Stability Evaluation of Slope Based on Global Sensitivity Analysis

• Published in: Complexity (New York, N.Y.) N.Y.), 2024-05, Vol.2024, p.1-14
• Main Authors: Xu, Zhaoxia, Wang, Xiuzhen, Guo, Lu, Yu, Teng
• Format: Article
• Language: English
• Subjects: Algorithms; Cost analysis; Efficiency; Engineering; Exact solutions; Feature selection; Methods; Monte Carlo simulation; Parameter sensitivity; Parameter uncertainty; Polynomials; Probability distribution; Random variables; Safety factors; Sensitivity analysis; Shear strength; Slope stability; Statistical analysis; Variance
• ISSN: 1076-2787; 1099-0526
• DOI: 10.1155/2024/2333859

The uncertainty of parameters will have a significant impact on slope stability, where sensitivity analysis is a commonly used method in uncertainty research. However, traditional sensitivity analysis method costs much computation time. When calculating the sensitivity index of one parameter, all other parameters are taken as fixed values, and the uncertainty of all parameters cannot be considered simultaneously. Therefore, the variance-based and the moment-independent global sensitivity analysis (GSA) methods are both introduced to determine the influence of geotechnical parameters on slope stability in this study. To solve the importance index of GSA, the least angle regression algorithm, the kernel density estimation, and orthogonal polynomial estimation methods are developed to obtain variance-based importance index and the moment-independent importance index, respectively. The proposed methods allow all variables to change simultaneously within their variation range and have high computational efficiency. The results are in good at with those obtained by the variance-based Monte Carlo simulation method, which is considered as the exact solution forobtaining the importance index. The influence of the correlation between the shear strength parameters (c and φ) on the importance index is also studied, which indicates that the negative correlation will have a great impact on the importance index, which in turn affects the safety assessment of slope. Three engineering cases have been studied for engineering application, and the compared results indicate that the impact of the geotechnical parameters uncertainty on the safety factor (Fs) and failure probability (pf) are different. Therefore, the approaches based on GSA which can integrate the Fs with pf will be a promising approach for slope stability evaluation.