考虑水力机械耦合观测的水库滑坡概率回溯分析

IF 5.3 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Yang Xue , Fasheng Miao , Jingze Li , Yiping Wu , Linwei Li
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引用次数: 0

摘要

主要由于土壤固有的不确定性和有限的现场特定数据,精确评估统计参数以描述土壤空间变异性是边坡稳定性概率分析中的一项重大挑战。概率回溯分析被认为是一种有效可靠的技术,它为利用观测数据反演土工材料特性参数提供了一种合理的方法。然而,以往用于斜坡稳定性分析的参数反演研究很少考虑水库滑坡中的水力机械特性耦合问题。本研究提出了一种新颖的综合贝叶斯框架,用于对水库滑坡进行反演分析,其中纳入了水力机械参数的空间变异性。在此框架内,开发了一种低塑性构造模型,用于描述水库边坡的阶梯状变形。通过收集地下水位和地面位移的实地监测数据,获得了饱和渗透系数和剪切强度参数的后验知识。以位于中国三峡库区的麻柳林滑坡为例,通过对空间可变土壤参数的回溯分析和概率稳定性分析,验证了所提出的框架。结果表明,所提出的贝叶斯更新框架显著降低了与土壤参数统计值相关的不确定性,为边坡稳定性概率分析提供了更准确、更合理的更新土壤参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probabilistic back analysis of reservoir landslide considering hydro-mechanical coupled observations
Precisely assessing statistical parameters to characterize spatial soil variability presents a significant challenge in probabilistic slope stability analysis, primarily due to inherent soil uncertainties and limited field-specific data. Probabilistic back analysis, recognized as an effective and reliable technique, offers a rational method for utilizing observational data to invert parameters of geomaterial properties. Nevertheless, previous investigations into parameter inversion for slope stability analysis have seldom considered the coupling of hydro-mechanical characteristics in reservoir landslides. This study proposes a novel integrated Bayesian framework to perform back analysis of reservoir landslides, incorporating the spatial variability of hydro-mechanical parameters. Within this framework, a hypoplastic constitutive model is developed to characterize the step-like deformation of the reservoir slope. The posterior knowledge of the saturated permeability coefficient and shear strength parameters is obtained by collecting field monitoring data of the underground water level and ground displacement. The Maliulin landslide, located in the Three Gorges Reservoir area of China, is adopted as an illustrative example to validate the proposed framework through back analysis of spatially variable soil parameters and probabilistic stability analysis. The results demonstrate that the proposed Bayesian updating framework significantly reduces the uncertainties associated with statistical values of soil parameters, providing more accurate and reasonable updated soil parameters for probabilistic slope stability analysis.
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来源期刊
Computers and Geotechnics
Computers and Geotechnics 地学-地球科学综合
CiteScore
9.10
自引率
15.10%
发文量
438
审稿时长
45 days
期刊介绍: The use of computers is firmly established in geotechnical engineering and continues to grow rapidly in both engineering practice and academe. The development of advanced numerical techniques and constitutive modeling, in conjunction with rapid developments in computer hardware, enables problems to be tackled that were unthinkable even a few years ago. Computers and Geotechnics provides an up-to-date reference for engineers and researchers engaged in computer aided analysis and research in geotechnical engineering. The journal is intended for an expeditious dissemination of advanced computer applications across a broad range of geotechnical topics. Contributions on advances in numerical algorithms, computer implementation of new constitutive models and probabilistic methods are especially encouraged.
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