Bayesian network analysis of domino accidents in high-pressure hydrogen storage systems
LIU Xin, WANG Bing, CAO Chenxi
Key Laboratory of Smart Manufacturing in Energy Chemical Processes, Ministry of Education, School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
Abstract：[Objective] High-pressure gaseous hydrogen storage systems, such as large-scale hydrogen tank farms and distributed hydrogen refueling stations, are prone to hydrogen leakage, fire, and explosion because of the unique physicochemical properties of hydrogen. These events could set off a series of more serious accidents that would cause domino accidents. This study proposes a Bayesian network (BN)-based analysis method for the assessment of internal domino risk distribution within such systems.[Methods] First, event tree models were established for various leakage scenarios in hydrogen-related facilities. Thereafter, all potential domino accident scenarios within the area were enumerated in calculation using accident consequence assessment models for hydrogen facility leaks. Next, BN models were automatically constructed to describe the propagation of domino accidents for each potential initial accident device. Finally, using BN models to analyze the magnitude and sources of overall risk for these systems, as well as the patterns of accident propagation and leakage scenarios.[Results] The overall risk in hydrogen refueling stations mainly originates from the self-failure risk of compressors and the domino risk of hydrogen storage cylinders; jet fire (JF) and vapor cloud explosion (VCE) contribute 76% and 23.4% to the domino risk of all hydrogen cylinders, respectively. When the storage pressure in hydrogen tank farms is between 2 and 15 MPa, the domino risk comprises >25% of the overall risk, with explosions serving as the predominant accident type resulting in domino accidents. Causal reasoning indicates that a JF from a medium hole is the most probable domino accident scenario for both the hydrogen storage cylinders in the hydrogen refueling stations affected by the JF and the spherical tanks in the hydrogen tank farms affected by the explosion. Diagnostic reasoning for initial accident scenarios indicates that rupture and large-hole leakage of hydrogen spherical tanks and cylinders, respectively, are the most probable cause, provided that a multistage domino accident has occurred.[Conclusions] Regarding the common 2-MPa hydrogen spherical tank employed in Chinese green hydrogen projects, the cumulative self-failure risk and domino risk of all tanks in the tank farms is 3.5×10-5 and 1.88×10-5 a-1, respectively, with the latter accounting for ~35%. In the future, decreasing the storage pressure to 1-1.7 MPa or increasing it to 10-15 MPa might lower the contribution of domino risk to <30% and maintain cumulative self-failure risk at a level of 10-5 a-1. At 70-MPa hydrogen refueling stations, the domino risk to hydrogen cylinders from the compressors and pipeline is ~2.9×10-4 and ~4.4×10-5 a-1, respectively. In the abovementioned hydrogen storage systems, explosions are a notable accident type that can trigger domino accidents. Therefore, the implementation of explosion-suppression measures to decrease the probability of ignition is a key focus for mitigating the overall risk of hydrogen storage systems. Our findings indicate that future quantitative risk assessments for high-pressure hydrogen storage systems should consider the possibility of domino accidents. We believe these results serve as notable references for the establishment of advanced quantitative risk assessment methods customized to high-pressure hydrogen storage systems.
刘鑫, 王冰, 曹晨熙. 高压储氢系统的多米诺事故Bayes网络分析[J]. 清华大学学报（自然科学版）, 2025, 65(5): 833-843.
LIU Xin, WANG Bing, CAO Chenxi. Bayesian network analysis of domino accidents in high-pressure hydrogen storage systems. Journal of Tsinghua University(Science and Technology), 2025, 65(5): 833-843.
