Prediction of Ultimate Bearing Capacity of Aggregate Pier Reinforced Clay Using Machine Learning

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Sharad Dadhich ◽  
Jitendra Kumar Sharma ◽  
Madhav Madhira
Keyword(s):  
Machine Learning ◽  
Bearing Capacity ◽  
Ultimate Bearing Capacity ◽  
Reinforced Clay

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

Experimental Investigation for Horizontal Ultimate Bearing Capacity and Target Ductility Factor Improvement Results of the RC Column Reinforced by AFL with Damages

2014 ◽  
Vol 488-489 ◽  
pp. 497-500
Author(s):  
You Lin Zou ◽  
Pei Yan Huang
Keyword(s):  
Bearing Capacity ◽  
Ultimate Bearing Capacity ◽  
Test Results ◽  
Rc Columns ◽  
Static Test ◽  
Rc Column ◽  
Ductility Factor ◽  
Secant Stiffness ◽  
Function Relationship ◽  
Reversed Cyclic

Deem test results from the low reversed cyclic loading quasi-static test with 2 RC columns as the basic information of secant stiffness damage of the reference column and take use of the TMS instrument in the test to artificially make the damage percentage of secant stiffness of the RC column as 33%, 50% and 66%, 6 damaged columns in total; reinforce the 6 damaged columns and 2 undamaged ones under the same conditions with AFL, through quasi-static contrast test. Test results show that it is able to effectively boost horizontal ultimate bearing capacity and ductility deformability of the RC columns with AFL for reinforcement; besides, there is a linear function relationship between horizontal ultimate bearing capacity, target ductility factor, and damage percentage of secant stiffness.

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