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
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