Abstract
During the investigation of terrorist attacks and other intentional explosion events, it is important to grasp the depth of a burst and the mass of the explosive used in attacks as soon as possible. The above explosion information can be rapidly obtained from the crater generated by blast waves through examining the location and dimensions of the crater. First, a brief review of methods for crater size prediction is presented. Then a series of explosion experiments under the ground or on the soil surface are conducted with different amounts of explosive. We propose the inverse analysis method of the feature parameters of explosive sources based on the crater sizes. Finally, in order to validate the inverse analysis method and prove its ability to model the non-linear relationship between crater dimensions and feature parameters of explosive sources, we compare the modeling results with the results calculated with empirical equations and the experimental results, respectively. The mass of the explosives obtained with Generalized Regression Neural Network was consistent with that used in the experiments in the soils.
Original language | English |
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Pages (from-to) | 27-35 |
Number of pages | 9 |
Journal | Shock Waves |
Volume | 27 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2017 |
Keywords
- Craters
- Explosive source
- Generalized regression neural network
- Inverse analysis
- Soil