Determination of bearing capacity of shallow foundations without using superposition approximation

Seismic Bearing Capacity of Shallow Foundations

Bearing Capacity of Shallow Foundations on Cohesionless Soils: A Random Forest Based Approach

Determining the ultimate bearing capacity (UBC) is vital for design of shallow foundations. Recently, soft computing methods (i.e. artificial neural networks and support vector machines) have been used for this purpose. In this paper, Random Forest (RF) is utilized as a tree-based ensemble classifier for predicting the UBC of shallow foundations on cohesionless soils. The inputs of model are wi...

The Effect of Spatial Variability and Anisotropy of Soils on Bearing Capacity of Shallow Foundations

Naturally occurred soil deposits inherit heterogeneity and anisotropy in their strength properties. The main purpose of this paper is to model the soil stratum with anisotropy consideration and spatially varying undrained shear strength by using random field theory coupled with finite difference numerical analysis to evaluate their effect on the bearing capacity of the shallow foundations. In t...

Bearing Capacity Zoning of Shallow Foundations in District 1 in Shiraz Municipality Using Geographic Information System (GIS)

This research presents the geotechnical zoning map of district 1 in Shiraz municipality with focus on allowable bearing capacity of foundation based on data from 160 boreholes. For this purpose, the mechanical properties are determined according to the results of direct shear, uniaxial, and SPT tests and then safe bearing capacity for strip foundations with widths of 1, 1.5, 2, and 2.5 m, and f...

prediction the ultimate bearing capacity of shallow foundations on the cohesionless soils using m5p model tree

bearing capacity prediction of shallow foundation is one of the most important problems in geotechnical engineering practices, with a wide variety range of methods which have been introduced to forecast it accurately. recently, soft computing methods such as artificial neural networks (anns) and support vector machines (svms) have been used for prediction of the ultimate bearing capacity of sha...