摘要
针对目前锯齿型板翅式换热器未能同时优化多参数,或者大多优化研究存在对经验关联式依赖的问题,提出了利用Kriging响应面来近似目标函数与设计变量之间的关系、应用遗传算法对锯齿型板翅式换热器翅片结构参数的优化方法。在维持翅片通道雷诺数为800时,把换热器的最大j因子、最小f因子和最大F_(TEF)因子作为3个单目标函数,对翅片的翅片高度h、翅片间距s、翅片厚度t和翅片节距l进行了优化研究。研究结果表明:翅片高度h与翅片间距s对换热器综合性能F_(TEF)因子呈正增长,而翅片厚度t和翅片节距l呈负增长;在翅片高度为9.5mm、翅片间距为2.2mm、翅片厚度为0.1mm和翅片节距为3mm时,换热器性能最佳;结合Kriging响应面的遗传算法克服了传统优化方法对经验关联式的依赖。该研究结果可以指导锯齿型板翅式换热器的优化设计。
In the current optimization for plate fin heat exchanger with offset fins,simultaneous multi-parameter optimization is rarely considered,or researches usually depend on empirical relations.A strategy by genetic algorithm（GA）combined with Kriging response surface is proposed,where the Kriging response surface provides an approximate relationship between the objective function and design variables.The fin height h,fin space s,fin thickness t and interrupted length j of offset fins are taken as four optimization parameters,while maximumj factor,minimumffactor and maximumF_（TEF）factor as three single objective functions at Reynolds number of 800.The results show that the effects of the fin height and fin space on the overall performance F_（TEF）factor are positive and the effects of the fin thickness and the interrupted length are negative;the heat exchanger performance reaches the optimum as fin height h=9.5mm,fin space s=2.1 mm,fin thickness t=0.1 mm and interrupted length l=3 mm;the genetic algorithm combined with Kriging response surface eliminates the dependence on empirical rela-tions.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2015年第12期90-96,共7页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(51106119
81100707)
中央高校基本科研业务费专项资金资助项目
