Automatic Layout and Optimization Method of Nuclear Power Plant
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摘要: 计算机技术的飞速发展使得核动力工程智能设计成为趋势，而核电厂房智能布置设计也是重要的一部分。本文建立了用以描述设备空间需求的设备间多空间模型，并将其作为布置设计的操作基础单元，基于穴度算法与吸引子法建立了设备间定序定位方法进行设备间布置，并在定序定位后考虑通道的空间占用对设备间进行调整，实现了核电厂房自动化布置设计，随后结合混合遗传算法形成核电厂房自动化布置优化方法。最后本文以核电厂房部分设备作为研究对象，以厂房布置参数为优化变量，以厂房布置方案占地面积最小为优化目标，通过优化搜索得到的最优布置方案占地面积为1160.44 m2，有效占用面积比例达到93.70%，结果证明核电厂房自动化布置与智能优化方法可行。Abstract: With the rapid development of computer technology, the intelligent layout design of nuclear power engineering has become a trend, and the intelligent layout of nuclear power plant is also an important part. In this paper, a multi-space model of equipment room was established to describe the equipment space requirements as the basic operation unit, and an equipment room sequencing and positioning method was established based on the cavitation algorithm and attractor method for equipment room layout. And the space occupation of the passage was considered to adjust the equipment room to realize the automatic layout design method of nuclear power plant. Then, a hybrid genetic algorithm was combined to form the automatic layout optimization method for nuclear power plant. Finally, this paper takes some equipment of nuclear power plant as the research object, takes plant layout parameters as the optimization variables, and takes the floor area of plant layout scheme as the optimization objective. The optimal layout scheme obtained by optimized search covers an area of 1160.44 m2, and the effective occupied area ratio reaches 93.70%. The results prove that the automatic layout and intelligent optimization methods of nuclear power plant are feasible.
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表 1 厂房设备间尺寸信息
Table 1. Size Information of Plant Equipment Room
设备编号 长/mm 宽/mm 设备编号 长/mm 宽/mm 13 11400 3000 404 7100 4670 14 11400 3000 405 7100 4670 43 4300 2700 406 7100 4670 44 4300 2700 407 7100 4670 45 4300 2700 408 9000 3600 46 6611 3628 409 7200 4500 400 7100 4670 410 3820 6240 401 7100 4670 411 7200 5400 402 7100 4670 412 6393 6500 403 7100 4670 413 6393 6500 
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表 2 优化变量信息
Table 2. Optimization Variable Information
序号 优化变量 变量下限 变量上限 最优方案 1 容器初始长度/mm 15000 50000 25559.11 2 容器初始宽度/mm 15000 50000 25177.36 3 定序长度权值 −10 10 6.43 4 定序宽度权值 −10 10 0.90 5 定序面积权值 −10 10 −2.49 6 定位贴面数权值 −10 10 0.61 7 定位他贴面数权值 −10 10 8.30 8 定位贴面率权值 −10 10 6.58 9 吸引子x吸引度权值 −10 10 2.96 10 吸引子y吸引度权值 −10 10 3.17 11 吸引子x值/mm 0 5000 2858.82 12 吸引子y值/mm 0 5000 2173.95
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表 3 算法参数信息
Table 3. Algorithm Parameter Information
序号 算法参数 参数值 1 每一代个体数 10 2 迭代数 50 3 精英选择比例 0.1 4 复合形计算次数 5
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