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International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP) (12th : 2015)
Uncertainty quantification of heavy gas release over a barrier Omrani, Pejman Shoeibi; O’Mahoney, Tom; Mack, Andreas; Witteveen, Jeroen A. S.
Abstract
In this study a procedure for input uncertainty quantification (UQ) in computational fluid dynamics (CFD) simulations is proposed. The suggested procedure has been applied to a test case. The test case concerns the modeling of a heavy gas release into an atmospheric boundary layer over a barrier. The following uncertain parameters are investigated in their respective intervals: release velocity (18 m/s, 22 m/s), release temperature (270 K, 310 K) and the atmospheric boundary layer velocity (3 m/s, 7 m/s). The Stochastic Collocation (SC) method is used to perform the probabilistic propagation of the uncertain parameters. The uncertainty analysis was performed with two sets of sampling grids (full and sparse grids) for the uncertain parameters. The results show which of the selected uncertain parameters have the largest impact on the dispersed gas plume and the local concentrations in the gas cloud. Additionally, using sparse grids shows potential to reduce the computational effort of the uncertainty analysis.
Item Metadata
Title |
Uncertainty quantification of heavy gas release over a barrier
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Creator | |
Contributor | |
Date Issued |
2015-07
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Description |
In this study a procedure for input uncertainty quantification (UQ) in computational fluid
dynamics (CFD) simulations is proposed. The suggested procedure has been applied to a test case. The
test case concerns the modeling of a heavy gas release into an atmospheric boundary layer over a
barrier. The following uncertain parameters are investigated in their respective intervals: release
velocity (18 m/s, 22 m/s), release temperature (270 K, 310 K) and the atmospheric boundary layer
velocity (3 m/s, 7 m/s). The Stochastic Collocation (SC) method is used to perform the probabilistic
propagation of the uncertain parameters. The uncertainty analysis was performed with two sets of
sampling grids (full and sparse grids) for the uncertain parameters. The results show which of the
selected uncertain parameters have the largest impact on the dispersed gas plume and the local
concentrations in the gas cloud. Additionally, using sparse grids shows potential to reduce the
computational effort of the uncertainty analysis.
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Genre | |
Type | |
Language |
eng
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Notes |
This collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.
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Date Available |
2015-05-22
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivs 2.5 Canada
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DOI |
10.14288/1.0076129
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URI | |
Affiliation | |
Citation |
Haukaas, T. (Ed.) (2015). Proceedings of the 12th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP12), Vancouver, Canada, July 12-15.
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Peer Review Status |
Unreviewed
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Scholarly Level |
Researcher; Other
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DSpace
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Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada