(57bt) Analyzing Gas Detection Coverage By Employing Dispersion Model Results
AIChE Spring Meeting and Global Congress on Process Safety
2017
2017 Spring Meeting and 13th Global Congress on Process Safety
Global Congress on Process Safety
GCPS Poster Session
Monday, March 27, 2017 - 5:00pm to 7:00pm
President and CEO
Kenexis
+1 (614) 451-7031
Abstract
Quantitative risk analysis tool application to the problem of gas detection coverage estimation is increasing in adoption, and the detail of the analysis is continually improving. Gas detector placement is moving from a imperfect heuristic art to a systematic engineering task. This paper will provide a discussion of how gas detector coverage, as defined in the ISA 84.00.07 technical report Guidance on the Evaluation of Fire and Gas System Effectiveness is being quantitatively calculated. Specifically, the paper will discuss the mechanics of calculating scenario coverage from the results of dispersion modeling and highlight its accuracy and effectiveness with respect to more simplified methods such as geographic coverage and heuristic techniques.
The paper will begin with a discussion of the creation of the most common dispersion models, Gaussian, from a sufficient set of scenario defining factors, such as process operating conditions and ambient weather. These modeling results will then be manipulated to consider multiple release orientations and their relative frequency, along with consideration of wind directions by modifying the relative directional release frequency based on wind direction frequency. Next a discussion of integration of the risk is presented, discussing accumulation release frequency at all geographic positions based release scenarios present in those locations. Coverage calculation is then described as the determination of which scenarios are detectable given the detector locations relative to locations of released gas clouds. Resulting the calculation of coverage as a fraction of detected scenario frequency over total scenario frequency. After the theory is defined based on Gaussian dispersion model, the paper will discuss the incorporation of more accurate computational fluid dynamics dispersion models. The paper will give an overview of the entire process using a case study of a wellbay in an offshore oil production platform.