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Scenario Substructure Method (SSM) for Simulation of Long Trains

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Advances in Dynamics of Vehicles on Roads and Tracks (IAVSD 2019)

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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Abstract

The simulation of long trains is a great challenge, especially if all vehicle and infrastructural properties are to be considered in detail. As part of a derailment investigation, a method was developed which uses the principle of superposition of mechanics to separate the longitudinal dynamics from vertical and lateral dynamics in train simulations, the so-called Scenario Substructure Method (SSM). In the first phase, the longitudinal dynamics of the entire train is calculated using simple models, while in the second phase the superposition of the vertical and lateral dynamics is carried out with complex models. Thus, the simulation of the accident (until the derailment occurs) can be split into two phases. The presented Scenario Substructure Method describes a procedure in which the computational effort can be substantially minimized and variant calculations with a few detailed models are possible. The starting point for the development of the Scenario Substructure Method is the task of simulating the derailment of a long freight train consisting of 48 single wagons in a switch due to an initiated emergency braking. This paper uses the example of the freight train accident to apply the Scenario Substructure Method. The different possibilities of the superposition are compared and evaluated. Furthermore, an estimation of the effort reduction for the simulation calculations is carried out and compared to a detailed modelling.

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References

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Correspondence to Sönke Lück or Rolf Naumann .

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Lück, S., Naumann, R. (2020). Scenario Substructure Method (SSM) for Simulation of Long Trains. In: Klomp, M., Bruzelius, F., Nielsen, J., Hillemyr, A. (eds) Advances in Dynamics of Vehicles on Roads and Tracks. IAVSD 2019. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-38077-9_35

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  • DOI: https://doi.org/10.1007/978-3-030-38077-9_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-38076-2

  • Online ISBN: 978-3-030-38077-9

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