Explosion Yield Estimation of Multi-Ground-Medium-Mixed Site
| Autor: | Liangyong Zhang, Weiguo Xiao, Xin Li, Xiaolin Hu, Wenjun Yin, Pengyi Li, Shiying Tang |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Journal of Physics: Conference Series. 2282:012012 |
| ISSN: | 1742-6596 1742-6588 |
| Popis: | The seismo-acoustic analysis approach, which is based on the fusion of acoustic and seismic data, is an extremely effective way of monitoring the yield of explosions over a long distance. To address the problem of estimating the explosion yield at a multi-ground-medium-mixed site (abbreviated as mixed site), this article derives the general explosion yield prediction forms of acoustic model and seismic model, establishes the inversion method for explosion source parameters at mixed site by introducing the ground medium amplification factor, analyzes the inversion accuracy by using experimental data, and discusses the amplification effect and the influence of different scaling relationships. The experimental results indicate that the dispersion of the acoustic impulse relative to the overpressure decreases with distance and the linear relationship of acoustic impulse is better on a logarithmic scale, whereas the vertical component of the first peak of the seismic particle velocity and displacement, as well as the radial-vertical-tangent vector sum, exhibit a good linear variation law over a certain range on the logarithmic scale. The results of the source parameter inversion demonstrate that when the amplification factor is introduced, the inversion of the explosion source parameters of the mixed site has a high accuracy for yield estimation; however, when only single hard-rock media is considered, the inversion of the explosion source parameters produces large errors. The results of the amplification effect and scaling relationship analysis indicate that geological amplification has a substantial effect on the explosion source parameter inversion results, and that the data dispersion degrees of Sachs and KG85 scaling relationships are essentially identical. |
| Databáze: | OpenAIRE |
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