These interferometers have been successfully mounted on-machine in manufacturing conditions, overcoming environmental challenges such as vibration and temperature. Nevertheless, rigidly mounting these instruments on a manufacturing platform has limitations, as not all platforms offer sufficient space. In this case, an alternative to perform metrology in a production line is to use robot-mounted inspection technologies, which are widely used with camera vision, laser scanning and structured-light 3D scanning. As for interferometric sensors, they can provide nanometre-scale measurement resolution under a well-stabilised environment. Integrating an interferometer into a robotic arm will offer flexibility to inspect complicated surfaces by approaching them from different directions, without taking up space in the machine. This combination will extend its capabilities for precision measurement, automation, and control across a wide range of industries and applications, providing a powerful tool for tasks that require high accuracy, repeatability, and efficiency. However, implementing robot-mounted interferometry sensors into a production chain brings significant challenges in automated and precise alignment, high-accuracy fringe analysis, and high-efficiency data interpretation to guide the measurement and manufacturing process. This project aims to tackle these challenges by investigating artificial intelligence-enabled automated robotic interferometry systems to perform high-precision measurements in complex and dynamic environments, eliminating the need for time-consuming and skill-intensive re-alignment after positioning. The proposed work includes 1) AI algorithms for automated alignment following positioning, along with compensation for position and angular misalignments resulting from environmental disturbances and errors in Robt movement; 2) AI-assisted data analysis to facilitate smart signal processing and accurate phase extraction even when dealing with complex fringe patterns, enabling accurate surface topography determination; 3) AI algorithms for the interpretation of measurement data and efficient management of large datasets, enabling robotic sensors to not only collect data but also make real-time decisions based on the information received from sensors. This PhD will be carried out at the University of Huddersfield’s Centre for Precision Technologies (CPT), which hosts a well-equipped state-of-the-art Optics Lab specialising in optical metrology research. The lab is well equipped for the tasks of instrument development and characterisation, and its facilities are widely acknowledged as being among the best in Europe and are certainly unique in the UK. The supervision team will leverage an existing relationship with CPT’s sub-group (the Engineering Control and Machine Performance group, ECMPG) and the Robotics group at the University of Bath, with whom we will collaborate for access to their robotic machining cells and extensive experience in robotics control.

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The importance of computed tomography (CT) measurements is increasing in the fields of dimensional and surface metrology. The typical workflow of a CT measurement, after the volume reconstruction, consists in applying an edge enhancing filter to remove the noise and performing the segmentation in order to find the object of interest. Modern CT devices may produce volumetric dataset of 2000 x 2000 x 2000 voxels, the size of the dataset is approximately 30 GiB. Though the data size is high, only a small portion of the volume is needed: the voxels around the surfaces of the objects. The total number of the voxels around the surface that has to be exacted is usually less than one tenth of the total number of voxels of the volume. The aim of the project is to is to use sparse volume data structure to convert a dense volume into a lighter representation. Using a sparse data structure allows faster filtering and segmentation processes. Mathematical models able to perform the segmentation of object with the accuracy required in the metrology will be designed. The candidate should design algorithms that work both multithreading CPU and GPU to use the advantages of modern graphical cards.

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This PhD proposal addresses the problem of thermal insulation and reinforcement of masonry buildings with new advanced materials. Thermal insulation helps reducing energy consumption for heating and cooling, thus lowering utility costs and minimizing environmental impact. Furthermore, reinforcing masonry structures with modern materials improves their durability and resilience against external forces such as seismic activity, and structural loads. This reinforcement increases the safety and longevity of the building, reducing the risk of collapse during natural disasters or other emergencies.

Incorporating new materials for insulation and reinforcement allows for innovative solutions that offer superior performance compared to traditional methods. These advancements not only address existing shortcomings but also contribute to sustainable construction practices by promoting energy efficiency and structural integrity. Overall, the integration of new materials in masonry buildings is crucial for enhancing their functionality, safety, and environmental sustainability.

