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Details of Grant 

EPSRC Reference: EP/M022684/1
Title: Predictive Modelling for Nuclear Engineering
Principal Investigator: Buchan, Dr AG
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Earth Science and Engineering
Organisation: Imperial College London
Scheme: EPSRC Fellowship
Starts: 01 January 2016 Ends: 18 June 2017 Value (£): 662,151
EPSRC Research Topic Classifications:
Energy - Nuclear
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
16 Mar 2015 Eng Fellowship Interviews Mar 2015 Announced
25 Feb 2015 Engineering Prioritisation Panel Meeting 25 February 2015 Announced
Summary on Grant Application Form
Computer models have played a central role in assessing the behaviour of nuclear power facilities for decades, they have ensured nuclear operations remain safe to both the public and the environment. The aim of the project is to develop a new and highly advanced modelling capability that is accurate, robust and validated. A new multi-physics, predictive modelling framework will be formed for simulating neutron transport, fluid flows and structural interaction problems. It aims to combine novel and world leading technologies in numerical methods and high performance computing to form a simulation tool for geometrically complex, nuclear engineering problems. This will surpass current computational capabilities, by providing modelling accuracy through the use of efficient adaptive resolution, and will tackle grand challenge problems such as full core reactor modelling. This model will be developed within a predictive framework that combines modelling with uncertainty and experimental data. This is a vital component as inherent uncertainties in data, geometry, parameterisations and measurement will place uncertainties in the modelled predictions. By integrating these uncertainties within the calculations we can quantify the uncertainty they place on the final result.

The combination of all these technologies will result in the first modelling framework of its kind, offering unprecedented detail through optimised resolution with combined uncertainty quantification and data assimilation. It will provide substantially improved analysis of nuclear facilities, improve operational efficiency and, ultimately, help ensure its safety. The project will work closely with world leading academics and industry, both within the UK and overseas. This collaboration will result in the technologies being used to analyse future reactor designs, including those reactors due to be built in the UK over the coming years.

Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Organisation Website: http://www.imperial.ac.uk