Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
586424 | Journal of Loss Prevention in the Process Industries | 2013 | 8 Pages |
•Gas dispersion was modeled for different cases of weather condition, release height and release location on plot plan.•The appropriate case of weather condition for dispersion modeling in order to place gas detector was the cold half-year.•The appropriate case of release height for dispersion modeling in order to place gas detector was the bottom of vessel.•The appropriate case of release location for dispersion modeling in order to place gas detector was the north of vessel.•Gas detectors were placed for an adsorber tower using modeling gas dispersion based on the selected appropriate cases.
To quickly and accurately quantify the material release in process units, gas detectors may be placed according to the results of gas dispersion modeling. DNV's PHAST software is one of the most useful and reliable tools for material dispersion modeling. In this software, fluid dispersion is modeled based on the process conditions, the weather conditions and the specifications of the material release point. However, varying weather conditions throughout the year and the exact determination of the release point on the plot plan and the release elevation are problematic; these issues cause the results to be non-exact and non-integrated. Choosing the most appropriate conditions is challenging. In this paper, a scheme was provided to select the most appropriate conditions for gas dispersion modeling. This scheme approaches modeling based on the worst-case scenario (the situation in which the dispersed gas reaches the detector later in comparison to the other cases). Therefore, different weather conditions, release elevations and release points on the plot plan were modeled for an absorber tower of the Gonbadli Dehydration Unit of the Khangiran Refinery. The worst case of each release condition was then chosen. Finally, gas detectors were placed using the gas dispersion modeling results based on the worst-case scenario.