遗传算法在含不凝气体冷凝传热试验中的应用

Application of Genetic Algorithm in Condensation Heat Transfer Experiment with Non Condensable Gas

为拓展试验参数范围,支持非能动安全壳工程设计,使用遗传算法针对含有不凝性气体的冷凝传热试验建立了优化数学模型。使用罚函数法定义增广目标函数,优化描述对流传热的无量纲参数(ρ_w-ρ_b)/ρ_b。混合气源的温度、气源中空气分压以及二次侧冷却水温度为控制变量;约束条件包括二次侧制冷机的冷却功率以及混合气源的压力。优化计算得到在现有试验设施上最大化目标无量纲参数的试验参数解。优化结果指导了试验的开展,拓宽了蒸汽冷凝传热试验方法。

The optimization mathematical model for steam condensation heat transfer experiment using genetic algorithm method, so as to expand experiment variable range and support the design of passive containment. Dimensionless number （ρw-ρb）/ρb is the optimization object. Penalty function method is used to set the objective function. The temperature of the gas source, the air partial pressure in the gas source and the temperature of coolant water are taken as the controlled variables. The cooling capacity of the system and the total pressure of the gas source are taken as constraints. The optimization calculation results gave the solution for maximizing the optimiza- tion object on the present test facility. The results had broadened the design method for condensation heat transfer experiment.