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@INPROCEEDINGS{Berchtold:844684,
author = {Berchtold, Florian and Knaust, Christian and Arnold, Lukas
and Thöns, Sebastian and Rogge, Andreas},
title = {{R}isk {A}nalysis for {R}oad {T}unnels – {A} {M}etamodel
to {E}fficiently {I}ntegrate {C}omplex {F}ire {S}cenarios},
address = {Stockholm},
publisher = {RISE Research Institutes of Sweden AB},
reportid = {FZJ-2018-02069},
isbn = {978-91-88695-48-2},
pages = {349 - 360},
year = {2018},
comment = {Proceedings from the 8th International Symposium on Tunnel
Safety and Security},
booktitle = {Proceedings from the 8th International
Symposium on Tunnel Safety and
Security},
abstract = {Fires in road tunnels constitute complex scenarios with
interactions between the fire, tunnel users and safety
measures. More and more methodologies for risk analysis
quantify the consequences of these scenarios with complex
models. Examples for complex models are the computational
fluid dynamics model Fire Dynamics Simulator (FDS) and the
microscopic evacuation model FDS+Evac. However, the high
computational effort of complex models often limits the
number of scenarios in practice. To balance this drawback,
the scenarios are often simplified. Accordingly, there is a
challenge to consider complex scenarios in risk analysis.To
face this challenge, we improved the metamodel used in the
methodology for risk analysis presented on ISTSS 2016. In
general, a metamodel quickly interpolates the consequences
of few scenarios simulated with the complex models to a
large number of arbitrary scenarios used in risk analysis.
Now, our metamodel consists of the projection array-based
design, the moving least squares method, and the prediction
interval to quantify the metamodel uncertainty.
Additionally, we adapted the projection array-based design
in two ways: the focus of the sequential refinement on
regions with high metamodel uncertainties; and the
combination of two experimental designs for FDS and
FDS+Evac.To scrutinise the metamodel, we analysed the
effects of three sequential refinement steps on the
metamodel itself and on the results of risk analysis. We
observed convergence in both after the second step (ten
scenarios in FDS, 192 scenarios in FDS+Evac). In comparison
to ISTSS 2016, we then ran 20 scenarios in FDS and 800
scenarios in FDS+Evac. Thus, we reduced the number of
scenarios remarkably with the improved metamodel. In
conclusion, we can now efficiently integrate complex
scenarios in risk analysis. We further emphasise that the
metamodel is broadly applicable on various experimental or
modelling issues in fire safety engineering.},
month = {Mar},
date = {2018-03-14},
organization = {Eighth International Symposium on
Tunnel Safety and Security, Borås
(Sweden), 14 Mar 2018 - 16 Mar 2018},
cin = {IAS-7},
cid = {I:(DE-Juel1)IAS-7-20180321},
pnm = {511 - Computational Science and Mathematical Methods
(POF3-511)},
pid = {G:(DE-HGF)POF3-511},
typ = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
url = {https://juser.fz-juelich.de/record/844684},
}