Efficient Quantification of Model Uncertainties When De-boarding a Train

Authors

  • Florian Künzner Department of Informatics, Technical University of Munich, Munich, Germany
  • Tobias Neckel Department of Informatics, Technical University of Munich, Munich, Germany
  • Hans-Joachim Bungartz Department of Informatics, Technical University of Munich, Munich, Germany
  • Felix Dietrich Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, USA
  • Gerta Köster Munich University of Applied Sciences, Munich, Germany

DOI:

https://doi.org/10.17815/CD.2020.104

Keywords:

pedestrian dynamics, uncertainty quantification, surrogate models

Abstract

It is difficult to provide live simulation systems for decision support. Time is limited and uncertainty quantification requires many simulation runs. We combine a surrogate model with the stochastic collocation method to overcome time and storage restrictions and show a proof of concept for a de-boarding scenario of a train.

References

Iaccarino, G., “Quantification of uncertainty in flow simulations using probabilistic methods, “ Report

on VKI Lecture Series, Sept. 8-12, pp. 1-30, 2008.

Von Sivers I. et al., “Modelling social identification and helping in evacuation simulation,” Safety

Science, vol. 89, pp. 288-300, 2016.

Smith, R.C., “Uncertainty Quantification: Theory, Implementation, and Applications,” SIAM

Computational Science and Engineering, 2014.

Xiu, D. and Karniadakis, G.E., “The Wiener–Askey polynomial chaos for stochastic differential

equations,” SIAM Journal on Scientific Computing, vol. 24(2), pp.359–718, 2002.

Dietrich et al., “Numerical model construction with closed observables,” SIAM Journal on Applied

Dynamical Systems, vol. 15, pp. 2078-2108, 2016.

Dietrich et al., “Fast and flexible uncertainty quantification through a data driven surrogate model,”

International Journal of Uncertainty Quantification, vol. 8, pp. 175-192 2018.

Coifman, R.R. and Lafon, S., “Diffusion maps, Applied and Computational Harmonic Analysis,” vol.

(1), pp. 5-30, 2006.

Downloads

Published

12.08.2020

How to Cite

Künzner, F., Neckel, T., Bungartz, H.-J., Dietrich, F., & Köster, G. (2020). Efficient Quantification of Model Uncertainties When De-boarding a Train. Collective Dynamics, 5, 477–479. https://doi.org/10.17815/CD.2020.104

Issue

Section

Proceedings of Pedestrian and Evacuation Dynamics 2018