Engineering (PhD)

2021-22 (also available for 2022-23)

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

Start date

1 October 2021

17 January 2022

25 April 2022

Duration

The maximum duration for a full-time PhD is 3 years (36 months) or part-time is 6 years (72 months) 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 PGR start date September 2021

02 July 2021

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.

A PhD is a programme of research, culminating 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 (excluding ancillary data).

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.

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).

You will be appointed a main supervisor who will normally be part of a supervisory team, comprising 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, 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 will be considered acceptable. 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

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 Large Hadron Collider at CERN is the largest and most important project in particle physics in the world. It is currently being upgraded to increase its potential for discovering new physics. This upgrade will increase the amount of beam in the accelerator. To make this possible, the accelerator collimation system must also be upgraded. This is a vital part of the accelerator that removes particles that would otherwise be lost from it and possibly cause damage to it. This upgrade will be very challenging.

The PhD will investigate new forms of collimation that would help to make this upgrade possible. It will involve the development of a software tool called Merlin, including comparisons with measurements made at CERN, and its use for studying and optimising the new collimation techniques.

The work will be done as part of an UKRI-STFC and CERN funded project and will include collaboration with the University of Manchester and CERN.

Funding

This is a fully funded project with the cost of tuition fees and an annual bursary (£15,285 in 2020/21) funded through the Science & Technology Facilities Council.

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

The way in which temperature change affects the performance of machine tools remains an unanswered challenge. There are several instances at which machine thermal conditions inevitably change from its current state such as machining itself, environmental conditions, development of air pockets during machining, production- intermittent processes, etc. To enable Finite Element Analysis (FEA) software to match and precisely simulate these time-variant boundary conditions, an interface link must be created between the FEA software and sensing or monitoring devices to allow live feedback of data to adapt the computation.

This project aims to develop an interface link between the FEA software and external sensing devices using e.g. Python programming to enable the simulation of time-varying boundary conditions. To ensure the quality and usability of the captured data, optimisation, reduction and machine learning techniques will be developed and tested on different platforms, including high-performance computing (HPC) or graphics processing unit (GPU) accelerated computing.

The project would be suitable for a computer programmer with an interest in advanced engineering applications, or a mechanical/design engineer with good programming skills.

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 share of adults who own a smart speaker increased to around 20% in 2020. They allow users to listen to audio, create lists, schedule events, control lighting, control heating and interact with others. Echo smart speakers are able to synchronise across multiple zones of the house, allowing for a continuous and uninterrupted end user experience. This project aims to produce a generative music system which pre-empts user requirements (for example by playing music if a user typically listens when arriving home). Appropriate methods of interaction with the device(s) will be established (e.g. voice, motion detection, time of day etc). Methods of tracking will be established to allow the device to build a profile of typical usage throughout the day relating to time, location and music style preference. The user’s voice commands will modify the generative music parameters to change music according to tempo, style, intensity etc.

The project would require a series of smart devices, such as Echo Show devices, to be available across the smart home (as would be the case in every smart home). This would be the minimum specification with regards to hardware required for this project. If the smart home is to be constructed with another integrated voice recognition system then this could be utilised to develop the system. Depending on availability, the system could interact with smart home cameras, speakers, temperature sensors, motion tracking sensors, and smart devices such as fridges. Therefore this project has the flexibility and potential to interact with a large range of devices, depending on their availability. This also demonstrates the potential for future growth of the system.

This project will allow collaboration with many areas of expertise within the university such as music composition, sonic art and computing. The project will facilitate outputs in all 3 of these areas. Journals targeted will be Organised Sound, Proceedings of the International Computer Music Conference, IET proceedings and Computer Music Journal. The project will also draw upon expertise within my Sonic Art Forum which has over 6000 members online, therefore driving public engagement (which the university has recently prioritised as a key area to address through the public engagement survey).

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 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

Renewable energy is an essential source for harnessing natural forces such as wind energy in an age which is very conscious of the environmental effects of burning fossil fuels, and where sustainability is an ethical norm. Therefore, the focus is currently on both the adequacy of long-term energy supply, as well as the environmental implications of particular sources. In that regard, the near certainty of costs being imposed on carbon dioxide emissions in developed countries has profoundly changed the economic outlook of clean energy sources. Wind turbines have vastly been developed in recent decades due to technology becoming more advanced. Since there is a continuous exhaustion of fossil fuels, it is of high interest with government encouragement to utilise wind technology. Wind turbines are currently advancing into cross-flow vertical axis operation, whereby research has shown a significant increase in performance compared to existing technologies. The need for sustainable energy sources becomes greater each year due to the continued depletion of fossil fuels and the resulting energy crisis. Solutions to this problem are potentially in the form of wind turbines, for sustainable urban environment, that have been receiving increased support. At present, a number of wind turbines have been developed that show significant increase in performance compared to existing technologies.

