Characteristic Statistic Algorithm （CSA） for In-Core Loading Pattern Optimization

LIU Zhi-hong; HU Yong-ming; SHI Gong

Jun. 2007

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LIU Zhi-hong, HU Yong-ming, SHI Gong. Characteristic Statistic Algorithm （CSA） for In-Core Loading Pattern Optimization[J]. Nuclear Power Engineering, 2007, 28(2): 1-4,18.

Citation:

LIU Zhi-hong, HU Yong-ming, SHI Gong. Characteristic Statistic Algorithm （CSA） for In-Core Loading Pattern Optimization[J]. Nuclear Power Engineering, 2007, 28(2): 1-4,18.

LIU Zhi-hong, HU Yong-ming, SHI Gong. Characteristic Statistic Algorithm （CSA） for In-Core Loading Pattern Optimization[J]. Nuclear Power Engineering, 2007, 28(2): 1-4,18.

Citation:

LIU Zhi-hong, HU Yong-ming, SHI Gong. Characteristic Statistic Algorithm （CSA） for In-Core Loading Pattern Optimization[J]. Nuclear Power Engineering, 2007, 28(2): 1-4,18.

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Characteristic Statistic Algorithm （CSA） for In-Core Loading Pattern Optimization

1. Institute of Nuclear Energy Technology, Tsinghua University, Beijing, 100084, China;
2. Department of Engineering Physics, Tsinghua University, Beijing, 100084, China

Received Date: 2006-01-11
Rev Recd Date: 2006-05-16

Available Online: 2025-07-21

Abstract

Abstract

To solve the problem of PWR in-core loading pattern optimization,a more suitable global optimization algorithm,i.e.,Characteristic statistic algorithm（CSA）,is used.The searching process of this algorithm and how to apply it to this problem are presented.Loading pattern optimization code SCYCLE is developed.Two different problems on real PWR models are calculated and the results are compared with other algorithms.It is shown that SCYCLE has high efficiency and good global performance on this problem.
- Characteristic Statistic algorithm（CSA）,
- Optimization,
- Loading Pattern