Risk quantification framework of hydride-based hydrogen storage systems for light-duty vehicles |
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| Institution: | 1. Institute of Thermal Science and Technology, Shandong University, Jinan 250061, China;2. State Power Investment Corporation Research Institute, Beijing 102209, China;3. The Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China;4. Key Laboratory of Thermal Science and Power Engineering of Ministry of Education, Tsinghua University, Beijing 100084, China;1. IRTES-M3M, UTBM, 90010 Belfort Cedex, France;2. FCellSYS, UTBM, 90010 Belfort Cedex, France;1. School of Chemical Engineering and Materials Science, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul, 06974, South Korea;2. Fire Explosion Research Department, Korea Gas Safety Corporation, Songhakjucheon-ro, Jucheon-myeon, Yeongwol-gun, Gangwon-do, 1467-51, South Korea;1. College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang Province 310027, China;2. Institute of Zhejiang University-Quzhou, Quzhou, Zhejiang Province 324000, China;3. Zhejiang Ocean University, Zhoushan, Zhejiang Province 316022, China |
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| Abstract: | This study aims to develop a quantitative risk assessment (QRA) framework for on-board hydrogen storage systems in light-duty fuel cell vehicles, with focus on hazards from potential vehicular collision affecting hydride-based hydrogen storage vessels. Sodium aluminum hydride (NaAlH4) has been selected as a representative reversible hydride for hydrogen storage. Functionality of QRA framework is demonstrated by presenting a case study of a postulated vehicle collision (VC) involving the onboard hydrogen storage system. An event tree (ET) model is developed for VC as the accident initiating event. For illustrative purposes, a detailed FT model is developed for hydride dust cloud explosion as part of the accident progress. Phenomenologically-driven ET branch probabilities are estimated based on an experimental program performed for this purpose. Safety-critical basic events (BE) in the FT model are determined using conventional risk importance measures. The Latin Hypercube sampling (LHS) technique has been employed to propagate the aleatory (i.e., stochastic) and epistemic (i.e., phenomenological) uncertainties associated with the probabilistic ET and FT models. Extrapolation of the proposed QRA framework and its core risk-informed insights to other candidate on-board reversible and off-board regenerable hydrogen storage systems could provide better understanding of risk consequences and mitigation options associated with employing this hydrogen-based technology in the transportation sector. |
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| Keywords: | Event tree Fault tree On-board reversible Off-board regenerable Dust cloud explosion Importance measures |
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