Random failure mechanism method for assessment of working platform bearing capacity with a linear trend in undrained shear strength

A bearing capacity evaluation for the surface strip foundation on a working platform modelled on a two-layered substrate is considered in the study. The upper layer is assumed as man-made and well-controlled and thus non-variable. The lower layer modelling natural cohesive soil is subjected to spatial variability of undrained shear strength. The random failure mechanism method (RFMM) is used to evaluate the bearing capacity. This approach employs a kinematic assessment of the critical load and incorporates the averaging of three-dimensional (3D) random field along dissipation surfaces that result from the failure mechanism geometry. A novel version of the approach considering an additional linear trend of undrained shear strength in the spatially variable layer is proposed. The high efficiency of the RFMM algorithm is preserved. The influences of foundation length, trend slope in the spatially variable layer, fluctuation scales, and thickness of the homogenous sand layer on the resulting bearing capacity evaluations are analysed. Moreover, for selected cases, verification of the RFMM based assessment obtained using random finite difference method (RFDM) based on 3D analysis is provided. Two types of analyses are performed using RFDM based on associated and non-associated flow rules. For associated flow rule which corresponds to RFMM, the RFMM is conservative and efficient and thus it seems preferable. However, if RFDM employs non-associated flow rule (much lower dilation angle for sand layer), the efficient RFMM is no longer conservative. For this situation, a combined approach that improves the efficiency of the numerical method is suggested. (C) 2021 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting by Elsevier B.V.

Automated summary

This study evaluates the bearing capacity for a surface strip foundation on a two-layered substrate using the random failure mechanism method. Various factors such as foundation length, trend slope, fluctuation scales, and thickness of sand layer are analyzed for their influence on the results. The efficiency of the RFMM algorithm is preserved and a combined approach is suggested for scenarios where RFDM employs non-associated flow rule.