Probabilistic Bearing Capacity Prediction of Square Footings on 3D Spatially Varying Cohesive Soils
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 147, Issue 6
Abstract
The bearing capacity of square and/or rectangular footings in geotechnical foundation designs traditionally is determined based on experimental observations and/or deterministic analysis assuming uniform soil profiles. However, soils are spatially varying, and this spatial variability can significantly affect the bearing capacity of the foundation soils. Probability-based design methods can address this problem explicitly. However, a full three-dimensional (3D) probabilistic simulation, such as that involving the random finite-element method, generally is prohibitive, because it involves numerous Monte Carlo runs of a complicated nonlinear elastoplastic algorithm. This paper developed and validated an approximate analytical method based on local averaging theory and geometric averages of soil properties directly under the footing. It was found that the theoretical prediction of the first two moments of a square footing bearing capacity agrees very well with crude Monte Carlo simulation. The analytical prediction of the probability of a design failure was validated through simulation and can be used directly in reliability-based designs against bearing failure.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The first author appreciates the financial support of the National Natural Science Foundation of China (No. 41807228) and the Fundamental Research Funds for the Central Universities (No. 2652019321).
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Journal of Geotechnical and Geoenvironmental Engineering
Volume 147 • Issue 6 • June 2021
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© 2021 American Society of Civil Engineers.
History
Received: Jan 11, 2020
Accepted: Feb 23, 2021
Published online: Apr 8, 2021
Published in print: Jun 1, 2021
Discussion open until: Sep 8, 2021
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