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 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

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

Supervisors

How to apply

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

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

Supervisors

How to apply

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

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 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

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

Multi component and multiphase mixture flows take place through a number of industrial stems and contribute to a number of processes. Some practical examples of such flows are solid-liquid flow, solid-gas flow, solid-liquid-gas flow, oil - water flow etc. Some of the most common industries where these flows are encountered are Nuclear Industry, Mining Industry, and Chemical Industry etc. The operation, monitoring and control of these flows need detailed knowledge about the flow characteristics of individual components and individual phases. The problem becomes especially complex if the flows are taking place through complex geometries for example helical pipes, elbows valves etc. Through this project novel techniques will be developed to understand local flow features associated with individual components and phases and integrating this information to develop design tools/standards for these processes. The special computational/experimental techniques developed will enable quantification of interphase interaction mechanism. It is expected that the work carried out under this project will enable removal of empiricism embedded in design methodologies to a large extent. It will further allow development of methodologies to trouble free operation and energy use optimisation for such systems.

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

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

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

Previous work shows that application of an array of synthetic jet actuators, embedded within wing’s lading edges, leads to a significant alteration (reduction) to the buffet excitation levels on the suction side of swept wings arising from the vortex breakdown. While this effect has been extensively documented, little is known about the underlying fluid mechanical processes. It has been hypothesised that the coherent vorticity originating from the orifices of the synthetic jets becomes rolled up within the leading edge vortices and interacts with large scale coherent structures originating from the vortex burst, so that the vortex filaments become kinked and dissipate more quickly than in an un-actuated wing. The proposed project aims at unravelling the flow physics behind these processes by investigating the propagation of coherent structures in the post-breakdown region (in both actuated and un-actuated situation) using either the optical flow diagnostics tool such as flow visualisation, LDA and PIV and/or CFD codes such as Fluent. (Industrial relevance: aerospace)

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 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.

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 importance of big data and artificial intelligence is increasingly emphasized in future manufacturing. It offers a tremendous opportunity to transform today’s manufacturing paradigm to the data-driven intelligent manufacturing, which allow continuously development of cost-effective manufacturing technologies with improved product quality.

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 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.

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

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.

Funding

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

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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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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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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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The project involves conceptualizing, developing, and demonstrating a digital twin for a biological indoor environment within a building. Various aims and objectives for this project are outlined below.

Aim: To develop an IOT based digital twin system for monitoring the biological health of an indoor environment.

Objectives:

1) Identify key indoor environment parameters responsible for inhabitants’ health

2) Develop a sensing infrastructure for important parameters

3) Develop a mechanistic/numerical model for processes within the specific indoor environment

4) Develop a hybrid sensor/model-based (data assimilation) system having adequate spatial and temporal resolution

5) Develop a visualization and analytics module for online monitoring of the environment

6) Use the developed system for predicting biological characteristics of specific indoor environments and informing intervention mechanisms

Methodology: The above objectives can be achieved by carrying out a combination of experimental and numerical investigations using equipment available within the Smart House facility and computational and analytical expertise available within the School of Computing and Engineering and the School of Applied Sciences.

Rationale: One of the major causes of morbidity and mortality globally is indoor air pollution. The indoor environment affects the inhabitants significantly as about 90% of the inhabitants' time is spent indoors and a poor-quality biological environment may cause a variety of adverse health effects. The situation in this regard has become worse recently because the time spent indoors has increased significantly because of COVID-19.

The indoor environment gets continually affected by the significant interaction of inhabitants, activities, and products used. A large number of processes continuously take place over different length scales and timescales within the environment. Many of these processes are visible and many others are invisible. This makes identification of threshold characteristics over which the indoor environment becomes hazardous, very difficult. The exposure time to a wide variety of undesirable sources present in the environment, is also an important parameter that affects the health outcomes. For example, exposure to cleaning and disinfection products has been associated with respiratory disorders such as asthma in cleaning and healthcare workers. Various sources that contribute to the indoor environment include occupants’ exhalation (carbon dioxide; CO2), activities such as cooking and smoking, emissions from building materials, etc. from which various air pollutants, such as carbon monoxide (CO), particulate matter (PM), and volatile organic compounds (VOCs) may be present.

The other problem can be caused by the presence of several pathogen sources coming in occasional contact with a specific indoor environment. The pathogens can linger in the air for hours and deposit on surfaces under the normal ventilation conditions provided in hospitals, domestic, and industrial environments. Several factors affect pathogen dispersion and hence infection transmission. These include room temperature and humidity, air-conditioning, if the windows are open or closed, general air quality, room size, and several people and sources present and their proximity to each other.

