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Inverse Analysis of Regional In Situ Stress Prediction Based on Multi-Points Measurement and BP Neural Network

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Abstract:

Based on the measurement of in-situ stress and engineering-geological conditions, we built computing models with pre-exerting boundary loads and simulated the regional stress field involved. Boundary loads can be approximately determined by use of the multiple linear regressions, and be further optimized with the artificial neural network. By calculation, the corresponding initial in-situ stress field can reach ideal accuracy. As an example, we inversely analyzed an engineering problem in Chinese Wo-bei mine. The results shows that the simulation can meet the point measurement very well, and the regional-stress estimation may play an important role in engineering.

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Periodical:

Applied Mechanics and Materials (Volume 510)

Pages:

226-231

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.510.226

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Online since:

February 2014

Authors:

Wei Qun Liu*, Ting Song, Yu Shou Li, Shu Fei Zheng, Jing Yang

Keywords:

BP Neural Network (BPNN), In Situ Stress, Inverse Analysis, Multi-Point Measuremnet

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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