Risk Evaluation Model of Rockburst in DeepTunnels Based on GA-SVM

摘要：

Rockburst is one of the most important problem during the excavation of deep tunnels. Being a kind of familiar geological hazard in deep tunnel and chamber, rockburst greatly threatens the safety of constructors and equipments. How to predict rockburst accurately is one of the major subjects in geotechnical engineering. In this paper, the main factors of rockburst, such as the maximum tangential stress of the cavern wall, uniaxial compressive strength, uniaxial tensile strength, and the elastic energy index of rock, are taken into account in the analysis as rockburst criterion index, risk evaluation model based on support vector machine(SVM) and genetic algorithm(GA) is built. Furthermore, set the actual tunnel engineering of Riverside Hydropower Station as an example to predict its rockburst after excavation. The comparative analysis and field practical verification prove(proved) that the result of the evaluation model is reliable and has great guiding role for later control rockburst.

关键词： Rockburst Risk evaluation model Deep tunnels Genetic algorithm Support vector machine

作者: LE-WEN ZHANG DAO-HONG QIU SHU-CAI LI ZHEN-NONG TIAN DE-YONG ZHANG HUAI-FENG SUN

作者单位: Geotechnical and Structural Engineering Research Center,Shandong University,Jinan 250061,P.R.China

会议类型: 国际会议

会议名称: 2009 International Symposium on Risk Control and Management of Design,Construction and Operation in Underground Engineering(地下工程设计、施工、运营安全风险控制及管理国际会议 IRCM09)

会议地点: 大连

会议语种:英文

页码: 72-75

在线出版日期: 2009-10-20（万方平台首次上网日期，不代表论文的发表时间）