Pre-research on Enhanced Heat Transfer Method for Special Vehicles at High Altitude Based on Machine Learning  

作　　者：Chunming Li Xiaoxia Sun Hongyang Gao Yu Zhang 

机构地区：[1]China North Vehicle Research Institute,Beijing 100072,China [2]Mechanical Engineering Department,Zhejiang University City College,Hangzhou 310015,China

出　　处：《Chinese Journal of Mechanical Engineering》2023年第2期314-326,共13页中国机械工程学报（英文版）

基　　金：Zhejiang Provincial Natural Science of China (Grant No.LQ20E060003);Zhejiang Provincial Basic Public Welfare Research Project of China (Grant No.LGG20E050007);Key Projects of Hangzhou Agricultural and Social Development Research Program of China (Grant No.20212013B04);Projects of Hangzhou Agricultural and Social Development Research Program of China (Grant Nos.20201203B128,20212013B04);Scientific Research Foundation of Zhejiang University City College of China (Grant Nos.J-202116,X-202205);2021 Teacher Professional Development Program for Domestic Visiting Scholars in Universities of China (Grant No.FX2021105)。

摘　　要：The performance of an integrated thermal management system signi?cantly in?uences the stability of special-purpose vehicles;thus,enhancing the heat transfer of the radiator is of great signi?cance.Common research methods for radiators include?uid mechanics numerical simulations and experimental measurements,both of which are time-consuming and expensive.Applying the surrogate model to the analysis of the?ow and heat transfer in louvered?ns can effectively reduce the computational cost and obtain more data.A simpli?ed louvered-?n heat transfer unit was established,and computational?uid dynamics(CFD)simulations were conducted to obtain the?ow and heat transfer characteristics of the geometric structure.A three-factor and six-level orthogonal design was established with three structural parameters:angleθ,length a,and pitch L_p of the louvered?ns.The results of the orthogonal design were subjected to a range analysis,and the effects of the three parametersθ,a,and L_p on the j,f,and JF factors were obtained.Accordingly,a proxy model of the heat transfer performance for louvered?ns was established based onthe arti?cial neural network algorithm,and the model was trained with the data obtained by the orthogonal design.Finally,the?n structure with the largest JF factor was realized.Compared with the original model,the optimizedmodel improved the heat transfer factor j by 2.87%,decreased the friction factor f by 30.4%,and increased the comprehensive factor JF by 15.7%.

关 键 词：Louvered fins Numerical simulation Machine learning Comprehensive performance 

分 类 号：U469.6[机械工程—车辆工程] TP181[交通运输工程—载运工具运用工程]