인공신경망을 이용한 터널 주변 폭파 시 파쇄영역의 빠른 예측에 관한 연구 (A study on the fast prediction of the fragmentation zone using artificial neural network when a blasting occurs around a tunnel)
| Author(s): |
Kwang-Ho You
Seok-Won Jeon |
|---|---|
| Medium: | journal article |
| Language(s): | Korean |
| Published in: | Journal of Korean Tunnelling and Underground Space Association (한국터널지하공간학회 논문집), 2013, n. 2, v. 15 |
| Page(s): | 81-95 |
| DOI: | 10.9711/ktaj.2013.15.2.081 |
| Abstract: | When collapse occurs due to explosion near a tunnel, fragmentation zone should be comprehended quickly to recover the function of the tunnel itself. In this study, a method to interpret explosion behavior and predict the fragmentation zone fast. For this purpose, the various 3D-meshes were generated using SolidWorks and explosion analyses were carried out using AUTODYN. The influence of explosion variables such as source location on fragmentation volume were examined by performing sensitivity analyses. Also, a training database for an artificial neural network analysis had been established and the optimal training model was selected, and the predicted results for fragmentation volume and radius were verified. The suggested method had demonstrated that it could be effective for the fast prediction of fragmentation zone. |
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10394734 - Published on:
04/01/2020 - Last updated on:
16/04/2023
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