This project aims to develop a hybrid model that integrates a sensor network with a computational model to predict in real-time the biological indicators for an inhabited space. Furthermore, an analytical framework will be developed to support intervention mechanisms to ensure a good quality environment. For this purpose, the smart house facility created within the School of Computing and Engineering at the University of Huddersfield will be extensively used.

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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This PhD project will work on the development of a virtual integrated manufacturing system for freeform surfaces based on our current freeform CAD/CAM framework. The virtual system will be developed with functional modules covering surface generation, toolpath planning, machining stability analysis and surface profile predication. The focus of the research is on the development of core data analysis modules for the surface characterisation of advanced freeform and micro/nano-structured surfaces. It will also include the integration of current operation methods and algorithms for decomposition, association, filtration, texture mapping and numerical parameterisation and characterisation into the metrology module of the system. The developed system will be evaluated against agreed partner-led case studies on creating complex and multiple freeform surfaces.

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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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Heating and cooling are responsible for 51% of final energy use in Europe and represents about 27% of CO2 emissions. Buildings and construction sector accounting for nearly 40% of energy-related CO2 emissions whilst also having a significant impact on our natural habitats. In the UK about 80% of heating energy consumed comes from fossil fuels (heating oil, gas or even coal). This is due to intermittent energy production from renewable resources. Furthermore, energy efficiency in residential buildings is an important factor in mitigating the challenges of climate change and environmental issues so it becomes important to make radical changes in existing structure of buildings. This project completely devoted to find out major loopholes in building energy use based on monitoring, controlling, simulating building loading and alteration in material components. The proposed project focuses on exploiting the renewable thermal technologies and its integration for the commercial, industrial and district heating sectors which will compliment UK’s net Zero Energy Building (nZEB) programme.

This project is aimed at developing computer simulation model for a prototype residential building in the UK with detailed parametric analysis and validation. It includes the development of sensor-based platform to assess the energy performance of the building which will also monitor all the activities within the building. The methodology includes building characterisation, simulation of energy performance, sensitivity analysis of different building components, indoor energy distribution and control mechanism for heating and cooling load. The research will be augmented by the experimental findings from the Huddersfield Smart House Research Facility (prototype house), the analysis of occupant thermal comfort and energy consumption pattern using Building Performance Simulation. This research also involves field work for occupant survey and their activities, experimental work for thermal comfort analysis and simulation study of passive techniques implementation. This is an interdisciplinary research which involves building physics, design and socio-technical evaluation of indoor environment quality management.

Methodology: The developed theoretical model will be validated by using experimental data acquired from a prototype building (Smart House) at the University of Huddersfield and the proposed project can be accomplished under following steps:

• Thermal comfort analysis with the help of survey of occupants or use the existing thermal comfort parameters.

• Designing and simulation of building on dynamic EnergyPlus software, sensitivity analysis of building parameters and evaluate the thermal load profile of the building.

• Regression analysis of all activities (occupants or machine) inside the building with the help of building parameters and make a detailed report of building energy consumption and identifying major affecting parameters.

• Development of measurement platform by equipping high accuracy sensors at different locations.

• Validation of simulation results by using data from the Huddersfield Smart House Research Facility.

• Implementation of passive technologies (most probably retrofit) in the building simulation.

• Implementation of these passive techniques in building and collect the result with the help of measuring platform.

• Compare the results with the base case and make a concluding report.

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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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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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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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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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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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 further develop and apply the mesoscopic approach FEA simulation of creep damage at grain boundary level.

The prototype of the software has been nearly developed, but its applications have not been seriously perused. This project aims to produce parametric study to yield the insight knowledge of the local interaction and the grain boundary creep cavitation and damage. The result will provide a more accurate understanding of the cavitation damage at grain boundary level. * https://pure.hud.ac.uk/en/publications/development-of-the-fe-in-house-procedure-for-creep-damage-simulat

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X-ray computed tomography (XCT) is becoming a capable non-destructive testing and metrology tool for industrial applications. In comparison to conventional tactile and optical measurement techniques, XCT has no line-of-sight constraint and can measure the full spectrum of geometrical features, e.g. dimension, surface roughness and porosity. However, in contrast, XCT is a more expensive metrology tool and usually takes longer time for part scanning and data processing, e.g. surface determination (identification of the material boundary of the scanned part), which limits its usefulness for industrial applications. This research project aims to develop a fast surface determination method based on machine learning (ML) technology. To facilitate the construction of a large database for ML training, a simulation approach will be employed, where the scanning of the designed virtual samples will be simulated by XCT simulation software. An efficient ML model for surface determination will be developed and trained to enable fast and accurate surface determination. The ML based surface determination method will be verified through comparing with conventional approaches. The project will be based on the Future Metrology Hub, Centre for Precision Technologies, and in collaboration with Dr Amin Garbout (external supervisor, the Henry Moseley X-ray Imaging Facility, the University of Manchester). The candidate is expected to have the experience of programming and machine learning. The selected student will be provided with the training of XCT machine and XCT simulation software.

