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Academic Journal of Architecture and Geotechnical Engineering, 2019, 1(1); doi: 10.25236/AJAGE.010101.

Failure Characteristics and Seismic Performance Based on Artificial Intelligence and Precast Concrete Shear Walls


Yurong Zhang1,*, Zhengqi Xu2, Chenghao Xu3, Jialu Xu4

Corresponding Author:
Yurong Zhang

1. SC Johnson College of Business, Cornell University, Ithaca, New York, USA
2. St. George’s Senior School, Vancouver, Canada
3. Hangzhou Foreign Languages School, Cambridge-A Level Center, Hangzhou, China
4. Watkinson School, Hartford, Connecticut, USA
*Corresponding author Email: yz845@cornell.edu


In order to study the failure characteristics and seismic performance of precast concrete shear walls, the basic failure processes and phenomena of six shear walls were introduced. The length of the reinforcing bar of the prefabricated shear wall specimens with three confinement anchors was 1 times that of the anchorage length of the steel bar. Through analysis and observation, the failure forms of three prefabricated concrete shear walls of YZ12, YZ16 and YZ20 were bending shear composite failure. Because of the effect of the spiral stirrup, the collapse phenomenon was not found in the concrete core area of the compression zone. At the end of the test, the vertical steel bars were yielded. The results show that the most lateral longitudinal bar of YZ12 was broken at the connection between the ground beam and the prefabricated shear wall specimens. In the late test of three contrast cast-in-situ shear walls, the concrete compression zone was completely crushed and the edge longitudinal reinforcement exposed and showed obvious deformation. Therefore, the binding method of constrained pulp anchorage bar is safe and effective.


Precast concrete, Shear wall, Destructive properties, Shock resistance, artificial intelligence

Cite This Paper

Yurong Zhang, Zhengqi Xu, Chenghao Xu, Jialu Xu. Failure Characteristics and Seismic Performance Based on Artificial Intelligence and Precast Concrete Shear Walls. Academic Journal of Architecture and Geotechnical Engineering (2019) Vol. 1, Issue 1: 1-19. https://doi.org/10.25236/AJAGE.010101.


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