Bayesian network analysis of domino accidents in high-pressure hydrogen storage systems

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.

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.

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.

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.