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Fear learning has been a strong source of inspiration for developing flexible and adaptive artificial intelligence in electronic systems. The project aims at developing a robot movement following an unexpected event that induces fear. The work will study spiking neural networks based controller for driving the robot, establishing a variety of tasks, and its intelligent modifications to adapt to a fearful situation. The robot models need to be designed in an FPGA (Field Programmable Array devices) using a standard HDL (hardware description language). The robotic platforms preferably would a raspberry-pi based, which interacts with the FPGA over a WIFi connection.

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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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Additive manufacturing technology, also called 3D printing, enables the construction of customised structures not possible with traditional fabrication methods. 3D printing for medical applications is expanding rapidly and is expected to revolutionize healthcare. For instance, nowadays many personalised healthcare products, e.g. joint implants, dental implants, personalised pharmaceutical drugs, are made by 3D printing. However, a barrier that impedes the increased uptake of 3D printed products to be used as more critical parts is their quality control and verification. Particularly, metrology is essential to ensure that products have correct geometries in all scales to achieve the desired function. Traditional tactile and optical metrology techniques are of limited use due to the light-of-sight restriction. This project will investigate how to use XCT to measure healthcare products, and to develop a set of characterisation methods to evaluate their dimensional accuracy, surface roughness and structural compliance.

(1) Dimensional accuracy The dimensions of customised healthcare products are patient-specific, which allows products to be personalised to match each patient’s individual needs. The measurement and assessment of dimensions of healthcare products are challenging, particularly for products with freeform shapes and lattice/porous structures. Effective approaches to evaluate dimensional geometry of healthcare products with complex shapes will be investigated.

(2) Surface roughness Surface roughness is playing a critical role in boosting functional performance of healthcare products, e.g. osseointegration of joint implants. As-built 3D printed surface is usually rough and often presents various surface topography depending on building orientation, layer thick as well as other relevant process parameters. Assessment of surface roughness in region of interest and the global uniformity using XCT will be investigated.

(3) Structural compliance For healthcare products with lattice and porous structures (e.g. porous scaffold in bone implant and porous lattice for drug release), structural compliance is directly relevant to product’s functioning. The connectivity of lattice cells, porosity rate, pore size distribution, surface areas and structure volume directly influence component’s function, e.g. stiffness, permeability. The evaluation of these measurands using XCT and their relation to functional performance will be investigated.

(4) Case studies A key case study will be to use XCT to quantitatively analyse the internal microstructure of AM lattice structure intended for drug delivery applications. This is via a UoH internal collaboration project with the School of Applied Science.

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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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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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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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Advances in medical science have helped people live longer and many old people select to live independently. This brings us a challenge as to how to monitor their physical condition and take care of their well-being. Generally speaking, there are two ways which can be used to address the problem. One is to use wearable sensors which can detect a person’s heart rate, blood pressure, blood sugar, oxygen saturation etc. However, the biggest disadvantage for this kind of technology is its intrusive and the requirement needed for professional management. Another common approach is non-wearable sensors like passive infrared sensors, cameras, acoustic and vibration sensors, etc. The main advantage of this technology is that it’s far less intrusive and easier to implemented. This research proposal is to develop and prototype a non-wearable in-bed smart sensor which includes acoustic and vibration measurement with the latest signal processing techniques and artificial intelligence algorithms such as supervised learning and unsupervised deep learning together to implement adaptive and continuous monitoring of sleeping. The proposed research will concentrate on the following two areas:

• Develop and prototype an in-bed smart sensor system based on microphones, accelerometers and cameras. Such a system should have novel cost-effective hardware and software architecture and use latest disruptive IC sensors, microprocessors and embedded algorithms with artificial intelligence capability such as k-means, support vector machine, linear regression, classification tree, and deep learning neural network in order to monitor elderly people’s physical conditions and provide a possible early warning for any abnormal phenomena whilst they sleep.

• Investigate proper novel signal processing techniques and algorithms which are capable of separating the wanted signal and the background noises. For example, one of the useful signals from sleeping monitoring is to analyse the ballistocardiograph (BCG). But this signal could be easily contaminated by background noise. It is necessary to develop some novel signal processing techniques for feature extraction such as time, frequency or time-frequency domain features for BCG identification and classification plus automated adaptive smart sensor calibrations.

