Probabilistic simulation for the certification of railway vehicles

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

Application de la méthode semi-Hertzienne pour la simulation du passage d'un TGV sur un appareil de voie

Dans la plupart des simulations en dynamique ferroviaire, le profil de rail est supposé constant le long de la voie. Cette hypothèse ne peut plus être retenue si l'on considère des appareils de voie. Les cœurs à pointes mobiles sont des composants d'appareils de voie conçus pour éviter le franchissement d'une lacune (présente dans les appareils classiques) permettant ainsi un roulement le plus continu possible, recherché dans le cas des grandes vitesses. L'objet des simulations est le calcul des contraintes à l'interface roue-rail lors du franchissement d'une pointe mobile par un TGV. Le problème du contact roue-rail est résolu par la méthode dite "semi-Hertzienne" qui autorise des formes d'empreintes plus réalistes que les ellipses de Hertz. Le principe de la méthode est brièvement présenté. Le cas traité permet de montrer l'avantage de la méthode lorsque l'on s'intéresse aux contraintes de contact

A multi-Hertzian contact model considering plasticity

Multi-body-system (MBS) simulation is widely used in the railway industry. One of its major topics is the assessment of rolling contact fatigue (RCF). This damaging process is linked to plasticity. MBS wheel–rail contact models usually neglect plasticity as it does not change the vehicle behaviour. With the proposed method, contact stresses are consistent with a perfect plastic law. This new method has been recently detailed: it is an extension of the STRIPES semi-Hertzian (SH) model. A multi-Hertzian (MH) variant is here described, which is less exact but faster than the SH method. This new method has been implemented in a MBS package without resulting in a much longer execution time than elastic models

International benchmarking of longitudinal train dynamics simulators: results

This paper presents the results of the International Benchmarking of Longitudinal Train Dynamics Simulators which involved participation of nine simulators (TABLDSS, UM, CRE-LTS, TDEAS, PoliTo, TsDyn, CARS, BODYSIM and VOCO) from six countries. Longitudinal train dynamics results and computing time of four simulation cases are presented and compared. The results show that all simulators had basic agreement in simulations of locomotive forces, resistance forces and track gradients. The major differences among different simulators lie in the draft gear models. TABLDSS, UM, CRE-LTS, TDEAS, TsDyn and CARS had general agreement in terms of the in-train forces; minor differences exist as reflections of draft gear model variations. In-train force oscillations were observed in VOCO due to the introduction of wheelâ\u80\u93rail contact. In-train force instabilities were sometimes observed in PoliTo and BODYSIM due to the velocity controlled transitional characteristics which could have generated unreasonable transitional stiffness. Regarding computing time per train operational second, the following list is in order of increasing computing speed: VOCO, TsDyn, PoliTO, CARS, BODYSIM, UM, TDEAS, CRE-LTS and TABLDSS (fastest); all simulators except VOCO, TsDyn and PoliTo achieved faster speeds than real-time simulations. Similarly, regarding computing time per integration step, the computing speeds in order are: CRE-LTS, VOCO, CARS, TsDyn, UM, TABLDSS and TDEAS (fastest)