Aerodynamic optimisation of a high-speed train head shape using an advanced hybrid surrogate-based nonlinear model repre
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RESEARCH ARTICLE
Aerodynamic optimisation of a high-speed train head shape using an advanced hybrid surrogate-based nonlinear model representation method Zhao He1,2,3 • Xiaohui Xiong1,2,3 • Bo Yang1,2,3 • Haihong Li1,2,3 Received: 6 February 2020 / Revised: 13 June 2020 / Accepted: 16 August 2020 Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract A global optimisation strategy based on the hybrid surrogate model method and the competitive mechanism-based multi-objective particle swarm optimisation (CMOPSO) algorithm was developed to improve the accuracy of the aerodynamic performance optimisation of a high-speed train running in open air without a crosswind. Free-form deformation was used to improve the optimisation efficiency without remodelling or remeshing. The sample points and their responses were obtained via optimal Latin hypercube sampling and computational fluid dynamics (CFD) simulations. The hybrid surrogate model (HSM) was constructed by using the theory of optimal weighted surrogate to combine a polynomial response surface (PRS) model with a radial basis function (RBF) model. Comprehensive error evaluation results indicated that the prediction accuracy achieved with the HSM was higher than that achieved with either the PRS model or the RBF model; thus, the HSM was selected for use in each iteration to approximate the CFD simulation model of the high-speed train in subsequent optimisation. Then, the CMOPSO algorithm was selected as the optimisation algorithm. After optimisation, a series of Pareto-optimal solutions was obtained, and the optimal and original head shapes were compared. The use of the hybrid surrogate model and the CMOPSO algorithm greatly improved the optimisation efficiency. Keywords High-speed train Aerodynamic performance Multi-objective optimisation FFD method Hybrid surrogate model CMOPSO algorithm
& Xiaohui Xiong [email protected] 1
Key Laboratory of Traffic Safety on the Track of Ministry of Education, School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
2
Joint International Research Laboratory of Key Technology for Rail Traffic Safety, Central South University, Changsha 410075, China
3
National and Local Joint Engineering Research Center of Safety Technology for Rail Vehicle, Changsha 410075, China
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1 Introduction The slenderness ratio of a high-speed train running on rails is much larger than those of other vehicles, and in the case of high-speed operation, the aerodynamic characteristics become more complicated. Therefore, the goals of reducing aerodynamic drag, aerodynamic lift, and noise have become key issues in the optimisation design of high-speed train head shapes (Tian 2019). The head of a high-speed train has a complex streamlined shape with dozens of design parameters. At present, the design methods for optimising the aerodynamic performance of high-speed trains mainly rely on obtaining the relationships between the
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