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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Pulsed laser deposition (PLD) is a physical vapour deposition technique used to deposit thin films (<100nm) of material. PLD has been expanding rapidly since the early 1990s owing to the relatively simple conceptual set-up, the high deposition rate and the ability to deposit materials with complex stoichiometry. In PLD, a pulsed laser is used to remove (ablate) material from a target which produces a plume of plasma that flows from the target surface. This plume of material is then deposited on a substrate a short distance away where it forms a thin film. These thin films are subsequently used in a range of applications including compound semiconductors, dielectrics, ferroelectrics, electro-optic oxides, high-temperature superconductors and heterostructure (layered crystalline) materials.

The overall aim of this project is to develop a novel method of pulsed laser deposition, X-PLD (eXtreme ultraviolet Pulsed Laser Deposition), and to demonstrate the capability of this new technology by improving the efficiency of the transparent conducting oxide (TCO) layer in solar cells. The proposed technique exploits a capillary discharge laser system operating in the extreme ultraviolet (XUV). The effectiveness of this technique will be demonstrated by depositing metal oxide thin films used as TCOs in solar cells and comparing these thin films with those generated using existing technology. The medium energy ion scattering (MEIS) facility, unique in the UK and situated at the University of Huddersfield, will be used as the primary analytical tool for this project.

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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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Project description: Various human health effects, aesthetic, and structural damage to buildings have been attributed to mould in indoor domestic and commercial environments. It can be caused by high relative humidity in ambient air which condenses into water droplets to form damp. These can deposit on surfaces under poor ventilation conditions, and in some cases under good ventilation but depending on the prevailing climatic conditions such as rain and season. Augmented reality tools have become attractive in providing immersive three-dimensional experience of real-world environments and can be used to visualise damp and mouldy hotspots in buildings. They are extremely popular in the video game industry as they superimpose or “augment” visual and other sensory input on the real world and puts it into the viewer’s eyesight as fast as possible. This has significant potential to aid the fight against dangerous respiratory infections that can occur from mouldy indoor spaces. This project aims to use computational fluid dynamics CFD results (which show predicted path lines and concentration of water droplets in the air and its subsequent deposition hotspots) to simulate and predict droplet transport in the Smart House. The results will then be integrated with commercially available augmented reality mobile devices to visualise droplet and damp hotspots in real-time.

CFD can produce very accurate predictions of droplet transport within complex indoor and outdoor spaces. Using AR to visualise the results of humidity/droplet hotspots can speed up detection and subsequent intervention as well as feed into the planning of homes and workplaces to minimise damp/mould occurrence and adverse health effects that can result.

Project objectives

• High-fidelity CFD simulations of droplet transport using the Large Eddy Simulations (LES) to predict airflow, droplet path lines and concentration in a model of the Smart House. The CFD will be validated with measurements collected using wireless humidity and temperature sensors installed with sufficient spatial resolution in the building.

• Development reduced-order model (ROM) from CFD results using a suitable machine learning technique for use with an AR device.

• Development of an augmented reality application for visualising droplet/damp hotspots as an overlay on the real environment with AR-enabled mobile devices – phones, tables, and commercial AR headsets (such as Microsoft HoloLens and HMT-1) by visualising the results.

Required technical and soft skills

• Proficiency in the use of commercial CFD simulation software e.g., Ansys. The ability to use open-source CFD will be an advantage.

• Ability to effectively analyse both CFD and experimental data by scripting with MATLAB or Python.

• Proficiency in producing applications for mobile devices with Python or Java languages is an advantage.

• Good experimental skills including ability to setup and work with wired and wireless sensors and data acquisition systems.

• Good technical report writing skills.

• Excellent communication and interpersonal skills.

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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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.

This PhD will focus on the development of a set of highly compact probes exploiting nanophotonic elements (nanostructured patterns that allow the precise control of light) to be used as the front end of a measurement instrument. This will not only allow measurements to be taken in areas that were previously inaccessible, but the additional control provided by the nanophotonic elements will mean that the illumination and collection of the light can tailored to specific types of task, and properties such as chromatic aberration be used to an advantage.

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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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Manufactured parts with complex structured surfaces have been widely used in automobile, bio-engineering, medical and consumer electronics etc. Compared with traditional ‘stochastic surface’, the complex structured surfaces have two significant characteristics: one is that they have complex base surface (reference surface/mean surface) which has complex shape, the other is that they have deterministic features with high aspect ratio on the base surface. The ability to adequately characterise these complex structured surface geometry features is crucial in the optimisation and control of such functional device/components. This proposed PhD project aims to develop an intelligent filtration framework for the complex freeform structured surface. It will be It will be achieved through fulfilling the following three objectives: • Develop a mathematical model for the intelligent adaptive filtration techniques, for example, the nonlinear diffusion filter; • Develop a smart unsupervised machining learning technique to segment and classify the features by using techniques such as active contour, level set. • Implement these practical algorithms in an efficient way, for example, use parallel computing through CUDA, open-source library.

