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(사)한국터널지하공간학회

ISSN : 2233-8292

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Vol.15 No.2

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A study on the fast prediction of the fragmentation zone using artificial neural network when a blasting occurs around a tunnel

(사)한국터널지하공간학회 / (사)한국터널지하공간학회, (P)2233-8292; (E)2287-4747
2013, v.15 no.2, pp.81-95


& (2013). A study on the fast prediction of the fragmentation zone using artificial neural network when a blasting occurs around a tunnel. (사)한국터널지하공간학회, 15(2), 81-95.

Abstract

When collapse occurs due to explosion near a tunnel, fragmentation zone should be quickly comprehended to recover the function of the tunnel. In this study, explosion behavior is to be understood and a method is described for a fast prediction of the fragmentation zone. To this end, the various 3D-meshes were made by using SolidWorks and explosion analyses were performed by using AUTODYN. The influence of explosion variables such as explosion location on fragmentation volume was examined by performing sensitivity analyses and analyzing their results. Also, a training database was established for an artificial neural network analysis, the optimal training model was selected, and the predicted results for fragmentation volume and radius were verified. As a result, it was confirmed that the demonstrated mothed in this study could be effectively used for the fast prediction of fragmentation zone.

keywords
Blasting, Tunnel, Artificial neural network, Fragmentation zone, 폭발, 터널, 인공신경망, 파쇄영역

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