International Journal of Hydrogen Energy, Vol.42, No.11, 7721-7730, 2017
3D risk management for hydrogen installations
This paper introduces the 3D risk management (3DRM) concept, with particular emphasis on hydrogen installations (Hy3DRM). The 3DRM framework entails an integrated solution for risk management that combines a detailed site-specific 3D geometry model, a computational fluid dynamics (CFD) tool for simulating flow-related accident scenarios, methodology for frequency analysis and quantitative risk assessment (QRA), and state-of-the-art visualization techniques for risk communication and decision support. In order to reduce calculation time, and to cover escalating accident scenarios involving structural collapse and projectiles, the CFD-based consequence analysis can be complemented with empirical engineering models, reduced order models, or finite element analysis (FEA). The paper outlines the background for 3DRM and presents a proof-of-concept risk assessment for a hypothetical hydrogen filling station. The prototype focuses on dispersion, fire and explosion scenarios resulting from loss of containment of gaseous hydrogen. The approach adopted here combines consequence assessments obtained with the CFD tool FLACS-Hydrogen from Gexcon, and event frequencies estimated with the Hydrogen Risk Assessment Models (HyRAM) tool from Sandia, to generate 3D risk contours for explosion pressure and radiation loads. For a given population density and set of harm criteria, it is straightforward to extend the analysis to include personnel risk, as well as risk-based design such as detector optimization. The discussion outlines main challenges and inherent limitations of the 3DRM concept, as well as prospects for further development towards a fully integrated framework for risk management in organizations. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Keywords:Hydrogen safety;3D risk management;Computational fluid dynamics;Risk communication;Emergency preparedness;Quantitative risk analysis