scholarly journals Prediction of Ultimate Bearing Capacity of Shallow Foundations on Cohesionless Soils: A Gaussian Process Regression Approach

2021 ◽  
Vol 11 (21) ◽  
pp. 10317
Author(s):  
Mahmood Ahmad ◽  
Feezan Ahmad ◽  
Piotr Wróblewski ◽  
Ramez A. Al-Mansob ◽  
Piotr Olczak ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Bearing Capacity ◽  
Gaussian Process Regression ◽  
Ultimate Bearing Capacity ◽  
Shallow Foundations ◽  
Cohesionless Soil ◽  
Unit Weight ◽  
Cohesionless Soils ◽  
Computing Technique ◽  
Theoretical Approaches

This study examines the potential of the soft computing technique—namely, Gaussian process regression (GPR), to predict the ultimate bearing capacity (UBC) of cohesionless soils beneath shallow foundations. The inputs of the model are width of footing (B), depth of footing (D), footing geometry (L/B), unit weight of sand (γ), and internal friction angle (ϕ). The results of the present model were compared with those obtained by two theoretical approaches reported in the literature. The statistical evaluation of results shows that the presently applied paradigm is better than the theoretical approaches and is competing well for the prediction of UBC (qu). This study shows that the developed GPR is a robust model for the qu prediction of shallow foundations on cohesionless soil. Sensitivity analysis was also carried out to determine the effect of each input parameter.

Exact probabilistic solution of two-parameter bearing capacity for shallow foundations

1992 ◽  
Vol 29 (5) ◽  
pp. 867-870 ◽  
Author(s):  
Said M. Easa
Keyword(s):  
Bearing Capacity ◽  
Random Variable ◽  
Friction Angle ◽  
Shallow Foundations ◽  
Cohesionless Soil ◽  
Unit Weight ◽  
Previous Solution ◽  
Probabilistic Solution ◽  
Two Parameter ◽  
Soil Unit

An exact probabilistic solution of the ultimate bearing capacity of cohesionless soil for shallow strip foundations is presented. The solution incorporates two random variables: effective friction angle [Formula: see text] and soil unit weight γ. This solution is an extension of a previous solution in which only [Formula: see text] is considered as a random variable. The exact solution is verified using Monte Carlo simulation and the sensitivity of the solution to the coefficient of variation of the soil unit weight is examined. Key words : probability, reliability, bearing capacity, shallow strip foundations, friction angle, soil unit weight.

Determination of Bearing Capacity of Shallow Foundation Using Soft Computing

2016 ◽  
pp. 292-328
Author(s):  
Jagan J. ◽  
Swaptik Chowdhury ◽  
Pratik Goyal ◽  
Pijush Samui ◽  
Yıldırım Dalkiliç
Keyword(s):  
Bearing Capacity ◽  
Gaussian Process Regression ◽  
Ultimate Bearing Capacity ◽  
Shallow Foundation ◽  
Successful Implementation ◽  
Important Criterion ◽  
Cohesionless Soils ◽  
Minimax Probability Machine Regression ◽  
Learning Machine

The ultimate bearing capacity is an important criterion for the successful implementation of any geotechnical projects. This chapter studies the feasibility of employing Gaussian process regression (GPR), Extreme learning machine (ELM) and Minimax probability machine regression (MPMR) for prediction of ultimate bearing capacity of shallow foundation based on cohesionless soils. The developed models have been compared on the basis of coefficient of relation (R) values (GPR= 0.9625, ELM= 0.938, MPMR= 0.9625). The results show that MPMR is more efficient tool but the models of GPR and ELM also gives satisfactory results.

Determination of Bearing Capacity of Shallow Foundation Using Soft Computing

2016 ◽  
pp. 1590-1626
Author(s):  
Jagan J. ◽  
Swaptik Chowdhury ◽  
Pratik Goyal ◽  
Pijush Samui ◽  
Yıldırım Dalkiliç
Keyword(s):  
Bearing Capacity ◽  
Gaussian Process Regression ◽  
Ultimate Bearing Capacity ◽  
Shallow Foundation ◽  
Successful Implementation ◽  
Important Criterion ◽  
Cohesionless Soils ◽  
Minimax Probability Machine Regression ◽  
Learning Machine

The ultimate bearing capacity is an important criterion for the successful implementation of any geotechnical projects. This chapter studies the feasibility of employing Gaussian process regression (GPR), Extreme learning machine (ELM) and Minimax probability machine regression (MPMR) for prediction of ultimate bearing capacity of shallow foundation based on cohesionless soils. The developed models have been compared on the basis of coefficient of relation (R) values (GPR= 0.9625, ELM= 0.938, MPMR= 0.9625). The results show that MPMR is more efficient tool but the models of GPR and ELM also gives satisfactory results.

scholarly journals Prediction of Ultimate Bearing Capacity of Cohesionless Soils Using Soft Computing Techniques