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This project is in the area of smart materials, one of the hot topics in the modern technology, and concerns the design of novel materials whose thermal characteristics could be controlled by varying the degree of geometrical anisotropy within complex/heterogeneous structures. The application of such materials is desirable in many situations including building insulation, automotive, electronics or defence. One simple arrangement for such smart materials is a suspension of disk-like particles in a liquid. Here, the modifier of system’s thermal properties could be an external field (electrical, magnetic), which could change particle orientation. Such structures could act as “shutters” for various heat transfer mechanisms (radiation, convection and conduction), or could be engineered in such a way that the ratio of one heat transfer mechanism to another could be controlled. The project aims at conducting numerical modelling of such materials in order to develop new concepts in controlling heat transfer processes. (Industrial relevance: energy, building and construction industries, defense)

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Traditional approaches to cooling/refrigeration/air conditioning are commonly based on vapour compression cycles that are driven by electrical input to the compressor. In the age of “environmental sustainability” these have major drawbacks of using as working fluids chemicals that are harmful to the environment and draining the electricity that in some instances may be in short supply. This project will investigate the provision of cooling/refrigeration/air conditioning capabilities for either industrial or domestic applications by using the coupling between solar power driven thermoacoustic engine and a thermoacoustic cooler. Thermoacoustic technologies utilised here are one of the emerging energy technologies with a significant future potential for providing cost-effective thermodynamic conversion processes. Thermoacoustic effect relies on the energy transfer between a compressible fluid and a solid material in the presence of an acoustic wave and thus allowing for the construction of thermodynamic machines with no moving parts.

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This study encompasses two main areas aimed at enhancing our understanding of spatial audio and its impact on the consumers’ experience. Firstly, it conducts perceptual listening experiments using popular music mixes from different genres to explore consumer perspectives on the overall listening experience, immersion, and related attributes. The experiments cover various environments (ITU standard rooms, headphones, sound bars), revealing how spatial audio impacts perception under different conditions. Secondly, the study develops a comprehensive questionnaire aligned with the listening experiments. The questionnaire uncovers factors influencing consumer preferences and experiences regarding spatial audio. A holistic understanding of how spatial audio affects the listening experience is established by linking the questionnaire with the experiments.

Funding

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Outline

Thermal barrier coating (TBC) is widely used to protect engineering surfaces at elevated temperature. Gas turbine gas washed surfaces, notably in the high-pressure turbine (HPT) see a critical application of such coatings. The practical limitations of the TBC processes, surface finishing and component geometry often lead to significant spatial variation in aerofoil surface texture. Consequently, there are component surface conformance and engine performance uncertainty issues. The aim of the project is to investigate HPT aerofoil TBC surface character, its variation and defects in terms of coating and finishing processes and inform the process of improving engine performance. Project objectives: • Carry out the detailed spatial surface characterisation of a range of coated HPT blade and guide vane surfaces • Correlate this spatial surface characterisation data with the TBC process parameters and component geometry • Correlate spatial surface character with the existing understanding of skin friction on turbine gas washed surfaces • Use spatial analysis results to inform the development of coating and finishing process • Results will inform ongoing engine performance developments

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Outline

Metamaterials are artificially designer materials with unusual properties that primarily originate from their geometrical design at various length scales. Mechanical metamaterials have received a significant attention within medical and automotive industries due to their novel mechanical properties including adjustable stiffness, negative Poisson’s ratio (auxetic), making them a suitable candidate for energy absorption applications. Additive manufacturing technology opens a new door in the creation of such complex structures. If the material used in these structures possesses a shape memory effect, mechanical metamaterials can also display thermomechanical characteristics, the so-called 4D printing concept. When exposed to outside stimuli, including heat, light, magnetic field, and moisture, 4D printing of structures can change their configurations. The functionality of the 4D printing concept allows for the widespread usage of 4D printing of metamaterials in various applications. In this regard, 4D printing of metamaterials with fully reversible deformation behaviours and energy absorption is of a great interest. By employing shape memory polymers, reversible energy absorption in metamaterials can be achieved using 4D printing. Furthermore, techniques for hybridisation are now being applied to further increase energy absorption capacity. In comparison to structures built entirely from pure polymers, the hybrid structure created by mixing nanoparticles and pure polymers can increase the energy absorption capacity.

The aim of this PhD project is using experimental and computational studies to introduce novel mechanical metamaterials made of polymer nanocomposites for recoverable energy absorption applications additively manufactured by 4D printing technology. Keywords: Additive Manufacturing, Metamaterials, 4D printing, Nanocomposite

Funding

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Deadline

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Outline

Metrology systems cost is a major challenge inhibiting the uptake of embedded metrology more widely across many areas of manufacturing, particularly in those areas requiring high/ultra-precision. Traditional optical measurement, based on techniques such as interferometry, is often carried out by costly and sizeable instrumentation. Even where efforts have been made to miniaturise measurement technology, the underlying technology is bulk optics, which has a large component and assembly costs.

