BEARING CAPACITY OF STRIP FOOTING USING KREY’S METHODS (FRICTION CIRCLE METHOD)

2014 ◽  
Vol 42 (1) ◽  
pp. 112-128
Author(s):  
AbdelAziz Ahmed Ali Senoon
Keyword(s):  
Bearing Capacity ◽  
Circle Method ◽  
Strip Footing

scholarly journals Study on the ultimate bearing capacity of a strip footing influenced by an irregular underlying cavity in karst areas

2021 ◽  
Author(s):  
Lianheng Zhao ◽  
Shan Huang ◽  
Zhonglin Zeng ◽  
Rui Zhang ◽  
Gaopeng Tang ◽  
...  
Keyword(s):  
Bearing Capacity ◽  
Ultimate Bearing Capacity ◽  
Strip Footing ◽  
Karst Areas

scholarly journals Evaluation of Bearing Capacity of Strip Footing Using Random Layers Concept

2015 ◽  
Vol 37 (3) ◽  
pp. 31-39 ◽  
Author(s):  
Marek Kawa ◽  
Dariusz Łydżba
Keyword(s):  
Monte Carlo ◽  
Bearing Capacity ◽  
Failure Mechanism ◽  
Design Theory ◽  
Cohesive Soil ◽  
Probability Of Failure ◽  
Mean Value ◽  
Strip Footing ◽  
Random Field Theory ◽  
The Mean

Abstract The paper deals with evaluation of bearing capacity of strip foundation on random purely cohesive soil. The approach proposed combines random field theory in the form of random layers with classical limit analysis and Monte Carlo simulation. For given realization of random the bearing capacity of strip footing is evaluated by employing the kinematic approach of yield design theory. The results in the form of histograms for both bearing capacity of footing as well as optimal depth of failure mechanism are obtained for different thickness of random layers. For zero and infinite thickness of random layer the values of depth of failure mechanism as well as bearing capacity assessment are derived in a closed form. Finally based on a sequence of Monte Carlo simulations the bearing capacity of strip footing corresponding to a certain probability of failure is estimated. While the mean value of the foundation bearing capacity increases with the thickness of the random layers, the ultimate load corresponding to a certain probability of failure appears to be a decreasing function of random layers thickness.

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