Optimisation of AGR-Like FHR Fuel Assembly Using Multi-Objective Particle Swarm Algorithm
Utilising molten salt as coolant instead of carbon dioxide in traditional advanced gas-cooled reactors (AGRs) can potentially increase their core power density, simplify the safety case and shorten the time needed for the development of the fluoride-salt-cooled high-temperature reactor (FHR). Howeve...
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Veröffentlicht in: | Journal of Nuclear Engineering 2021-03, Vol.2 (1), p.35-43 |
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description | Utilising molten salt as coolant instead of carbon dioxide in traditional advanced gas-cooled reactors (AGRs) can potentially increase their core power density, simplify the safety case and shorten the time needed for the development of the fluoride-salt-cooled high-temperature reactor (FHR). However, the change of coolant has a strong impact on the system behaviour. Therefore, a new type of fuel assembly is required. However, the design of a new assembly is affected by a wide range of parameters. Systematic search through all the potential configurations is prohibitively computationally expensive. In this work, a multi objective particle swarm optimisation (MOPSO) algorithm is utilised to identify the most attractive candidate configurations for the hybrid AGR-like FHR assembly. The first optimisation step targets basic design parameters such as radius and enrichment of the fuel pins, their number and arrangement. MOPSO is based on the concept of Pareto dominance, which is used to determine the flight direction of the simulated particles. The outcome of the optimisation process provides insight on families of possible solutions, which described by the Pareto front. |
doi_str_mv | 10.3390/jne2010004 |
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subjects | Algorithms Assembly Carbon dioxide Configurations Coolants Design optimization Design parameters Fluorides Fuels Gas cooled reactors Graphite High temperature Molten salts Nuclear engineering Nuclear fuels Nuclear reactors Nuclear safety Pressure vessels Velocity |
title | Optimisation of AGR-Like FHR Fuel Assembly Using Multi-Objective Particle Swarm Algorithm |
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