Analysis of the model-based corrector approach for explicit cosimulation

Timo Haid*, Daniel Watzenig, Georg Stettinger

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In many industries, the focus of testing is currently shifting away from classical hardware tests to the virtual verification and validation of products. To this end, cosimulation has become a common tool for the simulation and analysis of complex systems that span multiple engineering domains and usually involve multiple, heterogeneous and application-specific simulation environments. In particular, the so-called explicit cosimulation allows a widespread application since it has minimal requirements regarding the capabilities of the tool interfaces. However, explicit cosimulation also poses a numerical challenge, especially when the system includes stiff coupling loops. The model-based corrector approach presented in Haid et al. (The 5th Joint International Conference on Multibody System Dynamics, 2018) provides a method for the efficient cosimulation of such systems. In this article, this model-based corrector approach is extended to additional extrapolation methods. By modeling the cosimulation process through a linear recurrence equation and applying it to the two-mass oscillator test model, the influence of model-based correction on the underlying extrapolation methods in terms of stability, accuracy, and error convergence is analyzed. It is shown that adding model-based correction can significantly improve the overall cosimulation, allowing > 10 times larger macrostep sizes or reducing the cosimulation error by a factor of 10 or more in some cases.

Original languageEnglish
Pages (from-to)137-163
Number of pages27
JournalMultibody System Dynamics
Volume55
Issue number1-2
DOIs
Publication statusPublished - Jun 2022

Keywords

  • Accuracy analysis
  • Error convergence
  • Explicit cosimulation
  • Model-based correction
  • Propagation matrix
  • Stability analysis

ASJC Scopus subject areas

  • Modelling and Simulation
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Control and Optimization

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