A new approach to the estimation of settlement and ultimate bearing capacity of stone columns supported shallow foundation

2014 ◽  
pp. 541-546 ◽  
Author(s):  
K Ng ◽  
S Tan ◽  
J Sun
Keyword(s):  
Bearing Capacity ◽  
Ultimate Bearing Capacity ◽  
Shallow Foundation ◽  
Stone Columns ◽  
New Approach

scholarly journals Determination of bearing capacity of shallow foundations without using superposition approximation

2003 ◽  
Vol 40 (2) ◽  
pp. 450-459 ◽  
Author(s):  
D Y Zhu ◽  
C F Lee ◽  
K T Law
Keyword(s):  
Bearing Capacity ◽  
Field Method ◽  
Ultimate Bearing Capacity ◽  
Shallow Foundation ◽  
Closed Form Expression ◽  
Safe Side ◽  
Superposition Approximation ◽  
Bearing Capacity Factor ◽  
Rigorous Procedure

The Terzaghi superposition assumption has been widely used to determine the bearing capacity of shallow footings. Although this assumption always errs on the safe side, a rigorous procedure to calculate the bearing capacity is still of engineering value. This paper presents such a procedure that is free from errors as a result of the superposition assumption. It demonstrates that the ultimate bearing capacity can be precisely expressed by the Terzaghi equation, except that the bearing capacity factor Nγ is dependent upon the surcharge ratio. A recently developed numerical method, i.e., the critical slip field method, is used to calculate the modification coefficient for modifying Nγ. It is found that this modification coefficient increases with the surcharge ratio at small values of surcharge ratio and then remains constant for large values of surcharge ratio. However, the errors invoked by the superposition assumption do not exceed 10%. On the basis of numerical calculations, a simple closed-form expression of the modification coefficient is proposed that yields the theoretically rigorous ultimate bearing capacity. In the later part of the paper, errors in bearing capacity calculations owing to the use of conventional procedures are analyzed. It is concluded that the continued use of conventional procedures is justified, but the inherent errors should not be neglected in assessing the performance of shallow foundations.Key words: shallow foundation, strip footing, ultimate bearing capacity, critical slip field.

scholarly journals Influence of Natural Cavities on the Design of Shallow Foundations

2020 ◽  
Vol 10 (3) ◽  
pp. 1119
Author(s):  
Jesús Luis Benito Olmeda ◽  
Javier Moreno Robles ◽  
Eugenio Sanz Pérez ◽  
Claudio Olalla Marañón
Keyword(s):  
Rock Mass ◽  
Bearing Capacity ◽  
Ultimate Bearing Capacity ◽  
Shallow Foundation ◽  
Rock Masses ◽  
Volcanic Origin ◽  
Rock Types ◽  
Geometric Configurations ◽  
Relative Eccentricity ◽  
Decisive Parameter

When inner cavities of significant dimensions exist in natural rocks, problems arise when a shallow foundation for a building, bridge or other structure is builtonthem. Thus, taking one of the most representative cavity geometries in nature, the ellipsoidal horizontal shape, the main objective of this study is to obtain the ultimate bearing capacity of the foundation with cavities of different sizes and positions, on rock masses with different strengths and deformation characteristics. The study focuses on natural rocks of karst origin (in limestones, dolomites or gypsums) and of volcanic origin. The ultimate bearing capacity is determined relative to a situation without the existence of the cavity for different cavern positions and sizes, rock types (mi), strengths (UCS), and states (GSI) of the rock mass. The results showed that the most decisive parameter is the relative eccentricity. The influence of the rock type (Hoek’s parameter mi) is, for practical purposes, negligible (lower than 10%). The strength and condition of the rock mass (parameters UCS and GSI) have relatively little influence on the results obtained. This study aims to provide a simple design criteria for universal use, with different geometric configurations and qualities of rock masses that can be used directly without the need for sophisticated calculations by the designer.

Ultimate bearing capacity of shallow foundations on sand with geogrid reinforcement

1993 ◽  
Vol 30 (3) ◽  
pp. 545-549 ◽  
Author(s):  
M.T. Omar ◽  
B.M. Das ◽  
V.K. Puri ◽  
S.C. Yen
Keyword(s):  
Bearing Capacity ◽  
Key Words ◽  
Model Test ◽  
Ultimate Bearing Capacity ◽  
Shallow Foundations ◽  
Shallow Foundation ◽  
Laboratory Model ◽  
Critical Depth ◽  
Test Results ◽  
Laboratory Model Test

Laboratory model test results for the ultimate bearing capacity of strip and square foundations supported by sand reinforced with geogrid layers have been presented. Based on the model test results, the critical depth of reinforcement and the dimensions of the geogrid layers for mobilizing the maximum bearing-capacity ratio have been determined and compared. Key words : bearing capacity, geogrid, model test, reinforced sand, shallow foundation.

Analysis of Earth Pressure for Retaining Wall and Ultimate Bearing Capacity for Shallow Foundation by Variational Method

2004 ◽  
Vol 20 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Lai-Yun Wu ◽  
Yi-Feng Tsai
Keyword(s):  
Variational Method ◽  
Bearing Capacity ◽  
Governing Equation ◽  
Virtual Work ◽  
Retaining Wall ◽  
Earth Pressure ◽  
Ultimate Bearing Capacity ◽  
Shallow Foundation ◽  
Rupture Surface ◽  
Transversality Conditions

AbstractApplying the principle of virtual work, the slice element method, and the variational method proposed in this paper, one can derive the governing equation and transversality conditions for the rupture surface of a sliding mass of retaining wall and shallow foundation under several external conditions. The governing equation, transversality, and boundary conditions can be solved by the finite difference method (FDM) proposed in this paper, so that the rupture surface and its associated earth pressure acting on the retaining wall or the ultimate bearing capacity acting on the foundation can be determined effectively. By comparison of our results with those of some well known earth pressure and bearing capacity estimating methods, it can be concluded that determining the earth pressure on a retaining wall or the ultimate bearing capacity of a shallow foundation by using the variational method and FDM proposed in this paper, a logical and reasonable result can be obtained without the necessity of guessing the rupture surface.

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.

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