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

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..