遗传算法在板翅式换热器尺寸优化中的应用

提出了应用遗传算法对板翅式换热器的尺寸优化方法。该方法根据不同设计要求,把换热器的重量或效率分别作为遗传算法的目标函数,冷热两侧的翅片间距、高度作为待寻找最佳值的优化变量。设计方法的实施包括遗传算法程序和性能校核程序两大模块,其中遗传算法程序采用二进制编码、锦标赛选择、均匀交叉和单点变异,以及采用基于小生境下的共享技术和择优策略;性能校核程序中根据个体解码后的结构尺寸进行性能评价。应用结果表明,与原始数据比较,换热器的重量(效率)都有不同程度地减小(增加),但在工程实际中不宜采用效率最高为目标函数。该文的设计方法具有通用性,可作为优化设计不同换热器的结构尺寸。

Geometrical Optimization Design of Plate-fin Heat Exchanger Using Genetic Algorithm

A strategy for the optimization design of Plate-Fin Heat eXchanger (PFHX) was developed using Genetic Algorithms (GA). For different required designs, weight or effectiveness of a PFHX can be taken as an objective function respectively. Different parameters such as fin pitch and height on each side of PFHX were considered as variables to be optimized by means of GA approach The implement of optimum design consists of two routines, one is GA routine which included binary coding for tournament selection, uniform crossover and one-point mutation. Niching and elitism were adopted. The other is rating (RAT) routine which is used to evaluated performance of PFHX, and may be performed after decoding individuals to real geometrical sizes. An example from literature was solved with proposed method. The results show that the optimized PFHXs have lighter weight or higher effectiveness than those original cases. For a PFHX with high effectiveness in engineering practice, seeking higher effectiveness is not recommended due to sharply increase of the weight. The optimizing method of PFHX is universal and can be used for various PFHXs with those parameters of fin and layer can be modified into real world problems.