Proceedings of the 3rd International Conference on Green Building, Civil Engineering and Smart City (GBCESC 2024)

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Research on Aerodynamic Load Prediction of High-Speed Train based on Kriging Interpolation Algorithm

Authors
Taihui Zuo1, Wanjuan Xie2, *, Yunfeng Zou3
1College of Urban and Rural Development, Zhongkai University of Agriculture and Engineering, Guangzhou, China
2Information Network Engineering and Research Center, South China University of Technology, Guangzhou, China
3School of Civil Engineering, Central South University, Changsha, China
*Corresponding author. Email: wanjuanxie@scut.edu.cn
Corresponding Author
Wanjuan Xie
Available Online 19 May 2025.
DOI
10.2991/978-94-6463-728-1_68How to use a DOI?
Keywords
High-speed train; Wind pressure distribution; Aerodynamic coefficient; Kriging interpolation algorithm; Neural network
Abstract

To address the inaccuracies associated with the aerodynamic force coefficients and wind loads obtained from wind tunnel tests of the high-speed railway train models, this paper presents a method for predicting surface wind pressures and aerodynamic forces on trains based on Kriging interpolation model. Using wind tunnel test data from the CRH380A high-speed train head car model, a historical dataset for predictive purposes is established. The Kriging interpolation model is then employed to forecast the surface wind pressures on the train. In parallel, both the Kriging interpolation model and an enhanced AdaBoost_BP neural network method is applied to predict the aero-dynamic properties of the train. Comparative analysis of the predicted data against the wind tunnel test data illustrates that the Kriging interpolation algorithm is capable of effectively predicting the surface wind pressures and aerodynamic coefficients of high-speed trains, yielding prediction results with notably higher accuracy. This high-lights the efficacy of the Kriging method in enhancing the precision of aerodynamic predictions for high-speed railway vehicles.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference on Green Building, Civil Engineering and Smart City (GBCESC 2024)
Series
Advances in Engineering Research
Publication Date
19 May 2025
ISBN
978-94-6463-728-1
ISSN
2352-5401
DOI
10.2991/978-94-6463-728-1_68How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Taihui Zuo
AU  - Wanjuan Xie
AU  - Yunfeng Zou
PY  - 2025
DA  - 2025/05/19
TI  - Research on Aerodynamic Load Prediction of High-Speed Train based on Kriging Interpolation Algorithm
BT  - Proceedings of the 3rd International Conference on Green Building, Civil Engineering and Smart City (GBCESC 2024)
PB  - Atlantis Press
SP  - 727
EP  - 736
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-728-1_68
DO  - 10.2991/978-94-6463-728-1_68
ID  - Zuo2025
ER  -