Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques

Pillar stability is always evaluated using the safety factor (SF), which is defined as the ratio of pillar strength to pillar stress. However, most researchers have estimated pillar stress using the pillar shape ratio (w/h), uniaxial compressive strength (UCS) of the intact rock mass, and pillar dep...

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Main Authors: Li, Chuanqi, Zhou, Jian, Armaghani, Danial Jahed, Li, Xibing
Format: Article
Published: 2021
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Online Access:http://eprints.um.edu.my/26215/
https://doi.org/10.1016/j.undsp.2020.05.005
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Institution: Universiti Malaya
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spelling my.um.eprints.262152022-02-18T03:18:20Z http://eprints.um.edu.my/26215/ Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques Li, Chuanqi Zhou, Jian Armaghani, Danial Jahed Li, Xibing TA Engineering (General). Civil engineering (General) TP Chemical technology Pillar stability is always evaluated using the safety factor (SF), which is defined as the ratio of pillar strength to pillar stress. However, most researchers have estimated pillar stress using the pillar shape ratio (w/h), uniaxial compressive strength (UCS) of the intact rock mass, and pillar depth (H). In this study, the geological strength index (GSI) of hard rock pillars was considered as a new variable for predictive purposes. This index was developed by combining numerical simulation software (i.e., FLAC3D) and a backpropagation neural network (BPNN). A hard rock pillar stability analysis, based on three methods including deterministic method, sensitivity analysis, and Monte Carlo simulation (MCS), was performed. A new formula was proposed to estimate the SF values based on the predicted stress, considering the GSI variable in the deterministic method. The sensitivity analysis indicated that the variables impacting the SF from high to low are UCS, GSI, w/h, and H. In this study, pillar stability was analyzed mainly using the GSI and MCS techniques. The MCS results revealed that the GSI is also a major factor in pillar stability and has a greater effect on weak pillars than on strong ones. Furthermore, a pillar is more likely to be unstable when both the GSI and the UCS are decreased. This study provides several references and procedures for improving the design of stable pillars considering the GSI as an important factor. 2021 Article PeerReviewed Li, Chuanqi and Zhou, Jian and Armaghani, Danial Jahed and Li, Xibing (2021) Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques. Underground Space, 6 (4). pp. 379-395. ISSN 24679674, DOI https://doi.org/10.1016/j.undsp.2020.05.005 <https://doi.org/10.1016/j.undsp.2020.05.005>. https://doi.org/10.1016/j.undsp.2020.05.005 doi:10.1016/j.undsp.2020.05.005
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TA Engineering (General). Civil engineering (General)
TP Chemical technology
spellingShingle TA Engineering (General). Civil engineering (General)
TP Chemical technology
Li, Chuanqi
Zhou, Jian
Armaghani, Danial Jahed
Li, Xibing
Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques
description Pillar stability is always evaluated using the safety factor (SF), which is defined as the ratio of pillar strength to pillar stress. However, most researchers have estimated pillar stress using the pillar shape ratio (w/h), uniaxial compressive strength (UCS) of the intact rock mass, and pillar depth (H). In this study, the geological strength index (GSI) of hard rock pillars was considered as a new variable for predictive purposes. This index was developed by combining numerical simulation software (i.e., FLAC3D) and a backpropagation neural network (BPNN). A hard rock pillar stability analysis, based on three methods including deterministic method, sensitivity analysis, and Monte Carlo simulation (MCS), was performed. A new formula was proposed to estimate the SF values based on the predicted stress, considering the GSI variable in the deterministic method. The sensitivity analysis indicated that the variables impacting the SF from high to low are UCS, GSI, w/h, and H. In this study, pillar stability was analyzed mainly using the GSI and MCS techniques. The MCS results revealed that the GSI is also a major factor in pillar stability and has a greater effect on weak pillars than on strong ones. Furthermore, a pillar is more likely to be unstable when both the GSI and the UCS are decreased. This study provides several references and procedures for improving the design of stable pillars considering the GSI as an important factor.
format Article
author Li, Chuanqi
Zhou, Jian
Armaghani, Danial Jahed
Li, Xibing
author_facet Li, Chuanqi
Zhou, Jian
Armaghani, Danial Jahed
Li, Xibing
author_sort Li, Chuanqi
title Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques
title_short Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques
title_full Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques
title_fullStr Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques
title_full_unstemmed Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques
title_sort stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and monte carlo simulation techniques
publishDate 2021
url http://eprints.um.edu.my/26215/
https://doi.org/10.1016/j.undsp.2020.05.005
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