Research on the Back-Analysis of Tunnel Surrounding Rock Deformation Considering the Deterioration Effect of Surrounding Rock Parameters

IF 1.8 4区工程技术 Q3 ENGINEERING, CIVIL

International Journal of Civil Engineering Pub Date : 2024-08-07 DOI:10.1007/s40999-024-01019-3

Liang Yan, Yawei Zhang, Yunong Li, Qiang Wang, Yongfa Guo

{"title":"Research on the Back-Analysis of Tunnel Surrounding Rock Deformation Considering the Deterioration Effect of Surrounding Rock Parameters","authors":"Liang Yan, Yawei Zhang, Yunong Li, Qiang Wang, Yongfa Guo","doi":"10.1007/s40999-024-01019-3","DOIUrl":null,"url":null,"abstract":"<p>This paper investigates the deformation patterns of surrounding rock in the Xingzishan Tunnel Project, located in Yunnan Province, China, and a method that can respond to the deterioration pattern of the surrounding rock parameters is proposed. The surrounding rock in this project is carbonaceous slate, which possesses the characteristics of anisotropy, and it is hard to detect the mechanical parameters of the rock. A deformation back-analysis method that considers the deterioration effect of the surrounding rock is proposed by using the function approximation and pattern recognition functions of the back propagation (BP) neural network. The fitting equations for the deterioration pattern of the vertical and horizontal elastic moduli <i>E</i> of the surrounding rock are established. Based on the regression prediction of the back propagation (BP) neural network, it is found that the changes in the deformation parameters of the surrounding rock follow certain variation rules within 20 m from the excavation surface. Furthermore, by comparing the deterioration of the surrounding rock in the vertical and horizontal directions, it is considered that the degree of deterioration of the anisotropic surrounding rock varies in different directions. The result is a reference for studying tunnel deformation in anisotropic rocks, and provide a basis for further studies on the deformation mechanisms and control measures of rock surrounding tunnels.</p>","PeriodicalId":50331,"journal":{"name":"International Journal of Civil Engineering","volume":"131 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Civil Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s40999-024-01019-3","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}

引用次数: 0

Abstract

This paper investigates the deformation patterns of surrounding rock in the Xingzishan Tunnel Project, located in Yunnan Province, China, and a method that can respond to the deterioration pattern of the surrounding rock parameters is proposed. The surrounding rock in this project is carbonaceous slate, which possesses the characteristics of anisotropy, and it is hard to detect the mechanical parameters of the rock. A deformation back-analysis method that considers the deterioration effect of the surrounding rock is proposed by using the function approximation and pattern recognition functions of the back propagation (BP) neural network. The fitting equations for the deterioration pattern of the vertical and horizontal elastic moduli E of the surrounding rock are established. Based on the regression prediction of the back propagation (BP) neural network, it is found that the changes in the deformation parameters of the surrounding rock follow certain variation rules within 20 m from the excavation surface. Furthermore, by comparing the deterioration of the surrounding rock in the vertical and horizontal directions, it is considered that the degree of deterioration of the anisotropic surrounding rock varies in different directions. The result is a reference for studying tunnel deformation in anisotropic rocks, and provide a basis for further studies on the deformation mechanisms and control measures of rock surrounding tunnels.

Abstract Image

查看原文本刊更多论文

考虑围岩参数劣化效应的隧道围岩变形反分析研究

本文研究了位于中国云南省的星子山隧道工程围岩的变形规律，并提出了一种能够应对围岩参数劣化规律的方法。该工程围岩为碳质板岩，具有各向异性的特点，岩石力学参数难以检测。利用反向传播（BP）神经网络的函数逼近和模式识别功能，提出了一种考虑围岩劣化效应的变形反向分析方法。建立了围岩垂直和水平弹性模量 E 的劣化模式拟合方程。根据反向传播（BP）神经网络的回归预测，发现在距离开挖面 20 米范围内，围岩变形参数的变化遵循一定的变化规律。此外，通过比较围岩在垂直和水平方向上的劣化程度，可以认为各向异性围岩在不同方向上的劣化程度是不同的。该结果为研究隧道在各向异性岩石中的变形提供了参考，并为进一步研究隧道围岩的变形机制和控制措施提供了依据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

International Journal of Civil Engineering ENGINEERING, CIVIL-

CiteScore

3.90

自引率

5.90%

发文量

审稿时长

15 months

期刊介绍： International Journal of Civil Engineering, The official publication of Iranian Society of Civil Engineering and Iran University of Science and Technology is devoted to original and interdisciplinary, peer-reviewed papers on research related to the broad spectrum of civil engineering with similar emphasis on all topics.The journal provides a forum for the International Civil Engineering Community to present and discuss matters of major interest e.g. new developments in civil regulations, The topics are included but are not necessarily restricted to :- Structures- Geotechnics- Transportation- Environment- Earthquakes- Water Resources- Construction Engineering and Management, and New Materials.