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拉林铁路桑日至加查段三维地应力场反演分析
引用本文:王庆武,巨能攀,杜玲丽,黄健,胡勇.拉林铁路桑日至加查段三维地应力场反演分析[J].岩土力学,2018,39(4):1450-1462.
作者姓名:王庆武  巨能攀  杜玲丽  黄健  胡勇
作者单位:1. 成都理工大学 地质灾害防治与地质环境保护国家重点实验室,四川 成都 610059;2. 西南交通大学 交通运输与物流学院,四川 成都 610031
基金项目:国家创新研究群体科学基金项目资助(No. 41521002);国家自然科学基金资助(No. 41372306)。
摘    要:桑日至加查地区地形陡倾,河谷深切,构造活动强烈,早更新世以来雅鲁藏布江的强烈侵蚀下切作用引起了该区域构造应力的释放和重分布,应力环境极为复杂,地应力场分析对铁路的选线及施工建设具有重要意义。依据雅鲁藏布江沿岸阶地特征对河谷演化规律进行概化,结合工程地质条件建立三维地质力学模型;以实测地应力资料为基础,利用RBF神经网络和地层剥蚀原理相结合的地应力反演方法,计算得到拉林铁路桑日至加查段现今地应力场。结果表明:各测点处地应力计算值与实测值高度吻合,用该方法获得的地应力场是合理可靠的。在此基础上,分析了桑-加峡谷段河谷岸坡及沿岸主要隧道工程地应力场特征,并根据隧道轴线位置主应力量值及方向特征探讨了隧道建设中面临的主要问题。

关 键 词:地应力场  深切河谷  反演分析  RBF神经网络  拉林铁路  
收稿时间:2016-05-04

Three dimensional inverse analysis of geostress field in the Sangri–Jiacha section of Lasa–Linzhi railway
WANG Qing-wu,JU Neng-pan,DU Ling-li,HUANG Jian,HU Yong.Three dimensional inverse analysis of geostress field in the Sangri–Jiacha section of Lasa–Linzhi railway[J].Rock and Soil Mechanics,2018,39(4):1450-1462.
Authors:WANG Qing-wu  JU Neng-pan  DU Ling-li  HUANG Jian  HU Yong
Institution:1. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, Sichuan 610059, China; 2. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
Abstract:The terrain from Sangri to Jiacha is steep with deep-incised valleys and intense tectonic activities. The strong erosion trenching of Yarlung Zangbo River since early Pleistocene has caused release and redistribution of tectonic stress in this region. The stress field here is extremely sophisticated. Geostress field analysis is of great significance to the route selection and construction of railways. This study combines the terrace characteristics alongside the Yarlung Zangbo River to generalize the evolution laws of the river valley and create a 3D geological-mechanical model according to geological conditions. The existing geostress field from Sangri to Jiacha of Lasa-Linzhi railway is then calculated based on the real-tested geostress data and the utilization of the geostress inverting method combining the RBF neural network and the principle of strata denudation. The result shows that the geostress measurements in each testing point are in good consistency with the real-testing values, and the geostress field obtained through this method is reasonable and reliable. On this basis, the stress field features of the river bank slope of Sang-jia canyon section and the major tunnel projects along the valley river bank are analyzed, and the major problems during the tunnel construction are discussed based on the value and direction characteristics of the main stress field at tunnel axis location.
Keywords:geostress field  deep-incised valley  inversion analysis  RBF neural network  Lasa-Linzhi railway  
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