This project will investigate the creation of optical metrology systems on-a-chip, where monolithic photonic integration will be used to develop light sources, detectors and other sub-components necessary to development truly low-cost miniaturised sensors for the measurement of surface topography, layer thickness and displacement.

Optical design including modelling of components both in-air and in-waveguide will be required to develop front-end probing for the sensor. Gaining and applying a working knowledge of optical metrology techniques will be necessary to feed into the design and development of the monothically integrated photonic sub-components. Electrical and optical performance validation of developed photonic sub-components will also be an important activity. This will lead ultimately to complete systems integration, validation and a prototype device which will require the development of signal processing and calibration techniques prior to demonstration.

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Outline

This project relates to the prediction of railway track dynamics behaviour under train operation in view of predicting maintenance and design requirements. It requires the development of existing and new numerical modelling techniques, based on multibody system and finite element methods, to better predict track systems behaviour under its various forms (either ballasted or non-ballasted). A wide range of frequency needs to considered depending on associated damage mechanisms and in order to carry out design optimisation of the systems components. Key aspects of the work will be to develop improved understanding of the way in which the forces exerted by the train are supported and distributed through the rail, sleepers, ballast and substructure. The interdependent role of the subgrade in the performance of track and design characteristics is essential. Likewise improved rail materials have made a big impact on the performance of the rail but there is more to be done and this needs to be matched by improvements in other parts of the system. Discontinuities which exist at switches and crossings or rail joints as well as transitions zones are also key factors which need to be included in any analysis or model.

Funding

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Outline

Problem background: The ability of a train to brake effectively in low adhesion conditions is a consequence of the interaction between many train components; wheelsets, wheel-rail contact patch adhesion, dynamic brakes, friction brakes, sanders and brake controllers. In the presence of low adhesion conditions, the reduced accelerations achieved during traction and decelerations during braking, can significantly impact on journey times leading to delays across the network. Project aim: To optimise the train brake function at low adhesion conditions to avoid wheel damage, minimise braking distance, and minimise the power consumption. Project objectives: Develop a model for the current brake systems and validate it using experimental data. Propose and develop control system to overcome the current brake system problems at low adhesion conditions such as (train speed estimators, adhesion prediction). Propose a robust control strategy for the Wheel Slide Protection (WSP) to enhance the braking system performance. Study the feasibility of using electrical system instead of pneumatic system in the train brake system (performance and safety issues). Build Hardware in the Loop rig to test the developed control strategies. Candidate should have a degree in Mechanical/Electrical Engineering with strong background at maths and a good knowledge of MATLAB/Simulink software.

Funding

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Deadline

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Outline

The unprecedented growth of wireless traffic in recent years has led to the quest of next generation 5G mobile communication networks. The main targets of 5G network are 10-100x data rate, 1OOOx capacity per unit area, 10-100x connected devices, roundtrip latency(« 1ms), 10x energy efficiency, and support for Internet of Things (loT) applications. Motivated by the spectral inefficiency of orthogonal multiple access techniques in current mobile networks, non­ orthogonal multiple access (NOMA) has been recognised as a promising technique to significantly improve spectral efficiency of future wireless networks and is envisionedto be key component of the 5G networks. Power domain NOMA has been highlighted as a key technology to provide NOMA in 5G networks. In power domain NOMA, differentusers are allocated different power levels according to their channel conditions to obtain the maximum gain in system performance. Such power allocation is also beneficial to separate different users, where successive interference cancellation is often used to cancel multi-user interference. This project will develop highly-efficient, low-complexity, single-/ multi-user power domain NOMA transceiver solutions for 5G networks. The project will also focus on the applications of NOMA in loT where it is expected to provide useful results to achieve superior communication.

Funding

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Outline

With the rapid development of the Internet of Things (IoT), a continuous energy supply for electronics and sensors has become a key challenge to combat the shortcomings of the traditional battery. Triboelectric nanogenerators (TENGs) transfer mechanical energy from the surrounding environment into electricity providing a clean and distributed energy network. TENGs can harvest various forms of ambient energy such as human motion, wind, and vibration. The aim of this project is to examine materials and structures which could be used to enhance the triboelectric effect, the fabrication methods which can be used to optimise performance and durability, and the integration of TENGs with other energy harvesting technologies (e.g., piezoelectric and pyroelectric).