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Cyber-Physical Systems (CPSs) and the Internet of Things (IoT) are enhancing traditional critical infrastructures with data-rich operations. Modern railways are a prime example of such CPS. This augmentation of connectivity and data-intense operations creates complex interdependencies in modern railway networks that expose their components to new threats. One of the objectives of the work is to design an IoT enabled intelligent system to generate the list of testing requirements for smart railways, potentially incorporating formal verifications. The second objective of the work is to design infrastructure to detect and prevent potential cyber-attacks using software and hardware security primitives.

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The project looks at using inverse problem approach to develop complex flow handling systems such as pipings, valves, radiators, heat exchanges for better effieciency, operation and reliability. These fluid handling systems may be handling single or multiphase flow systems. State of the art numerical, analytical and experimental techniques will be used for such purposes.

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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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Material at high temperature suffers creep damage resulting in the failure of its structural integrity. For most engineering alloys, the primary cause for such failure is the cavitation at grain boundary, but the current research and knowledge is primarily empirical and phenomenological lack of the scientific support. 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 aims to provide the better understanding of the cavitation and rupture processes by multiscale approach and correlating to other material research. It is anticipated to produce international excellence/leading quality output. 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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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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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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Hydroelectric power has played an important part in the development of Nigeria's electric power industry. Hydroelectric power comes from flowing water. Water, when it is falling by the force of gravity, can be used to turn turbines and generators that produce electricity. The growing populations and modern technologies require vast amounts of electricity for creating, building, and expanding Although the amount of energy produced by hydro has increased steadily, the amount produced by other types of power plants has increased at a faster rate and hydroelectric power presently plays a big role in the generation of power in Nigeria. Nigeria, with its emerging industries, is facing a daunting task to cope with the power crisis. There is a lack of sufficient power generation capacity, and the existing national grid network is unable to power the whole nation. The rural and remote areas have a low-load demand but the electricity supply has been characterized by high transmission and distribution costs, transmission. Micro-Hydroelectric Power, called as a Micro-Hydro, usually does not supply electricity to the national grid. They are used in remote areas where the grid dose not extends. Typically they provide power to small rural communities. They range in size from a few kilowatts, just enough to provide domestic lighting to a group of houses, to 200kW, which can be used for small factories and to supply an independent local ‘mini-grid’ which is not part of the national grid. Often Micro-Hydro provides an economic alternative to the grid. This is because independent Micro-Hydro Schemes save on the cost of grid transmission lines, and because grid extension schemes often have very expensive equipment and staff costs. In contract, Micro-Hydro Schemes can be designed and built by local staff and smaller organizations following less strict regulations and using the local technology such as for traditional irrigation works or locally made machinery. A hydro scheme requires both water flow and a drop in height (referred to as a ‘Head’) to produce useful power. It is a power conversion system, absorbing power in the form of head and flow, and delivering power in the form of electricity or mechanical shaft power.

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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 bring 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. Current XCT data processing, however, are insufficient to capture these internal defects in terms of both 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 convolutional neural network (CNN) 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 selected student will be provided with the training of 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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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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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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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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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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The liquid desiccant dehumidification systems have been widely adopted both in the industrial and residential sector to absorb the moisture content using an absorbent solution and to control the indoor air humidity, respectively. The dehumidifier is one of the essential parts of these systems, which severely affects the whole system performance and size. In addition to higher consumption of energy, the size of the dehumidifier is usually bigger in order to provide higher surface area for contact between the liquid desiccant and the process air. Moreover, in the conventional desiccant-based dehumidification systems, the liquid desiccant is in direct contact with the process air. This can lead to the contamination of the process air by the liquid desiccant droplets crossover and therefore small liquid desiccant droplets may be carried over by the process air to indoor environment, which could be rather harmful to occupants. Recent studies have shown that the use of membrane contactors can allow the development of innovative dehumidifier for non-contacting air dehumidification. In addition, the larger surface area provided by the membrane contactors can allow the development of compact dehumidifier with enhanced performance. This study aims to perform modelling and simulation of a membrane based liquid desiccant dehumidification system in order to analyse the absorption performance of the membrane-based dehumidifier.

This work aims to analyse in detail the absorption process of a membrane based liquid desiccant dehumidification system by developing a CFD model and a numerical model based on global mass and energy equations for global analysis. The following objectives will be targeted in this work.

• Developing a steady-state 1-D global model in MATLAB to acquire the basic understanding of the absorption process in a membrane based liquid desiccant dehumidification system and to investigate the effect of different operating and design parameters on the absorption performance.

• Implementation of the global model based on mass and energy balance equations in the thermodynamic simulation of a membrane based liquid desiccant dehumidification system to evaluate the performance of the complete system and compare the performance with that of the commercial unit operating with conventional dehumidifier.

