Human Errors in the Inspection of Hydrogen Refueling Stations: a Bayesian Network Approach

The widespread use of hydrogen as an energy carrier for road transport and industrial applications was indicated as a promising solution for reducing pollutant emissions. The high flammability of this substance and its tendency to permeate and embrittle most structural materials make hydrogen handling and storage inherently challenging. Hence, inspection and maintenance activities are essential to guarantee the components' integrity and fitness for service. However, guidelines for inspecting and maintaining hydrogen refueling stations are still under development. The manufacturer is responsible for indicating the optimal inspection procedures for each facility. The lack of a unified regulatory framework and the limited operational experience with these technologies make human errors a potential cause of undesired events. In this context, the study evaluates the probability of human error during the high-pressure storage system inspection procedures in hydrogen refueling stations. The Petro-HRA methodology has been used to quantify the likelihood of unsafe or inappropriate actions. In addition, a Bayesian Network approach is proposed to investigate the conditional dependencies among human errors and performance shaping factors. The critical analysis of the results allowed the authors to provide recommendations regarding safety procedures that operators can adopt to reduce the likelihood of accidents in the hydrogen industry.