Funding

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Deadline

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Outline

The University of Huddersfield (Department of Engineering and Technology) has recently obtained from Ofcom an experimental licence for TV broadcasting in Ultra High Definition using the new HEVC codec (High Efficiency Video Codec-H265) in the area of Kirklees on Channel UHF 24 (498 MHz). The arrival of HEVC is a logical time for mature European DVB-T markets to consider switching to DVB-T2 and to introduce HEVC encoded services at the same time. The UK, for example, which already uses DVB-T2, would more than double its number of HD channels from 5 per multiplex to around 12 by switching to HEVC, thanks to the combined efficiency of HEVC, DVB-T2 and statistical multiplexing. Germany has recently launched DVB-T2 services with HEVC using the robust indoor reception mode to deliver up to 7 HD channels per multiplex to fixed and mobile receivers. A number of other countries are now actively making plans for combined roll-outs. This project requires knowledge of video processing-compression algorithms and of the DVB-T2 standard for digital television broadcasting. Various reception scenarios and geographical coverage will be investigated experimentally and theoretically during this project.

Funding

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Deadline

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Outline

This PhD will be carried out within the wider project ‘Next Generation Metrology Driven by Nanophotonics’, https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/T02643X/1, which brings together researchers from the University of Huddersfield’s Centre for Precision Technologies and the University of Southampton’s ORC, to translate the latest advances in nanophotonics, plasmonics and metamaterials research into metrological applications (metrology being the science of measurement). Such approaches will allow us to overcome existing problems and to implement new methods and techniques that these new approaches make possible.

Within the project nanophotonic, plasmonic and metasurface elements will be developed for use as components of an ultra-compact instrument, however at this point they will still need to be combined with other elements such as light sources and detectors/spectrometers. This PhD will focus on the development, characterisation and optimisation of such complete ultra-compact instrumentation which can then be deployed in real world manufacturing environments in ways which are currently unfeasible due to the bulky nature of current instrumentation. Such work is not trivial, and will need to take into account the difference between the nature of the elements used and traditional optical elements, however success could have significant impact on advanced manufacturing.

Funding

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Outline

This project relates to unsteady aerodynamics of swept wings and in particular addresses a challenging problem of the breakdown of leading-edge vortices. Vortex breakdown degrades the aircraft’s aerodynamic performance and induces flow field unsteadiness related to its varying location relative to the wing, interaction between port side and starboard side vortex breakdown regions, and generation of large-scale coherent structures causing significant aerodynamic loading. Current hypothesis is that the appearance of vortex breakdown is related to the overall balance of vorticity and the limited ability of the coherent vortex to convect the axial component of vorticity in the downstream direction. As the amount of vorticity continually increases, there comes a point when the excess vorticity can only be convected if the vortex structure changes. The proposed work will address these fundamental issues through wind tunnel experiments on a delta wing model using non-intrusive optical instrumentation and measurements of unsteady surface pressure. (Industrial relevance: aerospace)

Funding

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Outline

Electrochemical machining (ECM) is a technique for removing metal from the surface of a metallic material through an electrochemical process. The purpose of this research is to investigate the use of ultrasound as a fully passive (i.e. independent of process conditions), non-intrusive, in-line gap measurement device. Because of recent developments in the resolution of ultrasonic measurement technology, such an approach is now feasible. Another goal of the research is to look at how such continuous gap measurements may be utilised to improve accuracy in electrochemical machining. The technique is to be applied to complex shapes to illustrate shape optimization by gap control.

Funding

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Deadline

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Outline

Metrology applications require continuous monitoring of temperature changes for the detection of thermal errors in machine tools. Due to the current drive towards the use of IoT devices, smart wireless temperature measurement systems finding their way into industries to ensure continuous logging of temperature variation trends and feeding them into the thermal compensation system. Depending on the size of the machine, hundreds of temperature sensor may form part of the sensor network and receiving synchronised data from them continuously, wirelessly, calls for a robust system that can choose and switch between wireless protocols in case of breaks down of the current wireless method such as connection loss. This project aims to build a wireless system with various built-in wireless data transfer protocols with intelligent switching function to choose backup wireless methods to ensure continuous measurement.