[1] ZHANG Z G, SHANG M H. Research on hydrogen leakage and diffusion mechanism in hydrogenation station[J]. Scientific Reports, 2024, 14(1):3363. [2] ZOU L Z, LI B, HAN B, et al. Release of high-pressure hydrogen from type III tank in a fire scenario:Analysis and prediction of jet flame length and thermal response characteristics[J]. Fuel, 2024, 372:132153. [3] 王晓慧.大规模制氢与储氢技术现状及发展方向[J].河南科学, 2024, 42(2):165-172. WANG X H. Present situation and development direction of large-scale hydrogen production and storage technology[J]. Henan Science, 2024, 42(2):165-172.(in Chinese) [4] SUN B H, ZHAO H, DONG X Z, et al. Current challenges in the utilization of hydrogen energy-a focused review on the issue of hydrogen-induced damage and embrittlement[J]. Advances in Applied Energy, 2024, 14:100168. [5] MA Q J, HE Y, YOU J F, et al. Probabilistic risk assessment of fire and explosion of onboard high-pressure hydrogen system[J]. International Journal of Hydrogen Energy, 2024, 50:1261-1273. [6] BIRCH A D, HUGHES D J, SWAFFIELD F. Velocity decay of high pressure jets[J]. Combustion Science and Technology, 1987, 52(1-3):161-171. [7] LOWESMITH B J, HANKINSON G. Large scale high pressure jet fires involving natural gas and natural gas/hydrogen mixtures[J]. Process Safety and Environmental Protection, 2012, 90(2):108-120. [8] LI X F, HECHT E S, CHRISTOPHER D M. Validation of a reduced-order jet model for subsonic and underexpanded hydrogen jets[J]. International Journal of Hydrogen Energy, 2016, 41(2):1348-1358. [9] 王振华,蒋军成,尤飞,等.高压氢气储运设施泄漏喷射火过程预测模型及其验证[J].化工学报, 2021, 72(10):5412-5423. WANG Z H, JIANG J C, YOU F, et al. Prediction model for the process of jet fire induced by the leakage of high-pressure hydrogen storage and transportation facilities and its validation[J]. CIESC Journal, 2021, 72(10):5412-5423.(in Chinese) [10] GROTH K M, HECHT E S. HyRAM:A methodology and toolkit for quantitative risk assessment of hydrogen systems[J]. International Journal of Hydrogen Energy, 2017, 42(11):7485-7493. [11] WANG L, ZHANG J X, WANG H, et al. Hydrogen leakage risk assessment of HECS based on dynamic bayesian network[J]. International Journal of Hydrogen Energy, 2024, 78:256-267. [12] LI Y T, YU L, JING Q. Dynamic risk assessment method for urban hydrogen refueling stations:A novel dynamic Bayesian network incorporating multiple equipment states and accident cascade effects[J]. International Journal of Hydrogen Energy, 2024, 54:1367-1385. [13] ZHANG J X, SHI M H, LANG X S, et al. Dynamic risk evaluation of hydrogen station leakage based on fuzzy dynamic Bayesian network[J]. International Journal of Hydrogen Energy, 2024, 50:1131-1145. [14] KHAKZAD N, KHAN F, AMYOTTE P, et al. Domino effect analysis using bayesian networks[J]. Risk Analysis, 2013, 33(2):292-306. [15] WU X G, HUANG H R, XIE J Y, et al. A novel dynamic risk assessment method for the petrochemical industry using bow-tie analysis and Bayesian network analysis method based on the methodological framework of ARAMIS project[J]. Reliability Engineering&System Safety, 2023, 237:109397. [16] 伍东,宋文华,张茹,等.火电厂氢气储罐火灾爆炸危险性分析[J].消防科学与技术, 2008, 27(11):847-851. WU D, SONG W H, ZHANG R, et al. Analysis on hydrogen-holder fire explosion hazard of thermal power plants[J]. Fire Science and Technology, 2008, 27(11):847-851.(in Chinese) [17] 张迁,刘鑫,王冰,等.复杂风速风向与事件树下储罐区多米诺事故分析.化工进展, 2024:1-20.(2024-04-22). https://link.cnki.net/doi/10.16085/j.issn.1000-6613.2024-0146. ZHANG Q, LIU X, WANG B, et al. Quantitative analysis of domino effects in large tank farms urnder various wind conditions and accident scenarios. Chemical Industry and Engineering Progress, 2024:1-20.(2024-04-22). https://link.cnki.net/doi/10.16085/j.issn.10006613.2024-0146.