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| Hauptseite > Publikationsdatenbank > Risk Analysis for Road Tunnels – A Metamodel to Efficiently Integrate Complex Fire Scenarios > print |
| Hauptseite > Publikationsdatenbank > Risk Analysis for Road Tunnels – A Metamodel to Efficiently Integrate Complex Fire Scenarios > print |
| 001 | 844684 | ||
| 005 | 20210129233035.0 | ||
| 020 | _ | _ | |a 978-91-88695-48-2 |
| 024 | 7 | _ | |a 2128/17755 |2 Handle |
| 037 | _ | _ | |a FZJ-2018-02069 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Berchtold, Florian |0 P:(DE-HGF)0 |b 0 |
| 111 | 2 | _ | |a Eighth International Symposium on Tunnel Safety and Security |g ISTSS 2018 |c Borås |d 2018-03-14 - 2018-03-16 |w Sweden |
| 245 | _ | _ | |a Risk Analysis for Road Tunnels – A Metamodel to Efficiently Integrate Complex Fire Scenarios |
| 260 | _ | _ | |a Stockholm |c 2018 |b RISE Research Institutes of Sweden AB |
| 295 | 1 | 0 | |a Proceedings from the 8th International Symposium on Tunnel Safety and Security |
| 300 | _ | _ | |a 349 - 360 |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
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| 520 | _ | _ | |a 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. |
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| 700 | 1 | _ | |a Knaust, Christian |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Arnold, Lukas |0 P:(DE-Juel1)132044 |b 2 |e Corresponding author |u fzj |
| 700 | 1 | _ | |a Thöns, Sebastian |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Rogge, Andreas |0 P:(DE-HGF)0 |b 4 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/844684/files/Berchtold_ISTSS2018.pdf |
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