This paper presents a methodology for reliability-based design of slopes, taking into account the spatial variability of the strength parameters of the soil material. The objective is evaluation of the optimal slope angle for a given reliability constraint related to the stability of the slope. The corresponding performance function is expressed in terms of the factor of safety, computed by applying a strength reduction technique to a 2-dimensional elasto-plastic finite element model. The optimal slope angle is determined using an inverse reliability optimization algorithm, derived by modifying the Hasofer-Lind Rackwitz-Fiessler method used for the evaluation of the most probable failure point in the first order reliability method, whereby the search space is extended to include the design parameter. The spatial variability of the uncertain strength parameters is represented by a non-Gaussian random field. The underlying Gaussian field is discretized applying an embedded domain approach, whereby the actual domain is embedded in a standard volume and the Karhunen-Loève expansion is applied to the latter. Therefore, the random field discretization remains unchanged throughout the optimization procedure, not being affected by the change of the geometry of the soil profile. A numerical example demonstrates the solution approach and investigates the importance of the spatial variability of the soil material on the optimal slope angle.
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This paper presents a methodology for reliability-based design of slopes, taking into account the spatial variability of the strength parameters of the soil material. The objective is evaluation of the optimal slope angle for a given reliability constraint related to the stability of the slope. The corresponding performance function is expressed in terms of the factor of safety, computed by applying a strength reduction technique to a 2-dimensional elasto-plastic finite element model. The optima...
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