Rock burst risk assessment in deep-buried underground caverns: a novel analysis method
Arabian Journal of Geosciences(2020)
摘要
A rock burst often occurs during the construction period of deep-buried underground caverns. How to predict and prevent it is an urgent problem in underground engineering, especially in large hydropower stations. Combining grey correlation method, principal component analysis (PCA) and cloud theory, a novel analysis method that is proposed to evaluate rock burst. First, seven indices, namely, R c , R c /σ 1 , R c /σ t , σ θ /R c , W et , H and K V , are selected. Considering the relationship between these indices, the grey correlation method is used to analyze these indices and reduce them. According to the correlation coefficients, the five indices, namely, R c /σ 1 , R c /σ t , σ θ /R c , W et and K V, consist of the final evaluated system. Second, the weight of each index is calculated using principal component analysis (PCA). Take into consideration of the ambiguity and randomness of rock burst; the multi-dimensional cloud model is used to evaluate the rock burst level. The proposed model is applied to a case study of the Jiangbian hydropower station to certify the feasibility and effectiveness of the novel method. The results are basically consistent with the actual rock burst level. At last, the selection of the evaluation system and the accuracy of the multi-dimensional cloud model are discussed. This novel method provides a new idea for the risk assessment of rock burst in deep-buried underground caverns.
更多查看译文
关键词
Rock burst,Principal component analysis,Multi-dimensional cloud model,Risk assessment,Underground caverns
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络