Stochastic vs deterministic vs AI accelerated methods for HTGR design

About the Project

High-temperature gas-cooled reactors (HTGRs) are of significant interest to the UK due to their ability to deliver high-temperature, low-carbon energy for applications beyond electricity generation, and building on the UK’s extensive experience of gas-cooled reactor operation. HMG has selected the High Temperature Gas-cooled Reactor (HTGR) as the most credible Advanced Modular Reactor (AMR) technology.

Achieving improved performance requires accurate, high-fidelity modelling to reliably predict power distributions and ensure fuel operates within design limits.

The aim of this project is to establish a robust, validated framework for neutronics and thermal analysis of prismatic HTGR cores, integrating Monte Carlo simulation, deterministic methods, and AI/ML-assisted techniques. The study seeks to improve predictive accuracy for key performance and safety parameters while addressing the challenges associated with cross-section generation and homogenisation in HTGRs.

The project will aim to:

• Quantify the limitations of conventional deterministic HTGR analysis, particularly those arising from cross-section homogenisation and energy group structure.
• Investigate the use of AI/ML algorithms to predict or generate cross sections, enabling deterministic solvers to better capture strong heterogeneities and flux gradients.
• Provide insight on the appropriate use of Monte Carlo, deterministic, and AI-accelerated approaches for HTGR design, safety assessment, and operational analysis.
• Develop and validate a multiscale thermal solver tailored to prismatic HTGRs, capable of resolving heat transfer at the TRISO particle, fuel compact, and graphite block levels, and tightly coupled to a Monte Carlo neutronics solver.

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.

Funding

This 3.5-year PhD project is fully funded, home students are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend to increase each year. The start date is October 2026.

We recommend that you apply early as the advert may be removed before the deadline.

Before you apply

We strongly recommend that you contact the supervisors for this project before you apply. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.

How to apply

Apply online through our website: https://uom.link/pgr-apply-2425

When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees.

Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.

After you have applied you will be asked to upload the following supporting documents:

• Final Transcript and certificates of all awarded university level qualifications
• Interim Transcript of any university level qualifications in progress
• CV
• Supporting statement: A one or two page statement outlining your motivation to pursue postgraduate research and why you want to undertake postgraduate research at Manchester, any relevant research or work experience, the key findings of your previous research experience, and techniques and skills you’ve developed. (This is mandatory for all applicants and the application will be put on hold without it).
• Contact details for two referees (please make sure that the contact email you provide is an official university/work email address as we may need to verify the reference)
• English Language certificate (if applicable)

If you have any questions about making an application, please contact our admissions team by emailing FSE.doctoralacademy.admissions@manchester.ac.uk.