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- Title
Developing soft-computing regression model for predicting bearing capacity of eccentrically loaded footings on anisotropic clay.
- Authors
Sangjinda, Kongtawan; Banyong, Rungkhun; Alzabeebee, Saif; Keawsawasvong, Suraparb
- Abstract
In this investigation, the bearing capacity solution of a strip footing in anisotropic clay under inclined and eccentric load is analyzed using the numerical simulation model. The lower and upper bound finite element limit analysis (FELA) approaches are utilized to establish precise modeling and derive the numerical outcomes of a strip footing’s bearing capacity. All analyses use effective automated adaptive meshes with three iteration stages to enhance the accuracy of the outcomes. The parametric analysis is performed to examine the influence of four dimensionless parameters which are taken into account in this study, namely the anisotropic strength ratio, the dimensionless eccentricity, the load inclination angle, and the adhesion factor to the bearing capacity factor. Furthermore, a new model has been proposed to predict the bearing capacity factor for the calculation of the undrained bearing capacity for footings resting on an anisotropic clay using an advanced data-driven method (MOGA-EPR). The new model takes into account the anisotropy, eccentricity, and inclination of the applied load and could be used with confidence in routine designs of shallow foundations in undrained conditions with the consideration of the anisotropic strengths of clays.
- Subjects
CLAY; SOFT computing; FINITE element method; DATA analysis; COMPUTER simulation
- Publication
Artificial Intelligence in Geosciences, 2023, Vol 4, p68
- ISSN
2666-5441
- Publication type
Article
- DOI
10.1016/j.aiig.2023.05.001