基于遗传算法的蜂窝板换热器多目标优化

摘要

Based on the Workbench goal driven optimization system, genetic algorithm was used to optimize a honeycombed plate heat transfer exchanger. The effects of structural parameters (P1,P2, andP3) on the optimization objectives were investigated and the sensitivity of these parameters was studied. The results show that the honeycombed structure disrupts the fluid flow around the boundary layer which greatly improves heat transfer.Re has no effects on the relationship between the studied parameters and the objective function under the current calculation conditions.P2 has the most obvious influence on the objective function and 3 groups of optimal results were obtained. Correlation of heat transfer and flow was obtained by fitting the results at 3000≤Re≤ 25000, which shows certain universality for honeycombed plate heat transfer exchangers with similar structures.%基于Workbench目标驱动优化系统，采用遗传算法对蜂窝板换热器进行了多目标优化研究，探讨了焊孔半径P1、蜂窝板半径P2、焊点间距P3等结构参数对蜂窝板各优化目标的影响并考察了各参数灵敏度。结果表明：蜂窝板结构不断扰乱了流体的边界层，很大程度上强化了传热；在研究范围内雷诺数的改变并不影响各参数与目标函数的关系；发现蜂窝板半径P2对各优化目标影响最大，并得出了3组较优结果；通过对蜂窝板在3000≤Re≤25000的数据结果进行关联，得到了蜂窝板流动换热的准则关系式，对此结构有一定的通用性。