(in Chinese) [18] WEST M, AL-DOURI A, HARTMANN K, et al. Critical review and analysis of hydrogen safety data collection tools[J]. International Journal of Hydrogen Energy, 2022, 47(40):17845-17858. [19] 国家市场监督管理总局,国家标准化管理委员会.危险化学品生产装置和储存设施外部安全防护距离确定方法:GB/T 37243-2019[S].北京:中国标准出版社, 2019.State Administration for Market Regulation, National Standardization Administration. Determination method of external safety distance for hazardous chemicals production units and storage installations:GB/T 37243-2019[S]. Beijing:China Standard Press, 2019.(in Chinese) [20] 中华人民共和国工业和信息化部.石油化工过程风险定量分析标准:SH/T 3226-2024[S].北京:中国石化出版社, 2024.Ministry of Industry and Information Technology. Standard for quantitative analysis of petrochemical process risk:SH/T 3226-2024[S]. Beijing:China Petrochemical Press, 2024.(in Chinese) [21] UIJT DE HAAG P, ALE B. Guidelines for quantitative risk assessment (Purple book)[M]. The Hague (NL):Committee for the Prevention of Disasters, 2005. [22] AARSKOG F G, HANSEN O R, STR? MGREN T, et al. Concept risk assessment of a hydrogen driven high speed passenger ferry[J]. International Journal of Hydrogen Energy, 2020, 45(2):1359-1372. [23] 袁雄军,朱常龙,任常兴,等.加氢站定量风险分析研究[J].可再生能源, 2012, 30(5):75-79, 83. YUAN X J, ZHU C L, REN C X, et al. Study on quantitative risk analysis of Hydrogen refueling station[J]. Renewable Energy Resources, 2012, 30(5):75-79, 83.(in Chinese) [24] HUANG W, CHEN X W, QIN Y. A simulation method for the dynamic evolution of domino accidents in chemical industrial parks[J]. Process Safety and Environmental Protection, 2022, 168:96-113. [25] ROCOURT X, SOCHET I, PELLEGRINELLI B. Application of the TNO multi-energy and Baker-Strehlow-Tang methods to predict hydrogen explosion effects from small-scale experiments[J]. Journal of Loss Prevention in the Process Industries, 2023, 81:104976. [26] ASSAEL M J, KAKOSIMOS K E. Fires, explosions, and toxic gas dispersions:Effects calculation and risk analysis[M]. Boca Raton:CRC Press, 2010. [27] GROSSEL S S. Guidelines for chemical process quantitative risk analysis:2nd Edition; By Center for Chemical Process Safety; American Institute of Chemical Engineers, New York, NY, 2000, pp. 750[J]. Journal of Loss Prevention in The Process Industries, 2001, 14(5):438-439. [28] COZZANI V, ANTONIONI G, SPADONI G. Quantitative assessment of domino scenarios by a GIS-based software tool[J]. Journal of Loss Prevention in the Process Industries, 2006, 19(5):463-477. [29] WANG X Y, LI B, HAN B, et al. Explosion of high pressure hydrogen tank in fire:Mechanism, criterion, and consequence assessment[J]. Journal of Energy Storage, 2023, 72:108455. [30] QIAN J Y, LI X J, GAO Z X, et al. A numerical study of unintended hydrogen release in a hydrogen refueling station[J]. International Journal of Hydrogen Energy, 2020, 45(38):20142-20152. [31] HE X, KONG D P, YANG G D, et al. Hybrid neural network-based surrogate model for fast prediction of hydrogen leak consequences in hydrogen refueling station[J]. International Journal of Hydrogen Energy, 2024, 59:187-198. [32] 中华人民共和国住房和城乡建设部,国家市场监督管理总局.加氢站技术规范(2021年版):GB 50516-2010[S].北京:中国计划出版社, 2010. Ministry of Housing and Urban Rural Development of the People's Republic of China, State Administration for Market Regulation. Technical code for hydrogen fuelling station (2021 Edition):GB 50516-2010[S]. Beijing:China Planning Publishing House, 2010.(in Chinese) [33] 侯磊,吴守志,刘芳媛,等.油库池火灾多米诺效应定量分析方法及优选[J].中国石油大学学报(自然科学版), 2020, 44(5):122-130. HOU L, WU S Z, LIU F Y, et al. Quantitative analysis methods and optimization of domino effect triggerred by pool fire in tank farms[J]. Journal of China University of Petroleum (Edition of Natural Science), 2020, 44(5):122-130.(in Chinese)
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