Cranfield University, England invites online Application for number of Fully Funded PhD Degree at various Departments. We are providing a list of Fully Funded PhD Programs available at Cranfield University, England.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title:
Ultra-low NOx Hydrogen- Fuelled Gas Turbine Combustion Systems PhD
The objective of this project is to investigate the design, performance and emissions characteristics of a novel hydrogen-fuelled, ultra-low NOx combustion system over an entire range of operating conditions. The analysis will be undertaken using multi-fidelity tools ranging from reduced order models to high-fidelity computational fluid dynamics (CFD). Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power Engineering, Cranfield University, in the area of gas turbine combustors.
Deadline : 10 Jan 2024
(02) PhD Degree – Fully Funded
PhD position summary/title: Novel Methods for the Characterisation of Helicopter Aero-acoustics PhD
The proposed project aims to build a Reduced Order Model (ROM) capable of synthesising the noise hemispheres as functions of pertinent vehicle design parameters and operating conditions. A novel computational framework will be developed for helicopter noise hemisphere generation by integrating a series of validated Cranfield tools for rotor aero-mechanics and acoustics. A non-linear “free-wake” rotor model will be adapted to capture Blade Vortex Interaction (BVI) noise. This model will be extended to resolve the simultaneous evolution of the main and tail-rotor flow-fields, including the impact of the fuselage on the potential flow field. The acoustic model will be modified to be able to predict noise-hemispheres based on the combined free-wake flow solution of the main and tail rotor flows. This framework will be used to generate series of databases of noise hemispheres for a range of rotor architectures as functions of design parameters and operating conditions. Latin Hypercube Sampling (LHS) or Full Factorial (FF) sampling methods will be used for the Design of Experiments (DOE) to discretise the design space. State-of-the-art ROM approaches will be applied to analyse the noise data-bases, such as Proper Orthogonal Decomposition (POD) and dimensionality reduction (auto-encoders, non-linear Principal Component Analysis – PCA) to extract key aero-acoustic features. Surrogate modelling methods such as Gaussian Processes (Kriging) or Artificial Neural Networks (ANN), will be applied to derive analytical approximations of the scalar POD coefficients. The developed ROMs will be transferred to DSTL in the form of interpretable and generalizable aero-acoustic models using an agreed software format. This will be carried out through a series of dedicated student placements to facilitate the integration of the derived ROMs, as well as their application to a series of cases studies according to Dstl’s interest.
Deadline : 29 Nov 2023
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(03) PhD Degree – Fully Funded
PhD position summary/title: Fusion of advanced testing and machine learning methods in propulsion aerodynamics PhD
This PhD work will be sponsored by the Engineering and Physical Sciences Research Council – Doctoral Training Partnership (EPSRC – DTP) and LaVision in the UK. LaVision has proven expertise on measurement solutions, providing world class knowledge and delivering cutting-edge science and technology in non-intrusive methods for flow field characterisation with high resolution in space and time. It is expected that throughout this PhD opportunity, a new experimental capability will be developed to generate bespoke distortion patterns that could be encountered in complex aero-engine intakes. By deploying state-of-the-art AI and machine learning techniques, the experimental data will be further exploited to synthesise inlet flow patterns that can be used for industrial testing as part of engine development and certification programmes. This PhD opportunity includes a range of opportunities for the successful applicant to present the work in national and international conferences as well as to participate in training courses.
Deadline :29 Nov 2023
(04) PhD Degree – Fully Funded
PhD position summary/title: Extreme learning to handle ‘Big Data’ PhD
The integrating should enable to guarantee certain properties of the learned functions, while keep leveraging the strength of the data-driven modelling. Most of, if not all, the traditional statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big data demands new statistical thinking and methods. As data size increases, each feature and parameter also becomes highly correlated. Then, their relations get highly complicated too and hidden patterns of big data might not be possible to be captured by traditional modelling approaches. This implies that mathematical modelling of such data is infeasible. The data-driven modelling approach could resolve this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling using learning algorithms as Extreme Learning Machine (ELM) is that training data should cover the entire domain of process parameters to achieve accurate generalization of the trained model to new process configurations. In practice, this might not be possible, that is the sample data could cover only some space, not entire space, of process parameters. Integrating prior knowledge into the learning could enable accurate generalization of the data-driven model even when the space of system parameters is only sampled sparsely.
