Oil & Gas plants are risk-relevant complex facilities for the presence of toxic, flammable and pressurized fluids. Risk assessment is mandatory to guarantee plant sustainability and compliance with directives. For offshore plants characterized by congested spaces, semi-empirical models for accident consequence simulation often result in risk overestimation. This could be avoided through Computational Fluid Dynamics (CFD), which guarantees more accurate results. Complex phenomena and geometries, however, entail large computational efforts that force limiting the number of simulations to explore the accident scenarios. This calls for new approaches able to model and simulate complex congested geometries in affordable time, while achieving keeping the required accuracy of the results. In this context, a novel CFD model based on ANSYS Fluent, named SBAM (Source Box Accident Model), has been proposed by the research group of the SEADOG lab in Politecnico di Torino with the aim of simulating complex environments with good accuracy and reduced computational cost. In this work, the results provided by the SBAM model on an accidental high pressure flammable gas release in a platform, are compared with those provided by other tools and models available in the market, and widely used in industrial applications, such as FLACS developed by Gexcon US and KFX developed by DNV-GL.

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.