Advanced Monte Carlo Method for model uncertainty propagation in risk assessment
| Autor: | El Abed El Safadi, Olivier Adrot, Jean-Marie Flaus |
|---|---|
| Přispěvatelé: | Gestion et Conduite des Systèmes de Production (G-SCOP_GCSP), Laboratoire des sciences pour la conception, l'optimisation et la production (G-SCOP), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Geofencing DG research project, Adrot, Olivier |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Monte Carlo method
Markov chain Monte Carlo uncertainty propagation [SPI.AUTO]Engineering Sciences [physics]/Automatic Hybrid Monte Carlo symbols.namesake [SPI.AUTO] Engineering Sciences [physics]/Automatic Control and Systems Engineering Statistics Dynamic Monte Carlo method symbols Applied mathematics Monte Carlo method in statistical physics Monte Carlo integration atmospheric dispersion Quasi-Monte Carlo method interval analysis Mathematics Monte Carlo molecular modeling Risk assessment |
| Zdroj: | 15th Symposium Information Control Problems in Manufacturing INCOM2015 15th Symposium Information Control Problems in Manufacturing INCOM2015, May 2015, Ottawa, Canada |
| Popis: | International audience; In this paper, an Advanced Monte Carlo Method based on interval analysis approachand Monte Carlo simulation is proposed in order to propagate uncertainties in an atmosphericdispersion model. The purpose is to compute with accuracy the geographical region in whichthe concentration of the considered toxic gas is less than the threshold of irreversible eects.The problem of uncertainty propagation is tackled in order to assess the risk at the eventof an accident, which may have an important impact on population. The estimation of gasconcentration is based on an eect model associated with the studied dangerous phenomenonwhere some model inputs are known with imprecision. The principle of the proposed methodis to generate random interval supports of model inputs instead of random values in order toincrease accuracy and reduce the sampling size. The Advanced Monte Carlo Method is appliedand compared for estimating uncertainty on the computed region with the classical Monte Carlosimulation. |
| Databáze: | OpenAIRE |
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