Probabilistic simulation for the certification of railway vehicles

Christine Funfschilling, Guillaume Perrin, Michel Sebes, Yann Bezin, Laura Mazzola, Mac Lan Nguyen-Tajan

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

The present dynamic certification process that is based on experiments has been essentially built on the basis of experience. The introduction of simulation techniques into this process would be of great interest. However, an accurate simulation of complex, nonlinear systems is a difficult task, in particular when rare events (for example, unstable behaviour) are considered. After analysing the system and the currently utilized procedure, this paper proposes a method to achieve, in some particular cases, a simulation-based certification. It focuses on the need for precise and representative excitations (running conditions) and on their variable nature. A probabilistic approach is therefore proposed and illustrated using an example. First, this paper presents a short description of the vehicle / track system and of the experimental procedure. The proposed simulation process is then described. The requirement to analyse a set of running conditions that is at least as large as the one tested experimentally is explained. In the third section, a sensitivity analysis to determine the most influential parameters of the system is reported. Finally, the proposed method is summarized and an application is presented.

Original languageEnglish
Pages (from-to)770-781
Number of pages12
JournalProceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
Volume229
Issue number6
Early online date17 Jun 2015
DOIs
Publication statusPublished - 1 Aug 2015

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