Saturn_Nuclear_CDT
UoM_Nuclear
As part of the UK’s transition to a low carbon economy, the UK Government is committed to delivering new and advanced nuclear power, and has stated its preference for High Temperature Gas Reactors (HTGRs) and Advanced Modular Reactors (AMRs) [1]. HTGRs and numerous AMR designs use graphite in the reactor core, where it not only acts as a neutron moderator/reflector, but as a structural component. The graphite plays a pivotal role in the reactor and can dictate the operational lifetime of a reactor. Thus, it is essential that the designer and operators of HTGRs and AMRs have an understanding of how the graphite and graphite components within the reactor core will behave both during reactor operation and under accident scenarios.
In an HTGR or AMR core, the graphite will be subjected to temporal and spatial variations in fast neutron fluence, temperature, and, in some cases, thermal oxidation. The combination of these loadings leads to changes in the material properties and dimensions of the graphite [2]. The safe operation of the reactors requires the structural integrity of these nuclear graphite components to be accurately assessed. Central to this is the constitutive models of nuclear graphite under service conditions. Existing constitutive models are largely empirical and often struggle to reflect the dominating mechanisms across a wide range of operating conditions. It is hypothesised that a physics-informed machine learning (PIML) framework, integrating material property data and microstructure information of irradiated graphite, can provide more accurate and robust predictions of graphite behaviour than conventional constitutive models.
The aim of this project is to develop and validate a physics-informed machine learning framework for constitutive modelling of nuclear graphite under HTGR/AMR service conditions. The primary objectives to achieve this aim include:
1. Develop a database of irradiated graphite behaviour under representative reactor service conditions. Both the microstructure and material properties data from existing irradiation programs will be investigated. A database will be built that will be used as the starting point of a baseline machine learning model for irradiated graphite properties.
2. Extract quantitative descriptors to the microstructure of irradiated graphite including but not constrained to pores, pore connectivity, pore size distribution, filler/binder phase compositions, etc.
3. Link the measured material properties with the extracted microstructure descriptors using machine learning (ML).
4. Investigate the microstructure dependence of the irradiated graphite properties. Formulate the predicted graphite properties from ML into constitutive models for the irradiation dimensional change, elasticity, irradiation creep, and thermal expansion.
5. Integrate the developed model into a numerical solver (preferably finite element) and use that for graphite component integrity assessment under hypothetic HTGR/AMR working environments.
About SATURN
This PhD is based with the SATURN Centre for Doctoral Training. SATURN is made up form a consortium of NW Universities that include Manchester, Bangor, Leeds, Liverpool, Lancaster, Sheffield and Strathclyde. The ethos of the programme is to recruit students from across STEM and give them the necessary skills and training to become a subject matter expert in the nuclear sector in either industry or academia. You will be recruited with a cohort of other researchers all looking at nuclear- focused research but from across the breadth of the sector. Your training will include an introduction to nuclear course, as well as opportunities to do a deep dive in the areas that really interest you. You will also have the opportunity to broaden your experience and skills by visiting internationally relevant facilities, having an industry secondment, undertaking leadership training, and involving yourself in outreach and public engagement activities. If this sounds like the sort of opportunity that you are looking for, we would love to hear from you.
Nuclear Boot Camp (Months 1 - 3)
The Bootcamp is based in Manchester. For any of our students based at partner institutions.
Eligibility
Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline.
Before you apply
We strongly recommend that you contact the supervisor(s) for this project before you apply. For informal enquiries, please contact Xun Zhang (xun.zhang@manchester.ac.uk)
Projects are subject to funding confirmation
How to apply
Please complete the Enquiry Form to express your interest. We strongly recommend you contact the project supervisor after completing the form to speak to them about your suitability for the project.
If your qualifications meet our standard entry requirements, the CDT Admissions Team will send your enquiry form and CV to the named project supervisor.
Our application process can also be found on our website: here If you have any questions, please contact SATURN@manchester.ac.uk.
Equality, diversity and inclusion
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.
We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.
We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).
