% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Berchtold:893214,
      author       = {Berchtold, Florian and Arnold, Lukas and Knaust, Christian
                      and Thöns, Sebastian},
      title        = {{U}ncertainty {M}odelling in {M}etamodels for {F}ire {R}isk
                      {A}nalysis},
      journal      = {Safety},
      volume       = {7},
      number       = {3},
      issn         = {2313-576X},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2021-02631},
      pages        = {50 -},
      year         = {2021},
      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.},
      cin          = {IAS-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)IAS-7-20180321},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / ORPHEUS -
                      Optimierung der Rauchableitung und Personenführung in
                      U-Bahnhöfen: Experimente und Simulationen (BMBF-13N13266) /
                      Pyrolysis Modeling $(jjsc27_20190501)$},
      pid          = {G:(DE-HGF)POF4-5111 / G:(DE-Juel1)BMBF-13N13266 /
                      $G:(DE-Juel1)jjsc27_20190501$},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000701089200001},
      doi          = {10.3390/safety7030050},
      url          = {https://juser.fz-juelich.de/record/893214},
}