Hydrogen/methane explosion loads and their effects on high-performance concrete: A comprehensive review

Abstract

As the global energy sector transitions toward sustainability, hydrogen and natural gas (methane) are emerging as pivotal fuels. However, the explosive nature of these fuels poses substantial risks, highlighting the need for precise explosion-loading predictions and robust blast-resistant infrastructure. Although high-performance concrete (HPC) and ultra-high-performance concrete (UHPC) show promise for such infrastructure, their performance under gaseous explosions remains insufficiently understood. This review consolidated current methods for predicting hydrogen/methane explosion loads and for assessing structural response of HPC/UHPC members. Experimental tests (under unconfined, semi-confined, confined, vented, and congested conditions), empirical models (TNT equivalence, multi-energy), and numerical simulations (ranging from one-step to detailed reaction CFD) were examined. Recent advancements in data-driven prediction, such as machine learning and graph neural networks, show potential for improving prediction speed. Particularly, the SALE method, a computationally efficient approach based on user-defined detonation parameters, demonstrated its ability to model a wide range of gas detonations and structural damage scenarios in hydrocodes like LS-DYNA. Key gaps include the lack of dimensionless predictive models and universal data-driven frameworks for diverse blast scenarios. Future research should focus on improving deflagration-load predictions, expanding experimental and numerical databases, and integrating advanced machine learning techniques with numerical simulations to ensure the resilience and safety of HPC/UHPC systems.