Application of probabilistic methods to characterize soil variability and their effects on bearing capacity and settlement of shallow foundations: state of the art

2014 ◽  
Vol 8 (4) ◽  
pp. 352-364 ◽  
Author(s):  
Mohammad Kayser ◽  
Sivapalan Gajan
Keyword(s):  
Bearing Capacity ◽  
State Of The Art ◽  
Shallow Foundations ◽  
Probabilistic Methods ◽  
Soil Variability

scholarly journals Analytical and numerical methods for prediction of the bearing capacity of shallow foundations in unsaturated soils

2021 ◽  
Vol 44 (3) ◽  
pp. 1-18
Author(s):  
Sai Vanapalli ◽  
Won-Taek Oh
Keyword(s):  
Numerical Methods ◽  
Bearing Capacity ◽  
Unsaturated Soils ◽  
State Of The Art ◽  
Geotechnical Engineering ◽  
Shallow Foundations ◽  
Saturated Soils ◽  
Engineering Practice ◽  
Total Stress ◽  
Rational Understanding

Bearing capacity of saturated soils can be estimated using effective or total stress approaches extending the concepts proposed by Terzaghi (1943) and Skempton (1948), respectively. Recent studies have shown that similar approaches (i.e., Modified Effective Stress Approach, MESA and Modified Total Stress Approach, MTSA) can be used for interpretation and prediction of the bearing capacity of unsaturated soils by considering the influence of matric suction. However, comprehensive discussion for the application of the MESA and the MTSA in geotechnical engineering practice applications is lacking in the literature. For this reason, in this state-of-the-art paper, the background associated with the MESA and MTSA is first introduced. The analytical and numerical methods available for the prediction of the bearing capacity of unsaturated soils from the literature are revisited. The various available methods are explained by categorizing them into two groups: MESA and MTSA along with their applications using examples. The focus of this state-of-the-art paper is directed towards not only for providing tools for rational understanding but also for better prediction of the bearing capacity of unsaturated soils for extending them in geotechnical engineering practice applications.

Reliability evaluation of shallow foundation bearing capacity on c' ϕ' soils

2000 ◽  
Vol 37 (1) ◽  
pp. 264-269 ◽  
Author(s):  
C Cherubini
Keyword(s):  
Bearing Capacity ◽  
Probabilistic Models ◽  
Correlation Coefficients ◽  
Friction Angle ◽  
Reliability Evaluation ◽  
Shallow Foundations ◽  
Shallow Foundation ◽  
Probabilistic Methods ◽  
Deterministic Models ◽  
Modus Operandi

As our understanding of soils has been steadily improving, the characteristics of its variability can now be highlighted. This has practically changed our geotechnical modus operandi from strictly deterministic models to semiprobabilistic or even strictly probabilistic models. The latter are still to be regarded as experimental and cannot, for the time being, be used routinely in practical working applications. However, the ongoing, continued research and study of these methods combine to develop their worth and bring out any drawbacks. This paper proposes a possible application of probabilistic methods to the study of shallow foundations reliability with respect to their bearing capacity. The study concerns a foundation on a soil characterized by effective cohesion c' and friction angle ϕ', considering possible values of correlation coefficients between them and taking into account the effects of vertical fluctuation scale. The results show that higher reliability indexes are found when correlations between c' and ϕ' are negative and when the fluctuation scale has a minimum value.Key words: reliability, bearing capacity, shallow foundations, friction angle, cohesion.

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.

Bearing capacity improvement of shallow foundations using a trench filled with granular materials and reinforced with geogrids

2021 ◽  
Vol 14 (15) ◽  
Author(s):  
Mohammad Mahdi Hajitaheriha ◽  
Davood Akbarimehr ◽  
Amin Hasani Motlagh ◽  
Hossein Damerchilou
Keyword(s):  
Bearing Capacity ◽  
Granular Materials ◽  
Shallow Foundations ◽  
Capacity Improvement

scholarly journals Application of Artificial Neural Networks for Predicting the Bearing Capacity of Shallow Foundations on Rock Masses

2021 ◽  
Author(s):  
M. A. Millán ◽  
R. Galindo ◽  
A. Alencar
Keyword(s):  
Bearing Capacity ◽  
Analytical Solutions ◽  
Shear Failure ◽  
Numerical Models ◽  
Computational Effort ◽  
Shallow Foundations ◽  
Geological Strength Index ◽  
Rock Masses ◽  
Ann Model ◽  
Artificial Neural

AbstractCalculation of the bearing capacity of shallow foundations on rock masses is usually addressed either using empirical equations, analytical solutions, or numerical models. While the empirical laws are limited to the particular conditions and local geology of the data and the application of analytical solutions is complex and limited by its simplified assumptions, numerical models offer a reliable solution for the task but require more computational effort. This research presents an artificial neural network (ANN) solution to predict the bearing capacity due to general shear failure more simply and straightforwardly, obtained from FLAC numerical calculations based on the Hoek and Brown criterion, reproducing more realistic configurations than those offered by empirical or analytical solutions. The inputs included in the proposed ANN are rock type, uniaxial compressive strength, geological strength index, foundation width, dilatancy, bidimensional or axisymmetric problem, the roughness of the foundation-rock contact, and consideration or not of the self-weight of the rock mass. The predictions from the ANN model are in very good agreement with the numerical results, proving that it can be successfully employed to provide a very accurate assessment of the bearing capacity in a simpler and more accessible way than the existing methods.

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