Multi-Objective Aerodynamic Optimization of a High-Speed Train Head Shape Based on an Optimal Kriging Model
- سال انتشار: 1401
- محل انتشار: دوماهنامه مکانیک سیالات کاربردی، دوره: 15، شماره: 3
- کد COI اختصاصی: JR_JAFM-15-3_015
- زبان مقاله: انگلیسی
- تعداد مشاهده: 279
نویسندگان
State Key Laboratory of Heavy Duty AC Drive Electric Locomotive Systems Integration
Key Laboratory of Traffic Safety on Track, Ministry of Education, School of Traffic & Transportation Engineering, Central South University, Changsha, ۴۱۰۰۷۵, China
State Key Laboratory of Heavy Duty AC Drive Electric Locomotive Systems Integration
Key Laboratory of Traffic Safety on Track, Ministry of Education, School of Traffic & Transportation Engineering, Central South University, Changsha, ۴۱۰۰۷۵, China
چکیده
An optimal Kriging surrogate model based on a ۵-fold cross-validation method and improved artificial fish swarm optimization is developed for improving the aerodynamic optimization efficiency of a high-speed train running in the open air. The developed optimal Kriging model is compared with the original Kriging model in two test sample points, and the prediction errors are all reduced to within ۵%. Thus, the optimal Kriging model is selected for use in each iteration to approximate the CFD simulation model of a high-speed train in subsequent optimization. After that, the strong Pareto evolutionary algorithm II (SPEA۲) is adopted to obtain a series of Pareto-optimal solutions. Based on the above work, a multi-objective aerodynamic optimization design for the head shape of a high-speed train is performed using a free-form deformation (FFD) parameterization approach. After optimization, the aerodynamic drag coefficient of the head car and the aerodynamic lift coefficient of the tail car are reduced by ۵.۲% and ۳۲.۶%, respectively. The results demonstrate that the optimization framework developed in this paper can effectively improve optimization efficiency.کلیدواژه ها
High-speed train, Multi-objective aerodynamic optimization, FFD method, Improved artificial fish swarm algorithm, Optimal Kriging model, SPEA۲ algorithmاطلاعات بیشتر در مورد COI
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