Study on overpressure and seismic waves of large-scale vapor cloud explosions and rapid prediction method

Abstract

The destructive impact of large-scale vapor cloud explosions (VCEs) is significant. Rapidly predicting the overpressure field and seismic wave field generated by such explosions is crucial for assessing their damage effects. To gain a deeper understanding of the characteristics of VCEs, this paper presents an integrated methodology that combines experimental data with numerical simulations to establish a comprehensive computational model for large-scale VCEs. The model further investigates the attenuation characteristics of the overpressure field and the seismic wave field under cylindrical vapor cloud morphologies by varying parameters such as the aspect ratio and the explosion height. Furthermore, a predictive model based on Back Propagation Neural Network (BPNN) is constructed to enable swift estimation of overpressure and seismic wave fields for VCEs under different equivalence of vapor cloud and initial states. The findings of this study hold significant value for improving the safety design standards of fuel storage and transportation systems. Furthermore, by quantifying the characteristics of overpressure and seismic waves, this study provides critical data essential for predicting potential losses associated with accidents.