A modified multi-objective sorting particle swarm optimization and its application to the design of the nose shape of a high-speed train

Abstract

Based on the concepts of niche count and crowding distance, a modified multi-objective particle swarm optimization (MPSO) is introduced. The niche count and crowding distance are used to determine the globally best particle across four test cases using an external file. A comparative analysis was carried out between MPSO and non-dominated sorting multiobjective adaptive genetic algorithms, both real-coded and binary-coded. The results show that MPSO based on the crowding distance is best for getting the Pareto front, especially for problems with high-dimensional and non-continuous Pareto fronts. In order to verify the efficiency of MPSO in solving engineering problems, the optimal design of the aerodynamic nose shape of high-speed trains was undertaken using a modified vehicle modeling function (MVMF) parametric method. Taking the aerodynamic drag of the whole train (Cd) and the aerodynamic lift of the trailer car (Cl) as the optimization goals, the Kriging surrogate model was introduced to reduce the computational time, and the MPSO based on crowding distance was used to find the Pareto front. The optimization results show that MPSO is efficient at getting the Pareto front; compared to the original shape, the Cd and Cl of the optimal shape are reduced by 1.6% and 29.74%, respectively.

Skin Friction Reduction Characteristics of Nonsmooth Surfaces Inspired by the Shapes of Barchan Dunes

“…With the rapid development of computational mathematics, computational fluid dynamics (CFD) has been widely applied in engineering practice because of advantages of short calculation period and low cost. Yao et al [23] conducted an optimal design for the aerodynamic nose shapes of highspeed trains using modified multiobjective particle swarm optimization. The numerical simulation results showed the aerodynamic drag for the whole train (Cd) and aerodynamic lift for the trailer car (Cl) of the optimal shape are reduced by 1.6% and 29.74%, respectively.…”

Research on aerodynamic optimization of high-speed train’s slipstream

“…When performing parametrization of the streamlined shape, a large number of design variables are required (Yao et al, 2016). In the present paper, the vehicle modeling function (VMF) method is adopted to parametrize the streamlined shape, the details of which could be referred to in literature (Yao et al, 2014(Yao et al, , 2015, and will not be mentioned in detail here.…”

“…As a result, an unsteady numerical method is adopted to perform the aerodynamic optimization with the slipstream as its objective in the present study. Currently, except for the optimization on micro pressure waves , most aerodynamic optimization studies are based on steady numerical simulations (Vytla et al, 2010;Yao et al, 2014;Yao et al, 2015). Optimization based on an unsteady approach is rather rare [8].…”

“…Parametric design is a major difficulty for aerodynamic optimization design of high-speed trains. Current studies usually focus on some limited parameters of the streamlined shape and their relationship with the flow field around the train (Vytla et al, 2010;Yao et al, 2014Yao et al, , 2015Yao et al, , 2016. Yao et al (2016) developed several threedimensional parametric methods to perform the aerodynamic optimization study of high-speed trains, in which the cross section of the train is always kept constant, so that the influence of the geometry of the train body on aerodynamic performance of the train couldn't be analyzed.…”

The effect of moving train on the aerodynamic performances of train-bridge system with a crosswind

“…Besides, for the train-bridge system with a moving vehicle, it is not easy to measure the aerodynamic forces on the bridge. At the same time, with the rapid development of computer technology, the CFD approach is also widely approved and adopted in the studies (Alonso-Estébanez et al, 2017;Mosavi, Shamshirband, Salwana, Chau, & Tah, 2019;Niu et al, 2018;Sun, Song, & An, 2012;Yao, Guo, Sun, & Yang, 2015;Zhang, Yu, Zhang, Wu, & Li, 2019), which can better capture the flow characteristics around train-bridge system and easily obtain the aerodynamics affiliated to the train and bridge, compared with a moving vehicle wind tunnel test and full-scale experiment. At present, the dynamic mesh and sliding mesh method are usually used to present the movement of the train in the simulation.…”