Funding

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Deadline

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Supervisors

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We offer supervision to PhD level in a wide range of areas where we are carrying out state of the art research.

The School of Computing and Engineering has three institutes and a number of research centres and groups that cover a diverse range of topics within Mechanical and Electronic Engineering an example of these is featured below:

Browse our listed funded opportunities.

To find out more about the research we conduct, take a look at our Research, Innovation and Skills webpages, where you will find information on each research area. To find out about our staff visit ‘Our experts’ which features profiles of all our academic staff.

Student support

At the University of Huddersfield, you'll find support networks and services to help you get ahead in your studies and social life. Whether you study at undergraduate or postgraduate level, you'll soon discover that you're never far away from our dedicated staff and resources to help you to navigate through your personal student journey. Find out more about all our support services.

Researcher Environment

Our postgraduate researchers contribute to our thriving research [culture] community at Huddersfield, in return, we provide an experience that enhances your potential and inspires you to think big and become a globally competitive researcher.

Join our community of like-minded people who are passionate about research and gain access to world-leading facilities, advanced research skills training, and expert career advice.

Reduced inequalities

  • We recently ranked 6 out of 796 global institutions for reduced inequalities in the Times Higher Impact ratings – this recognises our research on social inequalities, policies on discrimination and commitment to recruitment staff and students from underrepresented groups.**

World-leading

  • We are in the top 50 UK universities for research power, and nearly two-thirds of our research environment is classified as world-leading and internationally excellent.***

As a researcher, you’ll gain access to our Researcher Skills Development Programme through The Graduate School, to help broaden your knowledge and access tools and skills to improve your employability. The programme is mapped against Vitae’s Researcher Development Framework (RDF), you’ll benefit from Vitae’s career support as well as our own programme. We also have a team dedicated to improving the academic English needed for research by our international PGRs.

Our training is delivered in a variety of ways to take advantage of online platforms as well as face-to-face workshops and courses. You can access a range of bespoke training opportunities and in-person events that are tailored to each stage of your journey;

  • Sessions on PhD thesis writing, publications and journals, post-doctoral opportunities, poster and conference presentations, networking, and international travel opportunities.

  • Opportunity to work and study abroad via the Turing Scheme through The Graduate School.

  • Externally accredited training programme with Advance HE (HEA) and CMI.

  • Online research training support accessed through a dedicated researcher module in Brightspace, the University’s Virtual Learning Environment.

  • We also hold a series of PGR focussed events such as 3 Minute Thesis, PGR led research conference and informal events throughout the year.

**THE Impact Rankings 2022

*** REF2021

Important information

We will always try to deliver your course as described on this web page. However, sometimes we may have to make changes as set out below.

When you are offered a place on a research degree, your offer will include confirmation of your supervisory team, and the topic you will be researching.

Whilst the University will use reasonable efforts to ensure your supervisory team remains the same, sometimes it may be necessary to make changes to your team for reasons outside the University’s control, for example if your supervisor leaves the University, or suffers from long term illness. Where this is the case, we will discuss these difficulties with you and seek to either put in place a new supervisory team, or help you to transfer to another research facility, in accordance with our Student Protection Plan.

Changes may also be necessary because of circumstances outside our reasonable control, for example the University being unable to access its buildings due to fire, flood or pandemic, or the University no longer being able to provide specialist equipment. Where this is the case, we will discuss these issues with you and agree any necessary changes.

Your research project is likely to evolve as you work on it and these minor changes are a natural and expected part of your study. However, we may need to make more significant changes to your topic of research during the course of your studies, either because your area of interest has changed, or because for reasons outside the University’s control we can no longer support your research. If this is the case, we will discuss any changes in topic with you and agree these in writing. If you are an international student, changing topics may affect your visa or ATAS clearance and if this is the case we will discuss this with you before any changes are agreed.

When you enrol as a student of the University, your study and time with us will be governed by the University’s Terms and Conditions and a framework of regulations, policies and procedures, which form the basis of your agreement with us. It is important that you familiarise yourself with these as you will be asked to agree to abide by them when you join us as a student. You will find a guide to the key terms here, along with the Student Protection Plan, where you will also find links to the full text of each of the regulations, policies and procedures referred to.

The Office for Students (OfS) is the principal regulator for the University.