流体机械2025，Vol.53Issue(11)：52-57,67,7.DOI:10.3969/j.issn.1005-0329.2025.11.007
R290板式蒸发器性能仿真与多目标优化分析
Performance simulation and multi-objective optimization analysis of R290 plate evaporator
摘要
Abstract
To address the challenges of limited heat transfer performance,high simulation costs,and low optimization efficiency faced by the environmentally friendly refrigerant R290(propane)with low GWP(global warming potential)and zero ODP(ozone depletion potential)in the design of efficient heat exchangers,a distributed parameter model and algorithm were established,significantly improving computational efficiency.The predicted heat exchange error was only 2.78％,showing good agreement with experiments.Selecting corrugation inclination angle(β),corrugation pitch-to-height ratio(p/b),and plate length-to-width ratio(L/W)as design variables,an artificial neural network(ANN)surrogate model was constructed and coupled with the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for multi-objective parameter optimization.The results show that the model's mean squared error(MSE)is only 0.54％,and the coefficient of determination(R2)is as high as 0.996 6,demonstrating strong predictive capability.By comprehensively analyzing heat exchange performance and pressure drop cost and analyzing the Pareto front,the optimal parameter combination is obtained:β=50°,p/b=2.0,L/W=2.0,achieving a total heat exchange increase of 31.20％.The research results provide a reliable method for the efficient design of R290 plate evaporators,contributing to the performance upgrade and low-carbon transition of environmentally friendly refrigeration systems.关键词
板式蒸发器/R290/分布参数模型/人工神经网络/遗传算法Key words
plate evaporator/R290/distributed parameter model/artificial neural network/genetic algorithm分类
能源科技引用本文复制引用
YANG Peilian,LEI Rui,SHUAI Weiqiang,LIU Bin,HU Haitao,LI Xuan..R290板式蒸发器性能仿真与多目标优化分析[J].流体机械,2025,53(11):52-57,67,7.基金项目
国家自然科学基金项目(52476013) （52476013）
高端压缩机及系统技术全国重点实验室开放基金项目(SKL-YSJ202306) （SKL-YSJ202306）