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
S. Adarsh ◽  
R. Dhanya ◽  
G. Krishna ◽  
R. Merlin ◽  
J. Tina
Keyword(s):  
Bearing Capacity ◽  
Soft Computing ◽  
Ultimate Bearing Capacity ◽  
Support Vector ◽  
Width Ratio ◽  
Cohesionless Soils ◽  
Inference System ◽  
Theoretical Approaches ◽  
Soft Computing Techniques ◽  
Gp Model

This study examines the potential of two soft computing techniques, namely, support vector machines (SVMs) and genetic programming (GP), to predict ultimate bearing capacity of cohesionless soils beneath shallow foundations. The width of footing (), depth of footing (), the length-to-width ratio () of footings, density of soil ( or ), angle of internal friction (), and so forth were used as model input parameters to predict ultimate bearing capacity (). The results of present models were compared with those obtained by three theoretical approaches, artificial neural networks (ANNs), and fuzzy inference system (FIS) reported in the literature. The statistical evaluation of results shows that the presently applied paradigms are better than the theoretical approaches and are competing well with the other soft computing techniques. The performance evaluation of GP model results based on multiple error criteria confirms that GP is very efficient in accurate prediction of ultimate bearing capacity cohesionless soils when compared with other models considered in this study.

Bearing capacity of anisotropic cohesionless soils

1978 ◽  
Vol 15 (4) ◽  
pp. 592-595 ◽  
Author(s):  
G. G. Meyerhof
Keyword(s):  
Shear Strength ◽  
Bearing Capacity ◽  
Ultimate Bearing Capacity ◽  
Shallow Foundations ◽  
Test Results ◽  
Cohesionless Soils ◽  
Inclined Load ◽  
Load Tests

Previous test results of the anisotropic shear strength of cohesionless soils are reviewed. The theory of the ultimate bearing capacity of shallow foundations on homogeneous isotropic soils is extended to anisotropic cohesionless soils. The proposed method of analysis is compared with the results of some load tests on anisotropic sand. An extension of this method to foundations under inclined load is briefly discussed.

scholarly journals Influence of the groundwater level on the bearing capacity of shallow foundations on the rock mass

2021 ◽  
Author(s):  
Ana Alencar ◽  
Rubén Galindo ◽  
Svetlana Melentijevic
Keyword(s):  
Rock Mass ◽  
Bearing Capacity ◽  
Groundwater Level ◽  
Sensitivity Study ◽  
Shallow Foundations ◽  
Unit Weight ◽  
Geological Strength Index ◽  
Strength Index ◽  
Mass Type

AbstractThe presence of the groundwater level (GWL) at the rock mass may significantly affect the mechanical behavior, and consequently the bearing capacity. The water particularly modifies two aspects that influence the bearing capacity: the submerged unit weight and the overall geotechnical quality of the rock mass, because water circulation tends to clean and open the joints. This paper is a study of the influence groundwater level has on the ultimate bearing capacity of shallow foundations on the rock mass. The calculations were developed using the finite difference method. The numerical results included three possible locations of groundwater level: at the foundation level, at a depth equal to a quarter of the footing width from the foundation level, and inexistent location. The analysis was based on a sensitivity study with four parameters: foundation width, rock mass type (mi), uniaxial compressive strength, and geological strength index. Included in the analysis was the influence of the self-weight of the material on the bearing capacity and the critical depth where the GWL no longer affected the bearing capacity. Finally, a simple approximation of the solution estimated in this study is suggested for practical purposes.

scholarly journals Influence of a Thin Horizontal Weak Layer on the Mechanical Behaviour of Shallow Foundations Resting on Sand

Geosciences ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 392
Author(s):  
Maurizio Ziccarelli ◽  
Marco Rosone
Keyword(s):  
Bearing Capacity ◽  
Mechanical Behaviour ◽  
Failure Mechanisms ◽  
Shear Bands ◽  
Ultimate Bearing Capacity ◽  
Shallow Foundations ◽  
Foundation Soil ◽  
Weak Layer ◽  
Geotechnical System ◽  
The Difference

The presence of minor details of the ground, including soil or rock masses, occurs more frequently than what is normally believed. Thin weak layers, shear bands, and slickensided surfaces can substantially affect the behaviour of foundations, as well as that of other geostructures. In fact, they can affect the failure mechanisms, the ultimate bearing capacity of footings, and the safety factor of the geotechnical system. In this research, numerically conducted through Finite Element Code Plaxis 2D, the influence of a horizontal thin weak layer on the mechanical behaviour of shallow footings was evaluated. The obtained results prove that the weak layer strongly influences both the failure mechanism and the ultimate bearing capacity if its depth is lower than two to four times the footing width. In fact, under these circumstances, the failure mechanisms are always mixtilinear in shape because the shear strains largely develop on the weak layer. However, the reduction in the ultimate bearing capacity is a function of the difference between the shear strength of the foundation soil and the layer. The presence of a thin weak layer decreases the ultimate bearing capacity up to 90%. In conclusion, this research suggests that particular attention must be paid during detailed ground investigations to find thin weak layers. Based on the obtained results, it is convenient to increase the soil volume investigation to a depth equal to four times the width of the foundation.

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