Fast-running model for predicting the blast loads in a confined room

Numerical simulations have been widely employed to predict the blast loads for confined explosions. Although they can provide accurate predictions, high-level computational resources are usually needed. Furthermore, the numerical simulations are often lengthy. To provide a quick response to emergencies and then a quick assessment of blast risks, a fast-running model is proposed in this study to predict the blast loads in a confined room. It is based on the method of images (MOI) and the low altitude multiple burst (LAMB) addition rules. The fast-running model can predict the multiple pressure pulses, which are caused by the multiple reflections of the shock wave from the surfaces of the confined room. Numerical models are developed to predict the internal blast loads. They are validated against the experimental data. After validation, numerical simulations are conducted to provide a reference for the evaluation of the accuracy of the fast-running model. It is shown that reasonable accuracy can be achieved by the fast-running model concerning the overpressure-time history, the arrival time, the first peak overpressure and the maximum impulse. Furthermore, the fast-running model has a significantly lower requirement of hardware resources and exhibits a much higher computational efficiency than the numerical model. The fast-running model provides a very fast and efficient method to predict the internal blast loads. It can be used to eliminate the need for a user to run a numerical simulation to determine the blast loads generated from confined explosions.

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Publication Details

Journal
International Journal of Protective Structures
Published
2025-04-24
DOI
https://doi.org/10.1177/20414196251336763
Citations
1
Primary Topic
Structural Response to Dynamic Loads
Type
article
Field-Weighted Citation Impact
0.95

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article

Fast-running model for predicting the blast loads in a confined room

Yaguang Sui, Long Fang, Mingtao Wu, Weifang Xiao et al.
1 citations
International Journal of Protective Structures
Structural Response to Dynamic Loads
0.95
article

Fast-running model for predicting the blast loads in a confined room

Yaguang Sui, Long Fang, Mingtao Wu, Weifang Xiao, Yunfeng Zhang, Zichao Liu
article en
1 citations

Abstract

Numerical simulations have been widely employed to predict the blast loads for confined explosions. Although they can provide accurate predictions, high-level computational resources are usually needed. Furthermore, the numerical simulations are often lengthy. To provide a quick response to emergencies and then a quick assessment of blast risks, a fast-running model is proposed in this study to predict the blast loads in a confined room. It is based on the method of images (MOI) and the low altitude multiple burst (LAMB) addition rules. The fast-running model can predict the multiple pressure pulses, which are caused by the multiple reflections of the shock wave from the surfaces of the confined room. Numerical models are developed to predict the internal blast loads. They are validated against the experimental data. After validation, numerical simulations are conducted to provide a reference for the evaluation of the accuracy of the fast-running model. It is shown that reasonable accuracy can be achieved by the fast-running model concerning the overpressure-time history, the arrival time, the first peak overpressure and the maximum impulse. Furthermore, the fast-running model has a significantly lower requirement of hardware resources and exhibits a much higher computational efficiency than the numerical model. The fast-running model provides a very fast and efficient method to predict the internal blast loads. It can be used to eliminate the need for a user to run a numerical simulation to determine the blast loads generated from confined explosions.

International Journal of Protective StructuresVol. 17(1)
Tongji University (CN), Northwest Institute of Nuclear Technology (CN)
Major Research Plan
Openalex Percentile: Top 27%
Structural Response to Dynamic Loads
0.95
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