Abstract
Hydrogen is pivotal in the transition to a sustainable energy supply. The presence of hydrogen-methane mixtures is increasing as the feasibility of utilizing existing natural gas infrastructure for large-scale hydrogen transportation and distribution. However, recent explosion accidents underscore the need to understand the detonation hazards of hydrogen and methane. Current modelling techniques for hydrogen-methane-air detonations are computationally prohibitive due to extra-fine mesh and time step requirements to solve the chemical reaction coupling within detonation structure. This study presented a generic approach to address these challenges, enabling precise and rapid simulation of hydrogen-methane-air blast profiles within hydrocodes. Modified open-source codes helped bypass the time-consuming implicit coupling of detailed chemical reactions with detonation structure and thermodynamic properties based on Chapman-Jouguet (C-J) theory and equilibrium reactive flow assumption, yielding a 90% reduction in computational time. An empirical model, developed through theoretic calculations, provided C-J parameters for hydrocode input with high accuracy across typical industrial conditions. Then, these C-J parameters were employed in LS-DYNA hydrocode based on modified Jones-Wilkins-Lee (JWL) equation of state (EoS) to simulate the hydrogen-methane-air blast loading. This approach was validated against diverse experimental data, encompassing hydrogen-air, methane-air, and hydrogen-methane-air mixtures, and various fuel concentrations, experimental scales, confinement conditions, and fuel shapes. Although conservative results were observed in unstable detonations near the lower detonable limit, it outperformed traditional CFD methods in both accuracy and efficiency. Furthermore, the use of hydrocodes enables the analysis of blast loading as well as the dynamic behaviour of structures subjected to explosive forces. This approach is easily adaptable to other gaseous detonations beyond hydrogen-methane-air by simply replacing the chemical reaction models, making it a versatile tool across various fields.
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