• Developing a numerical model of the membrane-based dehumidifier using CFD approach for detail heat and mass transfer analysis. The optimized design parameters and operating conditions obtained from the global model and system simulation will be used as input conditions in the detailed modelling.

• Performing numerical simulations to investigate the absorption performance of a membrane based liquid desiccant dehumidification system using potential novel working fluid mixtures.

The first objective of this research proposal is to acquire the basic understanding of the membrane based liquid desiccant dehumidification system and to obtain optimized input condition for the detail modelling. To achieve this, a steady-state 1-D global model will be used to investigate the effect of different operating and design parameters on the absorption performance. Further, ASPEN Plus process simulation tool will be used to perform steady-state thermodynamic analysis of a liquid desiccant dehumidification system employing membrane-based dehumidifier. The input variables for the thermodynamic simulation will be adopted similar to that of a commercial liquid desiccant dehumidification system. The effect of process air quality (humidity level) on the dehumidifier size will be studied and the design parameters will be optimized to achieve a compact dehumidifier.

Moreover, a CFD based solver will be used to carry out detailed heat and mass transfer analyses. The optimized design parameters and operating conditions obtained from the global model and system simulation will be used as input conditions in CFD simulations. CFD analysis can provide a sound foundation to investigate in detail the fluid dynamics behaviour and the heat and mass transfer processes at local levels to better understand the phenomenon and the effect of flow parameters. Potential working fluid mixtures will be investigated, and numerical analysis will be carried out to compare and evaluate the performance of the system with these working fluid mixtures.

The simulation results will be validated with the experimental data. For this purpose, a lab-scale setup will be built. In case of exceptional circumstances, validation of the numerical model can be performed using the available literature data.

This work will provide a sound foundation to investigate in detail the performance of a membrane based liquid desiccant dehumidification system. Furthermore, this study will recommend optimum operating and design parameters for new working fluids. Expected results of this study can help in designing a compact and an efficient membrane based liquid desiccant dehumidifier for dehumidification systems that can maintain the air quality in commercial buildings, hospitals, and commercial aeroplanes etc.

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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The project will adopt a multi-dimensional approach whereby high integration of Renewable Energy Sources (RES) technologies into a residential buildings can be achieved in a user-friendly and cost-effective way. It draws together a range of transnational expertise paving the way towards sustainable building policies and refurbishment of existing buildings into near-zero-energy buildings. The project will collect the real data from the Smart House, investigating its capability to fully function while it is isolated from the grid. In this context, a holistic control will be developed to enable this operation strategy without causing any interruptions to the supply. The vision of the project is a future generation of sustainable buildings with above 80% RES penetration supported by energy storage systems, innovative nano-grids and optimised efficiency, to optimise self-generation without compromising the comfort and service of users, i.e. occupants and operators. The advancement of nano-grids responsible for the electrification of such buildings, will make the buildings’ power supply more resilient and flexible to participate in energy markets through IT secured systems and interactive schemes, which will improve the economic profiles of these electrified and near-zero-energy buildings.

The project is designed to overcome existing barriers by introducing new methods and tools that allow optimal integration and operation of RES with other technologies, answering some challenges stated on SETPLAN and Energy efficient Buildings Roadmap, e.g. energy efficiency, RES integration, resilience and security, interactive buildings, etc.

The project will benefit from the implementation of the benchmark Hardware-In the-Loop testing facility that should virtually interconnect the Smart House facility, some of the in-house rooftop Panels and grid variations through an OPAL-RT multi I/O module.

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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This exciting project is for clean energy passionate candidates, as it will develop design and control methods for microgrid (neighborhoods) and Nano-girds (fully electrified large buildings). The project will consider the integration of 100% green generation mix supported by different energy storage technologies. The project will consider the feasibility of both the technical and economic dimensions of these energy systems. The candidate is expected to publish the developed solutions and the obtained results in top tier journals and conferences.

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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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Digitalisation of manufacturing machinery is essential for future development in condition monitoring, advanced prognostics and performance improvements. The growth in the number and complexity of sensors being installed by OEMs on Machine Tools and the growth in IoT systems from providers like Siemens means that more and more data will be captured. Typically, standard temperature sensors or accelerometers are used to monitor the machine, but these provide limited capability for advanced capabilities such as error compensation for finite stiffness effects in the machine structure due to, for example, thermal and mass variation effects.

In this research a newly developed sensor, which uses phase resolved interferometry to measure the elongation of an optical fibre, will be used to measure the structural distortion of mechanical systems such as the main elements of advanced machinery. This could include CNC machine tools, precision artefacts and coordinate measuring systems. Since the system will be embedded onto the machine, possibly for its lifetime, there will be no possibility of performing calibration to ensure the readings continue to be accurate. This is essential if the data is to be used for calculating structural distortion so that the resulting errors can be compensated to improve the accuracy of the machine or measuring system. A detailed uncertainty evaluation of the measuring system will be performed, with areas of uncertainty identified and then solutions for tracking or compensating these uncertainties created. Concepts such as reversal techniques, material constants, controlled self-excitation and differential systems will be explored, simulated and then the novel solution implemented into the prototype measurement system which will then be used for monitoring and improving the performance of precision machinery.

