A CFD Based Explosion Risk Analysis Methodology Using Time Varying Release Rates in Dispersion Simulations

Sharad Gupta, Sunny Chan

Journal of Loss Prevention in the Process Industries, Jan 2016

Abstract

A full probabilistic Explosion Risk Analysis (ERA) is commonly used to establish overpressure exceedance curves for offshore facilities. This involves modelling a large number of gas dispersion and explosion scenarios. Capturing the time dependent build up and decay of a flammable gas cloud size along with its shape and location are important parameters that can govern the results of an ERA. Dispersion simulations using Computational Fluid Dynamics (CFD) are generally carried out in detailed ERA studies to obtain these pieces of information. However, these dispersion simulations are typically modelled with constant release rates leading to steady state results. The basic assumption used here is that the flammable gas cloud build up rate from these constant release rate dispersion simulations would mimic the actual transient cloud build up rate from a time varying release rate. This assumption does not correctly capture the physical phenomena of transient gas releases and their subsequent dispersion and may lead to very conservative results. This in turn results in potential over design of facilities with implications on time, materials and cost of a project.

In the current work, an ERA methodology is proposed that uses time varying release rates as an input in the CFD dispersion simulations to obtain the fully transient flammable gas cloud build-up and decay, while ensuring the total time required to perform the ERA study is also reduced. It was found that the proposed ERA methodology leads to improved accuracy in dispersion results, steeper overpressure exceedance curves and a significant reduction in the Design Accidental Load (DAL) values whilst still maintaining some conservatism and also reducing the total time required to perform an ERA study.

This paper has been published in the Journal of Loss Prevention in Process Industry.