基于云模型和D-S证据理论的岩溶盾构隧道掌子面稳定性评价

王祥; 陈发达; 吴贤国; 冯宗宝; 陈虹宇

doi:10.13204/j.gyjzG22011206

基于云模型和D-S证据理论的岩溶盾构隧道掌子面稳定性评价

doi: 10.13204/j.gyjzG22011206

1. 贵阳城市轨道交通有限公司, 贵阳 550091;
2. 华中科技大学土木与水利工程学院, 武汉 430074;
3. 南洋理工大学土木工程与环境学院, 新加坡 639798

详细信息

作者简介:
王祥,男,硕士,高级工程师,870852150@qq.com。

通讯作者:
吴贤国,女,教授,wxg0220@126.com。

计量
- 文章访问数: 89
- HTML全文浏览量: 13
- PDF下载量: 5
- 被引次数: 0
出版历程
- 收稿日期: 2022-01-12

Stability Evaluation of Working Faces of Shield Tunnels in Karst Based on Cloud Model and D-S Evidence Theory

1. Guiyang Urban Rail Transit Co., Ltd., Guiyang 550091, China;
2. School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;
3. School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore

摘要

摘要: 岩溶地区盾构掘进过程中,复杂地质环境对隧道掌子面稳定性产生较大影响,进而引发开挖面失稳等安全问题。为准确评价掌子面稳定性,降低施工风险,提出一种基于云模型和D-S证据理论的安全评价方法,考虑影响因素的复杂性,解决评价信息的模糊不确定性及高冲突问题。根据大量工程实践和文献研究,从岩溶、施工以及围岩影响三个方面建立一套掌子面稳定性评价体系和标准。以云模型获取评价指标对于风险等级的关联度,继而转化为基本概率分配,利用D-S证据理论对多源证据信息进行融合和更新,实现掌子面安全风险实时评价,并基于全局敏感度确定敏感性因素。实例应用结果表明:评价段掌子面稳定性等级为Ⅱ级,能够保持相对稳定,与实际施工情况相符。
- 岩溶地区 /
- 盾构隧道 /
- 掌子面稳定性 /
- 云模型 /
- D-S证据理论 /
- 敏感性分析
Abstract: During tunnelling with tunnel boring machines in karst, the complex geological environment has a larger impact on the stability of working faces of tunnels, which would caused risks such as destabilization of working faces. To accurately evaluate the stability of working faces and reduce construction risks, a safety evaluation method based on the cloud model and the D-S evidence theory was proposed to consider the complexity of effect factors, which could solve the problem of fuzzy uncertainty and high conflict of evaluation information. Based on a large number of engineering practices and literature research, a set of stability evaluation systems and criteria for working faces was established from 3 aspects: karst, construction and the influence of surrounding rock. The cloud model was used to obtain the correlation degree of evaluation indexes for risk levels and then transformed into basic probability assignment, and the D-S evidence theory was used to fuse and update the multi-source evidence information to realize the real-time evaluation for safety risk of working faces and determine the sensitivity factors based on the global sensitivity. The results of the practical application indicated that the stability grade for working faces of the evaluated section was Ⅱ and could keep relative stability, that was consistent with the actual construction situation.
- karst /
- shield tunnel /
- stability of working face /
- cloud model /
- D-S evidence theory /
- sensitivity analysis

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参考文献(27)

