Data-driven rapid prediction model for aerodynamic force of high-speed train with arbitrary streamlined head
Chen, Dawei2; Sun ZX(孙振旭)1; Yao, Shuanbao2; 许盛峰Xu, Shengfeng1; Yin B(银波)1; Guo DL(郭迪龙)1; Yang GW(杨国伟)1; Ding, Sansan2
刊名ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS
2022-12-31
卷号16期号:1页码:2190-2205
关键词Aerodynamic force inverse design high-speed train SVM numerical simulation wind tunnel test
ISSN号1994-2060
DOI10.1080/19942060.2022.2136758
通讯作者Sun, Zhenxu(sunzhenxu@imech.ac.cn)
英文摘要Due to the complicated geometric shape, it's difficult to precisely obtain the aerodynamic force of high-speed trains. Taking numerical and experimental data as the training data, the present work proposed a data-driven rapid prediction model to solve this problem, which utilized the Support Vector Machine (SVM) model to construct a nonlinear implicit mapping between design variables and aerodynamic forces of high-speed train. Within this framework, it is a key issue to achieve the consistency and auto-extraction of design variables for any given streamlined shape. A general parameterization method for the streamlined shape which adopted the idea of step-by-step modeling has been proposed. Taking aerodynamic drag as the prediction objective, the effectiveness of the model was verified. The results show that the proposed model can be successfully used for performance evaluation of high-speed trains. Keeping a comparable prediction accuracy with numerical simulations, the efficiency of the rapid prediction model can be improved by more than 90%. With the enrichment of data for the training set, the prediction accuracy of the rapid prediction model can be continuously improved. Current study provides a new approach for aerodynamic evaluation of high-speed trains and can be beneficial to corresponding engineering design departments.
分类号一类
资助项目Youth Innovation Promotion Association CAS[2019020]
WOS研究方向Engineering ; Mechanics
语种英语
WOS记录号WOS:000884571500001
资助机构Youth Innovation Promotion Association CAS
其他责任者Sun, Zhenxu
内容类型期刊论文
源URL[http://dspace.imech.ac.cn/handle/311007/90783]  
专题力学研究所_流固耦合系统力学重点实验室(2012-)
作者单位1.Chinese Acad Sci, Inst Mech, Key Lab Mech Fluid Solid Coupling Syst, Beijing, Peoples R China
2.CRRC Qingdao Sifang Co Ltd, Qingdao, Peoples R China;
推荐引用方式
GB/T 7714
Chen, Dawei,Sun ZX,Yao, Shuanbao,et al. Data-driven rapid prediction model for aerodynamic force of high-speed train with arbitrary streamlined head[J]. ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS,2022,16(1):2190-2205.
APA Chen, Dawei.,孙振旭.,Yao, Shuanbao.,许盛峰Xu, Shengfeng.,银波.,...&Ding, Sansan.(2022).Data-driven rapid prediction model for aerodynamic force of high-speed train with arbitrary streamlined head.ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS,16(1),2190-2205.
MLA Chen, Dawei,et al."Data-driven rapid prediction model for aerodynamic force of high-speed train with arbitrary streamlined head".ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS 16.1(2022):2190-2205.
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