Projects: Projects for Investigator |
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Reference Number | EP/M022684/1 | |
Title | Predictive Modelling for Nuclear Engineering | |
Status | Completed | |
Energy Categories | Nuclear Fission and Fusion(Nuclear Fission, Nuclear supporting technologies) 100%; | |
Research Types | Basic and strategic applied research 100% | |
Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 100% | |
UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
Principal Investigator |
Dr AG Buchan No email address given Earth Science and Engineering Imperial College London |
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Award Type | Standard | |
Funding Source | EPSRC | |
Start Date | 01 January 2016 | |
End Date | 18 June 2017 | |
Duration | 18 months | |
Total Grant Value | £662,151 | |
Industrial Sectors | Energy | |
Region | London | |
Programme | Energy : Energy | |
Investigators | Principal Investigator | Dr AG Buchan , Earth Science and Engineering, Imperial College London (100.000%) |
Industrial Collaborator | Project Contact , AMEC Wind Energy (0.000%) Project Contact , AWE Plc (0.000%) Project Contact , Florida State University, USA (0.000%) Project Contact , HMS Sultan (0.000%) Project Contact , Hitachi, Ltd., Japan (0.000%) Project Contact , University of South Carolina, USA (0.000%) |
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Web Site | ||
Objectives | ||
Abstract | 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. | |
Data | No related datasets |
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Projects | No related projects |
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Publications | No related publications |
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Added to Database | 25/08/16 |