3D FE Analysis on Settlement of Footing Supported with Rammed Aggregate Pier Group

INTERNATIONAL JOURNAL OF GEOMECHANICS(2018)

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摘要
(c) 2018 American Society of Civil Engineers. The uncertainties involved in the current design of footings supported by rammed aggregate piers (RAPs) have brought about the need to analyze the complete foundation system accurately using the three-dimensional finite-element (3D FE) method and define the settlement improvements used in the footing design. The postconstruction stage of RAPs is considered in the 3D FE modeling by accounting for the unique installation effect of RAPs, the geometrical variation with depth, and the nonlinear behavior of both aggregates and the surrounding soil matrix. An image-processing technique allowing 3D FE modeling of such a complex foundation system was used, and the initial numerical models were validated through back-analysis of the well-known experimental results reported in the literature for a trial RAP. In a parametric study, extension of the numerical analysis to the complete foundation system of a footing supported with a RAP group of reinforced clay was accomplished by considering the mutual interaction between the foundation elements. The effects of such factors as loads, material properties, footing dimensions, RAP spacing, and lengths on the settlement improvements were investigated by considering numerous design configurations and soil conditions. Multiple nonlinear regression was used to develop a settlement model based on the results from the presented 3D FE analysis. This article provides new practical insights into the 3D postconstruction FE modeling of RAPs considering the installation effects. It also demonstrates that the proposed statistical model within the considered limiting values of variables is desirably accurate for predicting the settlement improvements of the footings supported with the end-bearing RAP groups.
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关键词
Footing,Rammed aggregate pier,Image processing,Three-dimensional finite-element modeling,Settlement improvement,Multiple nonlinear regression
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