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University of Bath URSA project: Physics-based and data-driven approach to understanding and predicting thermomechanical properties of ceramic matrix composites

   Department of Mechanical Engineering

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  Dr Yang Chen, Prof Chris Bowen, Dr Andrew Rhead, Dr Alex Leide  No more applications being accepted  Competition Funded PhD Project (European/UK Students Only)

About the Project

This project is one of a number that are in competition for funding from the University of Bath URSA competition.


This project aims to investigate the inelastic behaviour of ceramic matrix composites for nuclear applications. It will receive in-kind contributions from UK Atomic Energy Authority (UKAEA).

Modern energy and transportation industries, characterised by their new priority in sustainability, have a pressing requirement on identifying and using innovative materials with outstanding thermomechanical properties. In this context, ceramic matrix composites (CMCs) are strategically important, due to their unique capability in high temperature resistance and weight saving which will improve the efficiency of power stations and engines. Optimised design and service life assessment of CMCs are vital for more sustainable nuclear power plants with improved safety margins.

Utilising CMCs requires more detailed understanding of the inelastic behaviour of materials from microscale to the component scale. Conventional investigation techniques, relying on macroscopic and surface characterisations, cannot provide sufficient knowledge of the 3D structure of CMCs for the faithful prediction of structural integrity, and may lead to significant deviations. Data-driven computational mechanics in combination with multiscale material testing is an emerging research field and can bring a new paradigm for structural integrity assessment of composite materials.

Built upon the strength of department of Mechanical Engineering in high-performance composite materials, this PhD project will explore three interconnected techniques: data-rich experiments [1,2] (X-ray computed tomography and full-field measurement), high-fidelity simulations [3,4] (micromechanics-based damage modelling, image-based simulation, high-performance computing) and physics informed machine learning [5] (e.g. convolutional neural network, uncertainty quantification). For in-service lifecycle prediction, environmental effects, such as neutron irradiation and temperature gradient, will be taken into account.

Beside the already existing data, the PhD candidate will generate more dedicated data from in-situ experiments. She/He will also further develop an in-house code to predict the thermo-mechanical responses of CMCs under in-service conditions. The candidate will then use the experimental and simulation data to build machine learning techniques, which will in turn enhance the capacities of data processing and numerical simulation.

Candidate Requirements

Applicants should hold, or expect to receive, a First Class or good Upper Second Class Honours degree (or the equivalent) in Engineering or a related discipline, such as Mechanical Engineering, Applied Mathematics, Computer Science, Materials Sciences or Physics. A master’s level qualification would also be advantageous.

Non-UK applicants must meet our English language entry requirement by February 2023 in order to be considered.

Experience in numerical modelling and computer programming will be advantageous, but this is not compulsory.

Enquiries and Applications

Informal enquiries are encouraged! Direct these to Dr Yang Chen - [Email Address Removed]

Please make a formal application should via the University of Bath’s online application form for a PhD in Mechanical Engineering

When completing the form, please identify your application as being for the URSA studentship competition in Section 3 Finance (question 2) and quote the project title and lead supervisor’s name in the ‘Your research interests’ section. 

More information about applying for a PhD at Bath may be found on our website.

Funding Eligibility

To be eligible for funding, you must qualify as a Home student. The eligibility criteria for Home fee status are detailed and too complex to be summarised here in full; however, as a general guide, the following applicants will normally qualify subject to meeting residency requirements:

  • UK nationals (living in the UK or EEA/Switzerland)
  • Irish nationals (living in the UK or EEA/Switzerland)
  • Those with Indefinite Leave to Remain
  • EU nationals with pre-settled or settled status in the UK under the EU Settlement Scheme.

This is not intended to be an exhaustive list. Additional information may be found on our fee status guidance webpage, on the GOV.UK website and on the UKCISA website.

Equality, Diversity and Inclusion

We value a diverse research environment and strive to be an inclusive university, where difference is celebrated and respected. We encourage applications from under-represented groups. In particular, we are welcoming applications from candidates with Refugee, Asylum Seeker, or Humanitarian Protection in the UK to our Doctoral Sanctuary Studentship in Engineering and Design.

If you have circumstances that you feel we should be aware of that have affected your educational attainment, then please feel free to tell us about it in your application form. The best way to do this is a short paragraph at the end of your personal statement.

The Disability Service ensures that individuals with disabilities are provided the support that they need. If you state if your application that you have a disability, the Disability Service will contact you as part of this process to discuss your needs.

Keywords: Applied Mathematics; Ceramics; Computational Physics; Data Analysis; Machine Learning; Mathematical Modelling; Mechanical Engineering; Mechanics; Nuclear Physics; Solid Mechanics

Funding Notes

Candidates may be considered for a University of Bath (URSA) studentship tenable for 3.5 years. Funding covers tuition fees at the ‘Home’ rate, a stipend (£17,668 p/a in 2022/23) and a £1000/annum training budget.
As URSA studentships only cover the ‘Home’ tuition fee rate, Overseas students are not eligible to apply. Are you an Outstanding Overseas student (e.g. with a UK Masters Distinction or international equivalent) who is interested in this project? If so, please contact the intended supervisor in the first instance, to discuss the possibility of applying for additional funding.


[1]. Chen, Y., Shi, Y., Chateau, C., & Marrow, J. (2021). In situ X-ray tomography characterisation of 3D deformation of C/C-SiC composites loaded under tension. Composites Part A: Applied Science and Manufacturing, 145, 106390.
[2]. Chen, Y., Gélébart, L., Chateau, C., Bornert, M., King, A., Sauder, C., & Aimedieu, P. (2020). Crack initiation and propagation in braided SiC/SiC composite tubes: Effect of braiding angle. Journal of the European Ceramic Society, 40(13), 4403-4418.
[3]. Chen, Y., Gélébart, L., Marano, A., & Marrow, J. (2021). FFT phase-field model combined with cohesive composite voxels for fracture of composite materials with interfaces. Computational Mechanics, 68(2), 433-457.
[4]. Chen, Y., Vasiukov, D., Gélébart, L., & Park, C. H. (2019). A FFT solver for variational phase-field modeling of brittle fracture. Computer Methods in Applied Mechanics and Engineering, 349, 167-190.
[5]. Cuomo, S., Di Cola, V. S., Giampaolo, F., Rozza, G., Raissi, M., & Piccialli, F. (2022). Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next. arXiv preprint arXiv:2201.05624.

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