A Study on the Probabilistic Determination of Gas Cloud Characteristics for Explosion Risk Analysis of Offshore Topside Process Area

Abstract

Explosion risk analysis (ERA) is known as one of the dedicated safety studies for offshore installations and its purpose is to evaluate the explosion design accidental loads (DALs) on offshore topside structures and facilities. In general, ERA is more likely to be implemented in a probabilistic manner because it has a problem that needs to deal with a large number of explosion scenarios. In the probabilistic ERA, flammable gas cloud frequency distribution is a kind of intermediate result, which can be obtained by integrating the results of frequency analysis and gas dispersion modeling. In general, the distribution is applied to investigate a certain number of representative explosion scenarios to evaluate exceedance curves, which are commonly used to determine the DALs.

The use of Computational Fluid Dynamics (CFD) to perform the gas dispersion and associated ignition probability modeling has become a trend in recent offshore projects. In most cases, however, the gas cloud frequency distribution has not yet fully benefited from the CFD models due to the high computing costs. Therefore, the distribution is generally derived only using some particular values rather than reflecting the overall results of the CFD simulations. As a matter of fact, the consequences of explosion accidents may vary greatly, depending on variables such as ignition position, gas cloud size, position and shape etc. So far, except for the gas cloud size that can be provided by the gas cloud frequency distribution, the remaining variables are more likely to be determined by engineering judgment and experience. Though this process follows standard guidelines or recommended practices, the determined variables can vary widely depending on engineers.

In view of this, the current research aims to develop a new type of gas cloud frequency distribution that not only reflects the overall results of the CFD simulations performed with the time-varying leak rates, but also provides the information of gas cloud position to investigate the explosion scenarios. With regard to the new distribution, a method of determining the shape of the gas cloud is also proposed in this study. Taking into account all actual gas clouds obtained from the CFD dispersion simulations, it is possible to determine a shaped equivalent gas cloud for each investigated explosion scenario. Details on how to derive the proposed distribution as well as the way to determine the shaped equivalent gas cloud is provided in this thesis. Several case studies are performed, and the limitations of the existing approach is manifested. The case studies have shown that it is important to consider the entire gas clouds shown in the dispersion simulation results and that the position and shape of the gas cloud determined by the proposed method can improve the ERA results.