Identification of key design parameters of high-speed train for optimal design

Zhang, Jian, Ding, Guofu, Zhou, Y. S., Jiang, J., Ying, X. and Qin, Sheng-feng (2014) Identification of key design parameters of high-speed train for optimal design. The International Journal of Advanced Manufacturing Technology, 73 (1-4). pp. 251-265. ISSN 0268-3768

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Official URL: http://dx.doi.org/10.1007/s00170-014-5822-7

Abstract

As a complex mechatronic system, the running stability, safety, and comfort of high-speed train are affected by many design variables. It is of great difficulty to identify a set of effective design parameters to optimize its running performance. The current simulation systems like the SIMPACK can simulate the running dynamics, but cannot be used effectively for optimal design of the train and rail system because there are too many design variables being supposed to be dealt with. Therefore, there is a need to make a software solution from simulation analysis to optimal design so that the computer-aided design (CAD) and engineering (CAE) can be integrated into an integral design process. This paper presents a new method to identify the key design variables against the running performance indicators based on the sensitivity analysis, which in turn bases itself on simulation-oriented surrogate models. In this way, the optimal design of a high-speed train can be successfully conducted because (1) the surrogate model can reduce the simulation time greatly and (2) the design variable space with the key variables will be reduced significantly. The research shows that this method is of practical significance for speeding up the design of high-speed train or similar complex mechatronic systems.

Item Type: Article
Uncontrolled Keywords: high-speed train, surrogate model, design variable reduction, sensitivity analysis, neural network
Subjects: H700 Production and Manufacturing Engineering
Department: Faculties > Arts, Design and Social Sciences > School of Design > Design
Faculties > Arts, Design and Social Sciences > School of Design > Design
Faculties > Arts, Design and Social Sciences > School of Design > Design
Depositing User: Nicola King
Date Deposited: 24 Jul 2014 08:43
Last Modified: 31 Mar 2016 13:59
URI: http://nrl.northumbria.ac.uk/id/eprint/17277

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