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International Journal of Frontiers in Engineering Technology, 2024, 6(1); doi: 10.25236/IJFET.2024.060118.

Research on Head Shape Optimization of High-speed Trains Based on Multifactor ANOVA and Streamlined Head Optimization CST Methods


Yutong Zuo

Corresponding Author:
Yutong Zuo

Department of Rail Transit, Anhui Vocational and Technical College, Hefei, Anhui, China


This paper explores the optimization of high-speed train shapes, focusing on reducing wind resistance and noise. A multi-factor ANOVA model and streamlined head optimization CST method are used to analyze structural parameters. The study first establishes a wind resistance model, selecting the TP1-type high-speed railway for its minimal air resistance. The paper then optimizes the train head shape, identifying the warhead structure as optimal for aerodynamics. Additionally, it examines noise reduction in locomotive heads, finding the platypus-shaped TP4 type most effective. Finally, the results culminate in a comprehensive optimization model for the train head shape, providing an optimal design sketch with structural parameters.


High-Speed Train Design, Aerodynamics, Wind Resistance, Noise Reduction

Cite This Paper

Yutong Zuo. Research on Head Shape Optimization of High-speed Trains Based on Multifactor ANOVA and Streamlined Head Optimization CST Methods. International Journal of Frontiers in Engineering Technology (2024), Vol. 6, Issue 1: 114-119. https://doi.org/10.25236/IJFET.2024.060118.


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