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基于可变模糊集理论的公路隧道岩爆强度风险评估。

The risk assessment of rockburst intensity in the highway tunnel based on the variable fuzzy sets theory.

机构信息

School of Architecture, Nanyang Institute of Technology, Nanyang, 473004, Henan, China.

Henan Planning Design & Research Institute Co. Ltd., Zhengzhou, 450000, Henan, China.

出版信息

Sci Rep. 2023 Mar 23;13(1):4755. doi: 10.1038/s41598-022-27058-1.

DOI:10.1038/s41598-022-27058-1
PMID:36959219
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10036632/
Abstract

Rockbursts have important influences on construction safety, so the risk assessment of rockburst intensity has great significance. Firstly, the depth of the rockburst, the uniaxial compressive strength, the stress concentration coefficients, the brittleness coefficients, and the elastic energy index are selected as the evaluation index. Secondly, an assessment model is developed based on the fuzzy variable theory. And the model is proposed to assess the rockburst intensity in the highway tunnel. Finally, the results demonstrate that the results derived from the proposed model are consistent with the current specifications; the accurate rate comes to 100%. The method can determine the risk level of rockburst intensity and provide an alternative scheme. Hence, the study can accurately present a new approach to assess the rockburst intensity in the future.

摘要

岩爆对施工安全有重要影响,因此对岩爆强度进行风险评估具有重要意义。首先,选取岩爆深度、单轴抗压强度、应力集中系数、脆性系数和弹性能指数作为评价指标。其次,基于模糊变量理论建立评估模型,并将模型应用于公路隧道岩爆强度评估。最后,结果表明,所提出模型的结果与现行规范一致,准确率达到 100%。该方法可以确定岩爆强度的风险等级,提供替代方案。因此,该研究可以为未来准确评估岩爆强度提供一种新方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/26ca8874f13d/41598_2022_27058_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/0b8530adde7f/41598_2022_27058_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/87bc6133f8d9/41598_2022_27058_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/ee8a43fa22e8/41598_2022_27058_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/7c4e26dde6e3/41598_2022_27058_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/3f85af9676f3/41598_2022_27058_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/5d4ecbc2434b/41598_2022_27058_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/99433115d547/41598_2022_27058_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/7f0c7b5493b8/41598_2022_27058_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/26ca8874f13d/41598_2022_27058_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/0b8530adde7f/41598_2022_27058_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/87bc6133f8d9/41598_2022_27058_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/ee8a43fa22e8/41598_2022_27058_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/7c4e26dde6e3/41598_2022_27058_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/3f85af9676f3/41598_2022_27058_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/5d4ecbc2434b/41598_2022_27058_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/99433115d547/41598_2022_27058_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/7f0c7b5493b8/41598_2022_27058_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c904/10036632/26ca8874f13d/41598_2022_27058_Fig9_HTML.jpg

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