Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

October 30, 2023


Pages


DOI

Article

Application of improved genetic algorithm in the optimal design of seismic parameters of rail vehicle

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Authors

Wei Zhang Affiliation:
School of Urban Rail, Shandong Polytechnic, Jinan, Shandong, 250104, China.


Abstract

This paper first considers the seismic parameter model of rail vehicles with rail constraints and investigates the mechanism of beam-rail interaction under earthquake action. The computational parameters of rails, main girders, and piers are optimized using analytical and finite element methods during earthquake action. Finally, the NSGA-II genetic algorithm is improved and applied to optimize the seismic parameters of rail vehicles, and seismic damage indexes evaluate the damage to rails and vehicles. The results show that by optimizing the seismic parameters of rail vehicles, the track damage is lower than the median value of μ [μ1 = 1.03404, μ2= 1.2013] under the same earthquake intensity, and the probability of lateral damage to vehicles is reduced by 0.15. Applying the improved genetic algorithm proposed in this paper can effectively improve the seismic performance of rail vehicles and provide some theoretical support for the design and safety of rail vehicles.


Keywords

Track restraint, Seismic parameters, Finite element, Beam-rail interaction, NSGA-II genetic algorithm, 65D17


Citation

Zhang, W. (2023). Application of improved genetic algorithm in the optimal design of seismic parameters of rail vehicle. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00853

Published by: Engineering Journals

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