Reduced-Order Modelling with Domain Decomposition Applied to Multi-Group Neutron Transport
Autor: | Christopher C. Pain, Brendan Tollit, Claire Heaney, Toby R. F. Phillips, Paul N. Smith |
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Přispěvatelé: | Engineering & Physical Science Research Council (E, Engineering & Physical Science Research Council (EPSRC) |
Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Neutron transport
Mathematical optimization Technology Control and Optimization Energy & Fuels Computer science 020209 energy neutron diffusion equation reactor physics Energy Engineering and Power Technology Basis function 02 engineering and technology 01 natural sciences lcsh:Technology 09 Engineering 010305 fluids & plasmas Domain (software engineering) Simple (abstract algebra) 0103 physical sciences 0202 electrical engineering electronic engineering information engineering model reduction Electrical and Electronic Engineering Engineering (miscellaneous) reduced-order modelling Science & Technology 02 Physical Sciences Renewable Energy Sustainability and the Environment Group (mathematics) lcsh:T Domain decomposition methods Construct (python library) domain decomposition Slab Energy (miscellaneous) |
Zdroj: | Energies, Vol 14, Iss 1369, p 1369 (2021) Energies; Volume 14; Issue 5; Pages: 1369 |
ISSN: | 1996-1073 |
Popis: | Solving the neutron transport equations is a demanding computational challenge. This paper combines reduced-order modelling with domain decomposition to develop an approach that can tackle such problems. The idea is to decompose the domain of a reactor, form basis functions locally in each sub-domain and construct a reduced-order model from this. Several different ways of constructing the basis functions for local sub-domains are proposed, and a comparison is given with a reduced-order model that is formed globally. A relatively simple one-dimensional slab reactor provides a test case with which to investigate the capabilities of the proposed methods. The results show that domain decomposition reduced-order model methods perform comparably with the global reduced-order model when the total number of reduced variables in the system is the same with the potential for the offline computational cost to be significantly less expensive. |
Databáze: | OpenAIRE |
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