[1]	安永林,欧阳鹏博,岳健,等.基于强度折减法的隧道掌子面稳定性及破坏形态[J].矿业工程研究, 2018, 33(1):39-44.
[2]	郭佳奇,陈建勋,陈帆,等.岩溶隧道断续节理掌子面突水判据及灾变过程[J].中国公路学报, 2018, 31(10):118-129.
[3]	王志杰,高靖遥,张鹏,等.基于突变理论的高压岩溶隧道掌子面稳定性研究[J].岩土工程学报, 2019, 41(1):95-103.
[4]	王秀英,李凯,王丽娟,等.软弱围岩隧道掌子面极限支护压力研究[J].铁道学报, 2019, 41(9):110-117.
[5]	李姝,吕城.考虑孔隙水压力和非线性M-C准则的深埋隧道掌子面稳定性分析[J].公路, 2019, 64(12):322-327.
[6]	杨文钰,郑俊杰,章荣军,等.考虑黏土土性参数与支护压力变异性的盾构掌子面稳定性分析[J].土木与环境工程学报(中英文):2021,6(27):1-11.
[7]	PATERNESI A, SCHWEIGER H F, SCARPELLI G. Numerical analyses of stability and deformation behavior of reinforced and unreinforced tunnel faces[J]. Computers and Geotechnics, 2017, 88:256-266.
[8]	XUE Y G, LI X, QIU D H, et al. Stability evaluation for the excavation face of shield tunnel across the Yangtze River by multi-factor analysis[J]. Geomechanics and Engineering, 2019, 19(3):283-293.
[9]	LI W, ZHANG C P, TAN Z B, et al. Effect of the seepage flow on the face stability of a shield tunnel[J/OL]. Tunnelling and Underground Space Technology, 2021, 112[2022-01-12]. https://doi.org/10.1016/j.tust.2021.103900.
[10]	汤扬屹,吴贤国,陈虹宇,等.基于云模型与D-S证据理论的盾构施工隧道管片上浮风险评价[J].隧道建设(中英文), 2019, 39(12):2011-2019.
[11]	邢晓敏,徐海瑞,廖孟柯,等.基于云模型和D-S证据理论的配电终端健康状态综合评估方法[J].电力系统保护与控制, 2021, 49(13):72-81.
[12]	国强,李明松,周凯.基于势距图与改进云模型的多模雷达分选[J].吉林大学学报(工学版), 2022(8):1904-1911.
[13]	高磊,鲍学英,李爱春.基于DSR-云模型的高地温隧道施工安全评价[J].现代隧道技术, 2021, 58(3):43-51 ,78.
[14]	周恩帆,马俊,周永杰,等.一种D-S证据理论的多传感器数据融合算法[J].小型微型计算机系统,2022(43):795-807.
[15]	刘敦文,贾昊燃,周唱晓,等.基于云模型的盾构隧道开挖面稳定性评价[J].北京交通大学学报, 2019, 43(3):43-49.
[16]	吴贤国,王洪涛,何云.基于模糊物元的岩溶隧道开挖稳定性评价[J].中国安全科学学报, 2018, 28(1):99-104.
[17]	周艺.隧道掌子面稳定性分析及其控制技术研究[D].成都:西南交通大学, 2010.
[18]	刘大刚,姚萌,张霄.郑万高铁大断面岩质隧道掌子面稳定性评价及控制措施[J].隧道建设(中英文), 2018, 38(8):1311-1315.
[19]	魏琨.中山中路隧道掌子面稳定性与变形控制技术研究[D].重庆:重庆交通大学, 2014.
[20]	周雪,左忠义,程伟.基于组合赋权云模型的铁路旅客运输安全评价[J].中国安全科学学报, 2020, 30(增刊1):158-164.
[21]	刘英杰,丁静媛,薛智文.基于云模型与PSR模型的长江三角洲水资源承载力评价[J].华北水利水电大学学报(自然科学版), 2021, 42(2):42-49,75.
[22]	姚春桥,王金峰,杨赛,等.基于云模型和改进证据理论的盾构下穿铁路安全风险评价[J].铁道建筑, 2021, 61(5):60-65.
[23]	吴贤国,刘茜,陈虹宇,等.基于模糊贝叶斯证据理论的盾构下穿既有隧道安全风险评价[J].隧道建设(中英文), 2021, 41(5):713-720.
[24]	陶鹏,张洋瑞,李兵,等.基于D-S理论多源信息融合的电气设备故障诊断模型[J].计算机应用与软件, 2021, 38(7):73-79.
[25]	XIE S Y, CHEN Y N, DONG S H, et al. Risk assessment of an oil depot using the improved multi-sensor fusion approach based on the cloud model and the belief Jensen-Shannon divergence[J/OL]. Journal of Loss Prevention in the Process Industries, 2020, 67[2022-01-12]. https://doi.org/10.1016/j.jlp.2020.104214 Get rights and content.
[26]	FENG L Y, ZHANG L M. Assessment of tunnel face stability subjected to an adjacent tunnel[J/OL]. Reliability Engineering&System Safety, 2021, 205[2022-01-12]. https://doi.org/10.1016/j.ress.2020.107228.
[27]	KEYVANFAR A, SHAFAGHAT A, ISMAIL N, et al. Multifunctional retention pond for stormwater management:A decision-support model using Analytical Network Process (ANP) and Global Sensitivity Analysis (GSA)[J/OL]. Ecological Indicators, 2021, 124[2022-01-12]. https://doi.org/10.1016/j.ecolind.2020.107317.