SMR fuel cycle optimization using LWROpt

被引:2
|
作者
Ottinger K.E. [1 ]
Maldonado G.I. [1 ]
机构
[1] University of Tennessee, Department of Nuclear Engineering, Knoxville, 37996-2300, TN
来源
Ottinger, Keith E. (kottinge@utk.edu) | 1600年 / American Society of Mechanical Engineers (ASME), United States卷 / 03期
关键词
Control rod pattern search; Fuel cycle optimization; Small modular reactors (SMRs);
D O I
10.1115/1.4034573
中图分类号
学科分类号
摘要
This article describes the light water reactor optimizer (LWROpt), a fuel cycle optimization code originally developed for BWRs, which has been adapted to perform core fuel reload and/or operational control rod management for pressurized water reactors (PWRs) and small modular reactors (SMRs), as well. Additionally, the eighth-core symmetric shuffle option is introduced to help expedite large-scale optimizations. These new features of the optimizer are tested by performing optimizations starting from a base case of an SMR core model that was developed manually and unrodded. The new fuel inventory (NFI) and loading pattern (LP) search in LWROpt was able to eliminate all of the constraint violations present in the initial base solution. However, independent control rod pattern (CRP) searches for the best several LPs found were not successful in generating CRPs without any constraint violations. This indicates that fully decoupling the fuel loading from the CRP optimization can increase the computational tractability of these calculations but at the expense of effectiveness. To improve on the individual search results, a coupled fuel loading (NFI and LP) and CRP search was performed, which produced a better overall result but still with some small constraint violations, emphasizing the fact that optimizing the fuel loading arrangement in a small high-leakage unborated core while concurrently determining its operational rod patterns for a 4-year operational cycle is no easy feat even to an experienced core designer; thus, this process can be greatly aided by employing automated combinatorial optimization tools. © 2017 ASME.
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