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工程岩爆灾害判别的RBF-AR耦合模型
引用本文:王羽,许强,柴贺军,刘丽,夏毓超,王晓东.工程岩爆灾害判别的RBF-AR耦合模型[J].吉林大学学报(地球科学版),2013,43(6):1943.
作者姓名:王羽  许强  柴贺军  刘丽  夏毓超  王晓东
作者单位:1.重庆交通大学国际学院,重庆400074; 2.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,成都610059; 3.招商局重庆交通科研设计院有限公司,重庆400067
基金项目:交通部建设科技项目;地质灾害防治与地质环境保护国家重点实验室开放基金
摘    要:岩爆是深部高地应力区地下岩体工程中的主要工程地质灾害之一,其发生及烈度预测是一个复杂的不确定系统问题。为了有效预测和判别深部工程岩爆灾害,在总体考虑岩爆各影响因素的基础上,选取地下工程中岩体完整性指数、岩石单轴抗压强度、岩石单轴抗拉强度、围岩最大切向应力、围岩抗压强度与其抗拉强度的比值、围岩切向应力与围岩抗压强度比值、弹性能量指数、岩爆倾向性指数作为岩爆预测的评判指标,提出了一种基于非线性参数优化的RBF-AR岩爆预测模型。在终南山隧道竖井岩爆判别中,利用RBF-AR法进行计算,计算结果与实际情况完全一致,表明该模型在岩爆预测中的可行性和有效性。

关 键 词:隧道  岩爆  通风竖井  RBF-AR模型  围岩  
收稿时间:2013-04-15

Rock Burst Prediction in Deep Shaft Based on RBF-AR Model
Wang Yu,Xu Qiang,Chai Hejun,Liu Li,Xia Yuchao,Wang Xiaodong.Rock Burst Prediction in Deep Shaft Based on RBF-AR Model[J].Journal of Jilin Unviersity:Earth Science Edition,2013,43(6):1943.
Authors:Wang Yu  Xu Qiang  Chai Hejun  Liu Li  Xia Yuchao  Wang Xiaodong
Institution:1.International College ofChongqing Jiaotong Uuniversity,Chongqing400074,China;
2.State Key Laboratory of Geohazard Prevention and Geoenvironment Protection,Chengdu University of Technology, Chengdu610059,China;
3.Chongqing Communications Research and Design Institute,China Merchants,Chongqing400067,China
Abstract:Rock burst is one of the main engineering geological hazards of underground rock engineering in deep zone with high ground stresses. The prediction of rock burst intensity is a complex systematic problem of uncertainty. In order to predict the occurrence of rock burst in tunnel engineering, based on consideration of all rock burst factors, selecting several factors as the judging indexes of rock burst such as the integrity index of the rock mass, uniaxial compressive strength of surrounding rock, rock uniaxial tensile strength of rock, maximal tangential stress of rock, the ratio of uniaxial compressive strength and uniaxial tensile strength of rock, the ratio of surrounding maximal tangential stress and uniaxial compressive strength of rock, elasticity energy index and rock burst tendency index, a nonlinear parameter optimization model for rock burst predicting based on RBF-AR was put forward. The RBF-AR model has applied in rock burst predicting calculation of Zhongnanshan tunnel ventilation shaft and the result is very close to the actual situation. It indicates that the model is feasible and effective for rock burst prediction.
Keywords:tunnel  rock burst  ventilation shaft  RBF-AR model  surrounding rock  
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