An improved efficient adaptive method for large-scale multi-explosives explosion simulations

Abstract

Shock wave caused by a sudden release of high-energy, such as explosion and blast, usually affects a significant range of areas. The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise results is inefficient in terms of computational resource. This is particularly evident when large-scale fluid field simulations are conducted with significant differences in computational domain size. In this work, a variable-domain-size adaptive mesh enlargement (vAME) method is developed based on the proposed adaptive mesh enlargement (AME) method for modeling multi-explosives explosion problems. The vAME method reduces the division of numerous empty areas or unnecessary computational domains by adaptively suspending enlargement operation in one or two directions, rather than in all directions as in AME method. A series of numerical tests via AME and vAME with varying nonintegral enlargement ratios and different mesh numbers are simulated to verify the efficiency and order of accuracy. An estimate of speedup ratio is analyzed for further efficiency comparison. Several large-scale near-ground explosion experiments with single/multiple explosives are performed to analyze the shock wave superposition formed by the incident wave, reflected wave, and Mach wave. Additionally, the vAME method is employed to validate the accuracy, as well as to investigate the performance of the fluid field and shock wave propagation, considering explosive quantities ranging from 1 to 5 while maintaining a constant total mass. The results show a satisfactory correlation between the overpressure versus time curves for experiments and numerical simulations. The vAME method yields a competitive efficiency, increasing the computational speed to 3.0 and approximately 120,000 times in comparison to AME and the fully fine mesh method, respectively. It indicates that the vAME method reduces the computational cost with minimal impact on the results for such large-scale high-energy release problems with significant differences in computational domain size.