﻿ 不同优化算法在稳压器重量优化中的比较
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 应用科技  2020, Vol. 47 Issue (2): 98-103  DOI: 10.11991/yykj.201905020 0

### 引用本文

LI Chunmei, LI Yi, LIU Lizhi, et al. Comparison of different optimization algorithms in weight optimization of a pressurizer[J]. Applied Science and Technology, 2020, 47(2): 98-103. DOI: 10.11991/yykj.201905020.

### 文章历史

Comparison of different optimization algorithms in weight optimization of a pressurizer
LI Chunmei, LI Yi, LIU Lizhi, HAO Chengming, SUN Guanyu, ZHANG Qi, WANG Yi, XIE Lidong, MIAO Yiran, XIA Junbao, YAN Siwei
Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu 610041, China
Abstract: In order to supply a feasible method to optimize the design of nuclear power plant, the case study on the weight optimization of pressurizer, which is one of the key devices in nuclear power system with pressurized water reactor, is performed in this paper. The improved complex algorithm, genetic algorithm and particle swam algorithm are incorporated in the optimization case study as representative algorithms. Such performance as global optimization, convergence, stability and efficiency are compared among three selected algorithms. The results show that in aspect of the pressurizer weight optimization, the genetic algorithm can find global optimization scheme in greater possibility as well as the particle swam algorithm, while the improved complex algorithm takes the advantage in aspects of convergence and efficiency. The findings in this paper are beneficial to the optimization of nuclear power plant.
Keywords: pressurizer    design optimization    weight optimization    improved complex algorithm    genetic algorithm    particle swam algorithm    optimization of nuclear power plant    convergence

1 稳压器计算模型

1.1 稳压器容积计算模型

1.2 稳压器重量计算模型

1.2.1 封头壁厚计算

 ${\delta _1} = \frac{{PDk}}{{2[\sigma ]\varphi - 0.5P}}$

 ${\delta _2} = \frac{{PD}}{{2[\delta ]\varphi - P}}$ (1)

 ${\delta _3} = \frac{{PD}}{{2[\delta ]r - P}}$

1.2.2 稳压器重量的计算

1）若稳压器采用椭圆封头，则其重量可由式（2）确定：

 ${M_1} = \left\{ {\frac{{{\rm{2{\text{π}} }}{{(D + 2{\delta _1})}^2}}}{{\rm{3}}}{{h'}_1} - \frac{{{\rm{2{\text{π}} }}{D^2}}}{{\rm{3}}}{h_{\rm{1}}}} \right\}\rho$ (2)

 ${M_1} = \left\{ {\frac{{{\text{π}}}}{6}\left[ {{{\left( {D + 2{\delta _1}} \right)}^3} - {D^3}} \right]} \right\}\rho$

 ${M_1} = \left\{ {\frac{{2{{\text{π}}}}}{3}\left[ {{{\left( {D + 2{\delta _1}} \right)}^3} - {D^3}} \right]} \right\}\rho$

2）圆柱筒体重量

 $\begin{array}{l} {M_2} = \dfrac{{{\text{π}}}}{4}\left[ {{{\left( {D + 2{\delta _2}} \right)}^2} - {D^2}} \right]{H_y}\rho \\ \;\;\;\;{H_y} = {H_{{\rm{PR}}}} - 2{H_s} - {H_2} \end{array}$

3）电加热区筒体重量

 ${M_3} = \frac{{{\text{π}}}}{4}\left[ {{{\left( {D + 2{\delta _3}} \right)}^2} - {D^2}} \right]{H_2}\rho$

4）稳压器总重量

 $M = 2{M_1} + {M_2} + {M_3}$

 ${M_{{\rm{PR}}}} = 2{M_1} + {M_2} + {M_3} + {M_4}$

2 优化算法 2.1 复合形算法

2.2 遗传算法

2.3 粒子群算法

3 稳压器重量优化问题

 ${{M}}({{{X}}_{{\rm{opt}}}}) = \min [M({{X}})],\forall {{X}} \in { R}$ (3)

4 结果与讨论 4.1 敏感性分析

4.2 优化计算结果比较