Probabilistic evaluation method for the stability of large underground cavern considering the uncertainty of rock mass mechanical parameters: A case study of Baihetan underground powerhouse project

岩体分类 岩土工程 岩体评级 流离失所(心理学) 理论(学习稳定性) 地质学 地质强度指标 蒙特卡罗方法 概率逻辑 地下开采(软岩) 发掘 岩石力学 工程类 计算机科学 煤矿开采 数学 心理学 统计 机器学习 人工智能 心理治疗师 废物管理
作者
Guofeng Liu,Chi Zhou,Kun Feng,Quan Jiang,Shengfeng Li,Han Bao,Ang Li
出处
期刊:Engineering Geology [Elsevier BV]
卷期号:340: 107660-107660 被引量:2
标识
DOI:10.1016/j.enggeo.2024.107660
摘要

For deep large underground cavern projects under complex geological conditions, the determination of rock mass mechanical parameters and stability analysis is fraught with a great deal of uncertainty. This paper proposes a set of methods for estimating rock mass mechanical parameters and probabilistic stability assessment suitable for construction characteristics of large underground caverns. On the one hand, according to the Hoek-Brown criterion and Monte Carlo simulation, a dynamic estimation method for rock mass mechanical parameters is proposed by using Rock Mass Rating (RMR), the uniaxial compressive strength (UCS) of intact rock, and the material constant (mb) as input parameters. On the other hand, considering the uncertainty of rock mass mechanical parameters, a probabilistic evaluation method applicable to the unloading response characteristics of rock mass (including displacement and fracturing zones) around large cavern is put forward, combining point estimation methods and numerical simulation. The proposed methods were applied to an underground powerhouse, with an excavation span of 34 m and height of 88.7 m, at the Baihetan hydropower station in the southwest of China. Based on extensive field investigations and tests, the probability distributions of key rock mass mechanical parameters were obtained. Furthermore, the high sensitivity of input parameters in the H-B criterion for estimating rock mass mechanical parameters were revealed. Through dynamic simulation, the probability distribution of the displacement and fracturing zones in surrounding rock during the layer-by-layer excavation of the cavern was presented. Comprehensive on-site tests showed that the simulated results were in basic agreement with the actual unloading response behavior during the cavern excavation, validating the correctness and applicability of the proposed methods. The study provides a relatively comprehensive approach for estimating rock mass mechanical parameters and stability evaluation in similar underground engineering projects, and also has guiding significance for predicting and preventing engineering rock mass hazards.
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