Deadline : Open until filled
(05) PhD Degree – Fully Funded
PhD position summary/title: Development of Advanced Coatings for Improved Environmental Performance PhD
This PhD project involves researching the bridging technologies on behalf of the industrial sponsor Siemens Energy Industrial Turbomachinery Limited, which is a manufacturer of industrial gas turbines (IGT). The successful research into those bridging technologies (which will include modelling and experimental work) will reduce greenhouse emissions by enabling operation of the IGTs at higher metal temperatures and with novel fuels. The proposed research therefore aims to develop coating technologies, which will provide component materials the ability to cope with higher operating temperatures, and may be further beneficial when hydrogen fuel, or other novel green fuels, become standard, as these fuels may induce higher operating temperatures. The proposed research will be co-funded by the prestigious EPSRC iCASE (Industrial Collaborative Awards in Science and Engineering) award and the industrial sponsor, providing a four-year tax free fully funded PhD studentship. The successful candidate will work within a multi-disciplinary team supported by academics and industrial supervisors. Upon completion of the research, the successful candidate will have developed understanding/expertise in the bridging technologies and environmental issues, in coating, which may ultimately lead to a future in either academia or industry.
Deadline : Open until filled
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(06) PhD Degree – Fully Funded
PhD position summary/title: Decarbonisation of Welding and Associated Processes in the fabrication of large steelwork structures – supported by BAE Systems iCASE award
This challenging and rewarding iCASE award will effectively investigate and report the energy consumption across different manufacturing processes in the Barrow site of BAE Systems. The project will span across Energy and Sustainability and Manufacturing themes of Cranfield University and would be rewarding as it will endeavour to establish the carbon emission measuring, reporting and prioritisation principles which has the potential to shape the future of manufacturing.
Deadline : 29 Nov 2023
(07) PhD Degree – Fully Funded
PhD position summary/title: Forest Resilience and Compound Events (FoRCE) in a changing climate PhD
This is an exciting PhD opportunity in collaboration with Forest Research, UK’s largest forestry and tree-related research agency, to assess the impact of compound climate and weather events on forests using remote sensing data, climate models, field surveys, data science and machine learning approaches. The project outputs will contribute to the development of new management strategies to mitigate forest damage and promote resilience in a changing climate. It is a fully funded NERC – CENTA PhD Studentship for 3.5 years. Successful home-fees-eligible candidates will receive an annual stipend, stipend, set at £18,622, plus full university fees and a research training support grant.
Deadline : 10 Jan 2024
(08) PhD Degree – Fully Funded
PhD position summary/title: Intelligent sorting for urban mining to upcycle post-consumer scrap (I-Case) PhD
Applications are invited for a fully funded PhD studentship in the area of sustainable manufacturing and materials and more specifically in intelligent sorting to upcycle post-consumer metal scrap, within the Sustainable Manufactruring Systems Centre and in collaboration with Constellium (a global manufacturer of aluminium rolled products, extruded products, and structural parts based on a large variety of advanced alloys).
Deadline : 06 Dec 2023
(09) PhD Degree – Fully Funded
PhD position summary/title: Ultra-low NOx Hydrogen-Fuelled Gas Turbine Combustion Systems PhD
Current gas turbine engines use hydrocarbon fuels, such as kerosene, diesel and natural gas which inevitably produce CO2 and NOx emissions. To reduce their environmental impact, gas turbine engines may move from burning traditional hydrocarbon-based fuels to hydrogen fuel. This will eliminate exhaust CO2 emissions. However, gas turbine designers are facing technological challenges in designing low NOx hydrogen-fuelled combustion systems without compromising other performance and operability requirements such as combustion efficiency, pressure loss, durability, stability, resistance to flashback and more.
Deadline : 10 Jan 2024
About Cranfield University, England – Official Website
Cranfield University is a British postgraduate-only public research university specialising in science, engineering, design, technology and management. Cranfield was founded as the College of Aeronautics (CoA) in 1946. Through the 1950s and 1960s, the development of aircraft research led to growth and diversification into other areas such as manufacturing and management, and in 1967, to the founding of the Cranfield School of Management. In 1969, the College of Aeronautics was renamed the Cranfield Institute of Technology, was incorporated by royal charter, gained degree awarding powers, and became a university. In 1993, it adopted its current name.
Cranfield University has two campuses: the main campus is at Cranfield, Bedfordshire, and the second is at the Defence Academy of the United Kingdom at Shrivenham, southwest Oxfordshire. The main campus is unique in the United Kingdom (and Europe) for having its own airport – Cranfield Airport – and its own aircraft, used for teaching and research.
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