Quantification of Uncertainty in CFD Simulation of Accidental Gas Release for O & G Quantitative Risk Assessment

Fabrizio Pappalardo, Alberto Moscatello, Gianmario Ledda, Anna Chiara Uggenti, Raffaella Gerboni, Andrea Carpignano, Francesco Di Maio, Riccardo Mereu and Enrico Zio
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Fabrizio Pappalardo: Department of Energy, Politecnico di Milano, 20156 Milano, Italy
Alberto Moscatello: Department of Energy, Politecnico di Torino, 10141 Torino, Italy
Gianmario Ledda: Department of Energy, Politecnico di Torino, 10141 Torino, Italy
Anna Chiara Uggenti: Department of Energy, Politecnico di Torino, 10141 Torino, Italy
Raffaella Gerboni: Department of Energy, Politecnico di Torino, 10141 Torino, Italy
Andrea Carpignano: Department of Energy, Politecnico di Torino, 10141 Torino, Italy
Francesco Di Maio: Department of Energy, Politecnico di Milano, 20156 Milano, Italy
Riccardo Mereu: Department of Energy, Politecnico di Milano, 20156 Milano, Italy
Enrico Zio: Department of Energy, Politecnico di Milano, 20156 Milano, Italy

Energies, 2021, vol. 14, issue 23, 1-16

Abstract: Quantitative Risk Assessment (QRA) of Oil & Gas installations implies modeling accidents’ evolution. Computational Fluid Dynamics (CFD) is one way to do this, and off-the-shelf tools are available, such as FLACS developed by Gexcon US and KFX developed by DNV-GL. A recent model based on ANSYS Fluent, named SBAM (Source Box Accident Model) was proposed by the SEADOG lab at Politecnico di Torino. In this work, we address one major concern related to the use of CFD tools for accident simulation, which is the relevant computational demand that limits the number of simulations that can be performed. This brings with it the challenge of quantifying the uncertainty of the results obtained, which requires performing a large number of simulations. Here we propose a procedure for the Uncertainty Quantification (UQ) of FLACX, KFX and SBAM, and show its performance considering an accidental high-pressure methane release scenario in a realistic offshore Oil & Gas (O & G) platform deck. The novelty of the work is that the UQ of the CFD models, which is performed relying on well-consolidated approaches such as the Grid Convergence Index (GCI) method and a generalization of Richardson’s extrapolation, is originally propagated to a set of risk measures that can be used to support the decision-making process to prevent/mitigate accidental scenarios.

Keywords: Quantitative Risk Assessment (QRA); Computational Fluid Dynamics (CFD); Uncertainty Quantification; impinging jet; gas release (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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