Predictive modeling of hazard radius for refinery hydrogen releases using regression technique. (13th July 2016)

• Record Type: Journal Article
• Authors: Zohdirad, H.; Ebadi, T.; Givehchi, S.
• Is Part Of: International journal of hydrogen energy. Volume 41:Number 26(2016)
• Page Start: 11491
• Page End: 11496
• Publication Date: 2016-07-13
• Subjects: Hazardous area classification -- Hazard radius -- Hole size -- Release pressure -- Regression; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2016.04.005
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: Fundamental safety principle of hazardous area classification study is to avoid ignition of those releases that may occur during the operation of facilities handling flammable fluids. One of the methods for this study is the point source approach. Regarding this approach one can estimate hazard radius due to a release by having hole size and release pressure. However, till now no reference represents hazard radii for the wide range of possible hole sizes and release pressures. The aim of the present study is to propose a predictive model for estimation of hazard radii due to releases of typical refinery hydrogen gas based on hole size and release pressure. In this study, a complete database of hazard radii due to a broad range of hole sizes and release pressures is provided using available discharge and dispersion models. A regression-based model for estimation of hazard radii is developed based on the provided database. Performance investigation of the proposed model shows that the results are reliable with an acceptable standard error. Highlights: A database of hazard radii from the release of refinery hydrogen gas was developed using discharge and dispersion modeling. The behavior of hazard radius was investigated in different hole sizes and release pressures. A regression-based model for estimation of hazard radii was developed based on the provided database. The performance of proposed regression equation was investigated and reported.