Multi-Objective Optimization of Rail Pre-Grinding Profile in Straight Line for High Speed Railway

doi:10.1007/s12204-018-1974-1

Abstract

Abstract: In order to modify the rail pre-grinding profile smoothly, non-uniform rational B-spline (NURBS) curve with weight factors is used to establish a parameterized model of the profile. A wheel-rail contact stochastic finite element model (FEM) is constructed by the Latin hypercube sampling method and 3D elasto-plastic FEM, in which the wheelset’s lateral displacement quantity is regarded as a random variable. The maximum values of nodal accumulated contact stress (NACS) and nodal mean contact stress (NMCS) in different pre-grinding profiles with differential weight factors are calculated and taken as the training samples to establish two Kriging models. A multi-objective optimization model of pre-grinding profile is established, in which the objective functions are the NACS and NMCS Kriging models. The optimum weight factors are sought using a non-dominated sorting genetic algorithm II (NSGA-II), and the corresponding optimum pre-grinding profile is obtained. The contact stress calculation before and after optimization indicates that the maximum values of NACS and NMCS decline significantly.

Key words: rail grinding| profile optimization| Kriging model| lateral displacement quantity| non-dominated sorting genetic algorithm II (NSGA-II)

摘要： In order to modify the rail pre-grinding profile smoothly, non-uniform rational B-spline (NURBS) curve with weight factors is used to establish a parameterized model of the profile. A wheel-rail contact stochastic finite element model (FEM) is constructed by the Latin hypercube sampling method and 3D elasto-plastic FEM, in which the wheelset’s lateral displacement quantity is regarded as a random variable. The maximum values of nodal accumulated contact stress (NACS) and nodal mean contact stress (NMCS) in different pre-grinding profiles with differential weight factors are calculated and taken as the training samples to establish two Kriging models. A multi-objective optimization model of pre-grinding profile is established, in which the objective functions are the NACS and NMCS Kriging models. The optimum weight factors are sought using a non-dominated sorting genetic algorithm II (NSGA-II), and the corresponding optimum pre-grinding profile is obtained. The contact stress calculation before and after optimization indicates that the maximum values of NACS and NMCS decline significantly.

关键词: rail grinding| profile optimization| Kriging model| lateral displacement quantity| non-dominated sorting genetic algorithm II (NSGA-II)

CLC Number:

U 213.2

ZENG Wei (曾威), QIU Wensheng (丘文生), REN Tao (任涛), SUN Wen (孙文), YANG Yue (杨岳). Multi-Objective Optimization of Rail Pre-Grinding Profile in Straight Line for High Speed Railway[J]. Journal of Shanghai Jiao Tong University (Science), 2018, 23(4): 527-.

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