Discussion on Calculation Formula of Standard Value of Ultimate Bearing Capacity of Single Anti-floating Pile in Technical Standard for Anti-floating of Building Engineering

2021 ◽  
2013 ◽  
Vol 671-674 ◽  
pp. 409-412
Author(s):  
Chun Min Dong ◽  
Ke Dong Guo

To investigate the influence of wire mesh type, wrapped way and stress of column on the behavior of RC square columns, the experiment including an unreinforced column and 7 strengthened columns with the high strength wire mesh mortar were tested. The results were shown that the strength and axial deformation of columns reinforced by high strength wire mesh mortar were enhanced. Finally, the calculation formula for ultimate bearing capacity of the reinforced columns was given based on the test results, which agreed with the tested results well.


2013 ◽  
Vol 351-352 ◽  
pp. 980-985
Author(s):  
Yong Feng Xu ◽  
Wei Tong Guo ◽  
Teng Fei He

Now concrete beams reinforced with near surface mounted FRP bars has been researched at home and abroad. This article research the Bearing capacity of concrete beams reinforced with near surface mounted FRP bars by test, and also, Immunobead binding test, infer the calculation formula of ultimate bearing capacity with near surface mounted some bars base on the the single bar.


2011 ◽  
Vol 101-102 ◽  
pp. 228-231
Author(s):  
Jian Ping Jiang

Based on BP neural network, this paper had a prediction on ultimate bearing capacity of prestressed pipe pile. Taking pile diameter, effective pile length, ultimate average value of friction standard value, ultimate average value of end resistance standard value as influences factors, the prediction model of pile bearing capacity based on BP neural network was obtained. It was found that, the average value of absolute value for the relative error of fitting value of pile bearing capacity compared with the observed value for 70 groups of independent variables training BP neural network model was 3.1498%; And the average value of absolute value for the relative error of prediction value of pile bearing capacity compared with the observed value for 10 groups of independent variables validating BP neural network model was 3.50126% whose precision was better than ANFIS’5.32293%. The following conclusion can be drawn that, the prediction model of ultimate bearing capacity of prestressed pipe pile based on BP neural network is feasible.


2014 ◽  
Vol 578-579 ◽  
pp. 232-235 ◽  
Author(s):  
Yong Mei Qian ◽  
Da Peng Zhao ◽  
Xue Wen Xie

In the paper, the existing unreasonable place of the calculation formula of the bearing capacity of single pile is put forward. Through analyzing the failure mechanism of the soil up and under the Multi-under-reamed, the method for calculating the ultimate bearing capacity of soil around the PEMUR pile can be determined by using the slide-line theory, and the calculation formula of the bearing capacity of single pile of the PEMUR pile is further revised and perfected.


Author(s):  
Lianheng Zhao ◽  
Shan Huang ◽  
Zhonglin Zeng ◽  
Rui Zhang ◽  
Gaopeng Tang ◽  
...  

2014 ◽  
Vol 488-489 ◽  
pp. 497-500
Author(s):  
You Lin Zou ◽  
Pei Yan Huang

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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