Effect of uncertainties in geometry, inter-layer boundary and shear strength properties on the probabilistic stability of a 3D embankment slope

IF 6.5 3区 工程技术 Q1 ENGINEERING, GEOLOGICAL
D. Varkey, M. Hicks, P. Vardon
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引用次数: 5

Abstract

ABSTRACT This paper investigates the influence of three forms of uncertainty on the probabilistic stability of an idealised 3D embankment slope. These are: 1D spatial variability in the external geometry of the slope along its length, 2D spatial variability in the depth of the boundary between the embankment material and the foundation layer, and 3D spatial variability in the shear strength properties of the slope and foundation materials. The relative influence of each uncertainty has been investigated using the random finite element method, based on statistics consistent with a Dutch regional dyke. The results indicate that, for such a structure, the soil spatial variability has a much greater influence than uncertainties relating to embankment geometry and inter-layer boundary. In particular, it is demonstrated that the spatial correlation of material properties along the length of the embankment has a greater influence on the probabilistic characteristics of the embankment slope stability and failure consequence than the spatial correlation of properties perpendicular to it. A worst case scale of fluctuation for the material properties is identified.
几何、层间边界和抗剪强度特性的不确定性对三维路堤边坡概率稳定性的影响
摘要本文研究了三种形式的不确定性对理想化三维路堤边坡概率稳定性的影响。这些是:沿长度方向的边坡外部几何形状的1D空间变异性,路堤材料和基础层之间边界深度的2D空间变异性以及边坡和基础材料抗剪强度特性的3D空间变异性。根据与荷兰区域堤坝一致的统计数据,使用随机有限元方法研究了每个不确定性的相对影响。结果表明,对于这种结构,土壤空间变异性的影响远大于与路堤几何形状和层间边界相关的不确定性。特别是,研究表明,材料特性沿路堤长度的空间相关性对路堤边坡稳定性和破坏后果的概率特征的影响大于垂直于其的特性的空间相关性。确定了材料特性波动的最坏情况尺度。
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来源期刊
CiteScore
8.70
自引率
10.40%
发文量
31
期刊介绍: Georisk covers many diversified but interlinked areas of active research and practice, such as geohazards (earthquakes, landslides, avalanches, rockfalls, tsunamis, etc.), safety of engineered systems (dams, buildings, offshore structures, lifelines, etc.), environmental risk, seismic risk, reliability-based design and code calibration, geostatistics, decision analyses, structural reliability, maintenance and life cycle performance, risk and vulnerability, hazard mapping, loss assessment (economic, social, environmental, etc.), GIS databases, remote sensing, and many other related disciplines. The underlying theme is that uncertainties associated with geomaterials (soils, rocks), geologic processes, and possible subsequent treatments, are usually large and complex and these uncertainties play an indispensable role in the risk assessment and management of engineered and natural systems. Significant theoretical and practical challenges remain on quantifying these uncertainties and developing defensible risk management methodologies that are acceptable to decision makers and stakeholders. Many opportunities to leverage on the rapid advancement in Bayesian analysis, machine learning, artificial intelligence, and other data-driven methods also exist, which can greatly enhance our decision-making abilities. The basic goal of this international peer-reviewed journal is to provide a multi-disciplinary scientific forum for cross fertilization of ideas between interested parties working on various aspects of georisk to advance the state-of-the-art and the state-of-the-practice.
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