A dynamic risk model to analyze hydrogen infrastructure

Safety management of hydrogen infrastructure is vital for sustainable progress in the hydrogen economy. Accordingly, this paper presents a dynamic and holistic risk model to address some significant shortcomings of the current hydrogen risk analysis models. The hydrogen release scenarios are modeled using the Bow-tie technique integrated with improved D Numbers Theory and Best-Worst Method. This helps to analyze epistemic uncertainty in the prior probabilities of the causation factors and barriers. Subsequently, a Dynamic Bayesian Network (DBN) model is developed to analyze dynamic risk and deal with aleatory uncertainty. The application of the proposed model is demonstrated on a water electrolysis process. The results of the case study provide a better understanding of the causal modeling of accident scenarios, associated evolving risks with uncertainty. The proposed model will serve as a useful tool for the operational safety management of the hydrogen infrastructure or other complex engineering systems. (C) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Automated summary

This paper introduces a dynamic and holistic risk model to address significant shortcomings of current hydrogen risk analysis models, using improved techniques such as Bow-tie and Dynamic Bayesian Network. The model helps analyze uncertainty in factors and barriers while demonstrating its application in a water electrolysis process. The proposed model serves as a useful tool for operational safety management in complex engineering systems.