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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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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 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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Additive manufacturing (AM) is paving its way toward the next industrial revolution. However many technical barriers still hinder its full commercialisation today. One major issue is that AM processes are not robust enough and AM needs measurement methods to control its process. This project aims to develop a set of advanced surface topography analysis techniques for the characterisation of additively manufactured (AM) products. Through characterising AM surface topography, the project will contribute to the optimisation of AM process variables, facilitate the functional evaluation of complex AM components and benefit the accurate geometrical measurement of AM products. The proposed research work include: (1) development of numerical analysis methods, including filtration and segmentation, to extract AM process signature features; (2) investigation of the relevance of area surface texture parameters to AM processes; (3) proposal of new parameters to reflect the unique characteristics of AM surfaces; (4) comparison of various surface metrology techniques for AM surfaces, including tactile, optical and x-ray computed tomography; (5) investigation of the influence of AM roughness texture on dimensional measurement; (6) investigation of the impact of AM process variables on produced surface topography; (7) prediction of AM surface topography in terms of AM process variables.

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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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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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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.

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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.

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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

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 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

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 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

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 studentship concerns research in advanced robotic manufacture of ultra-precision surfaces in glassy materials, required for numerous applications in science, medicine and industry. Fine surface processing involves “rubbing” rather than cutting, is of limited predictability, and still poorly understood. The studentship is associated with a major new EPSRC-funded project to deepen that understanding, by exploring challenging multi-physics, multi-scale science at the interface between computational fluid dynamics and molecular dynamics. This will be informed by controlled experiments with extensive process-monitoring, with modelling reinforced by machine-learning. The end-game is to use real-time process-monitoring to keep processes ‘on track’, reducing manufacturing cost, time and defect-rate.

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 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

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

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:

[*] [Institute of Railway Research|http://www.hud.ac.uk/research/researchcentres/irr/]

[*] [Turbocharger Research Institute|http://www.hud.ac.uk/tri/]

[*] [Centre for Innovative Manufacturing in Advanced Metrology|http://www.hud.ac.uk/research/researchcentres/cimam/]

[*] [Institute for Accelerator Applications|http://www.hud.ac.uk/research/researchcentres/iiaa/]

[*] [Centre for Efficiency and Performance Engineering|http://www.hud.ac.uk/research/researchcentres/cepe/]

[*] [Centre for Precision Technologies|http://www.hud.ac.uk/research/researchcentres/cpt/]

[*] [Adaptive Music Technologies Research Group|http://www.hud.ac.uk/research/researchcentres/amtrg/]

[*] [Energy, Emissions and the Environment Group|http://www.hud.ac.uk/research/researchcentres/eeerg/]

[*] [Condition Monitoring and Diagnosis Group|http://www.hud.ac.uk/research/researchcentres/cmdg/]

[*] [Measurement and Data Analysis Group|http://www.hud.ac.uk/research/researchcentres/mdag/]

[*] [Electron Microscopy and Materials Analysis Group|http://www.hud.ac.uk/research/researchcentres/emma/]

[*] [Automotive and Marine Engineering Research Group|http://www.hud.ac.uk/research/researchcentres/ameg/]

[*] [Music Technology and Production Research Group|http://www.hud.ac.uk/research/researchcentres/mtprg/]

[*] [Systems Engineering Research Group|http://www.hud.ac.uk/research/researchcentres/serg/]

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

The University of Huddersfield has a thriving research community made up of over 1,350 postgraduate research students. We have students studying on a part-time and full-time basis from all over the world with around 43% from overseas and 57% from the UK.

Research plays an important role in informing all our teaching and learning activities. Through undertaking research our staff remain up-to-date with the latest developments in their field, which means you develop knowledge and skills which are current and relevant to your specialist area.

Find out more about our research staff and centres here

Important information

We will always try to deliver your course as described on this web page. However, sometimes we may have to make changes to aspects of a course or how it is delivered. We only make these changes if they are for reasons outside of our control, or where they are for our students' benefit. We will let you know about any such changes as soon as possible. Our regulations set out our procedure which we will follow when we need to make any such changes.

When you enrol as a student of the University, your study and time with us will be governed by a framework of regulations, policies and procedures, which form the basis of your agreement with us. These include regulations regarding the assessment of your course, academic integrity, your conduct (including attendance) and disciplinary procedure, fees and finance and compliance with visa requirements (where relevant). 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.