Uncertainty modelling in metamodels for fire risk analysis

Florian Berchtold, Lukas Arnold, Christian Knaust, Sebastian Thöns

Research output: Contribution to journalArticlepeer-review

Abstract

In risk-related research of fire safety engineering, metamodels are often applied to approximate the results of complex fire and evacuation simulations. This approximation may cause epistemic uncertainties, and the inherent uncertainties of evacuation simulations may lead to aleatory uncertainties. However, neither the epistemic ‘metamodel uncertainty’ nor the aleatory ‘inherent uncertainty’ have been included in the results of the metamodels for fire safety engineering. For this reason, this paper presents a metamodel that includes metamodel uncertainty and inherent uncertainty in the results of a risk analysis. This metamodel is based on moving least squares; the metamodel uncertainty is derived from the prediction interval. The inherent uncertainty is modelled with an original approach, directly using all replications of evacuation scenarios without the assumption of a specific probability distribution. This generic metamodel was applied on a case study risk analysis of a road tunnel and showed high accuracy. It was found that metamodel uncertainty and inherent uncertainty have clear effects on the results of the risk analysis, which makes their consideration important.

Original languageEnglish
Article number50
JournalSafety
Volume7
Issue number3
DOIs
Publication statusPublished - 2021 Sep

Bibliographical note

Funding Information:
Funding: The authors gratefully acknowledge the computing time granted (project jjsc27) by the JARA-HPC Vergabegremium and VSR commission on the supercomputer JURECA [36] at Forschungszentrum Jülich. This research was funded by the German Ministry for Education and Research (BMBF), contract No. 13N13266 (project ORPHEUS). BMBF did not influence this research and publication in any aspects.

Subject classification (UKÄ)

  • Other Civil Engineering

Keywords

  • Evacuation
  • Fire
  • Metamodel
  • Risk
  • Surrogate
  • Uncertainty

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