2026-09-19T02:03:41Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/824432022-01-13T07:54:05Zcom_1721.1_7582com_1721.1_7581col_1721.1_131024
Kord Smith.
Burns, Chad (Chad D.), III
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering.
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
2013-11-18T19:23:56Z
2013-11-18T19:23:56Z
2013
http://hdl.handle.net/1721.1/82443
862978075
Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2013.
"June 2013." Cataloged from PDF version of thesis.
Includes bibliographical references (pages 32-33).
Given the highly complex nature of neutronics and reactor physics, efficient methods of optimizing are necessary to effectively design the core reloading pattern and operate a nuclear reactor. The current popular methods for optimization are Simulated Annealing and the Genetic Algorithm; this paper explores the potential for a new method called Greedy Exhaustive Dual Binary Swaps (GEDBS). The mandatory trade-off in computation is accuracy for speed; GEDBS is an exhaustive search and tends toward longer runtimes. While GEDBS performed acceptably for the criterion administered in this paper (local peaking and k, on a Boiling Water Reactor (BWR) fuel lattice) the exhaustive nature of GEDBS will inevitably lead to combinatorial explosion for the addition of the potential dozens of factors that commercial application mandates. This issue may be resolved with the addition of metaheuristics to reduce the search space for GEDBS, or by an increasing computation.
by Chad Bums.
S.B.
40 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Nuclear Science and Engineering.
Optimization algorithms in boiling water reactor lattice design
Optimization algorithms in BWR lattice design
Thesis
application/pdf
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Publication
unknown
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<Abstract>Given the highly complex nature of neutronics and reactor physics, efficient methods of optimizing are necessary to effectively design the core reloading pattern and operate a nuclear reactor. The current popular methods for optimization are Simulated Annealing and the Genetic Algorithm; this paper explores the potential for a new method called Greedy Exhaustive Dual Binary Swaps (GEDBS). The mandatory trade-off in computation is accuracy for speed; GEDBS is an exhaustive search and tends toward longer runtimes. While GEDBS performed acceptably for the criterion administered in this paper (local peaking and k, on a Boiling Water Reactor (BWR) fuel lattice) the exhaustive nature of GEDBS will inevitably lead to combinatorial explosion for the addition of the potential dozens of factors that commercial application mandates. This issue may be resolved with the addition of metaheuristics to reduce the search space for GEDBS, or by an increasing computation.</Abstract>
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