Boiling Water Reactor In-Core Fuel Management through Parallel Simulated Annealing in FORMOSA-B
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Date
2009-04-27
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Abstract
A commercial nuclear power plant with a boiling water reactor will
utilize between 368 and 800+ individual fuel assemblies to generate
steam for 18 to 24 months between refueling outages. The composition
and reactivity of each fuel assembly will vary due to variations in
initial enrichment, burnable poison loading and irradiation conditions
in the core. These variations pose a challenge to the engineers who
must design subsequent reloads because only one quarter to one half of
the fuel will be replaced at a time. One of the challenges is to
determine the optimum layout of the fuel within the core in order to
get the highest value from the fuel without violating any safety or
operational limits. The FORMOSA-B program was
developed to automatically find a family
of optimum loading patterns by combining a robust, accurate 3-D core
simulator with a simulated annealing loading pattern search. Other
features have been added to allow the program to rapidly compute
shutdown margins and optimize control rod programming
through the application of heuristic rules. One
drawback of the FORMOSA-B program is that long run-times,
sometimes exceeding a week, are
required to generate and evaluate the large numbers of solutions
required by the simulated annealing algorithm. The rising popularity
and availability of parallel computing and computational clusters
provides a possible solution to the problem of long run-times. To
this end, a parallel simulated annealing capability has been developed
for the FORMOSA-B program.
The parallel simulated annealing driver utilizes standardized Message
Passing Interface routines to divide the individual Markov search
chains of the simulated annealing algorithm among a large number of
processors. By evaluating multiple loading patterns concurrently, run
times are significantly reduced. In testing with a 368-assembly BWR/4
model, parallel speedup factors exceeding 32 were observed with 48
processors. Parallel efficiencies are calculated to be in the range
of 68% to 95% when correcting for hardware variations and CRP update
frequency. Further testing was performed to investigate the
effects on the annealing performance of the Control Rod Programming
update frequency, Markov chain length versus parallelization width and
solution downselect method.
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Keywords
Boiling Water Reactor, BWR, , Optimization, Fuel Management, Nuclear, Simulated Annealing, Parallel Computing
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Degree
MS
Discipline
Nuclear Engineering