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2023 | OriginalPaper | Buchkapitel

Numerical Analysis of Precast Shear Wall with Opening and Unspliced Vertical Distribution Bars

verfasst von : Qi Cai, Xiaobin Song, Xuwen Xiao

Erschienen in: Proceedings of The 17th East Asian-Pacific Conference on Structural Engineering and Construction, 2022

Verlag: Springer Nature Singapore

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Abstract

To investigate the effect of opening on the lateral behaviour of precast concrete shear wall with unspliced vertical distribution bars, a series of nonlinear numerical analyses is carried out. Cohesive elements and nonlinear springs are adopted to simulate the joints around the precast wall panel and the steel bars across the joints, respectively. The numerical analysis model was verified based on test results of the lateral behaviour of precast shear wall with unspliced vertical distribution bars. Based on the verified model, parametric studies are carried out for the influence of the opening’s characteristic parameters and the length of the boundary element. The results show that the influence of the area ratio and location of the opening on the lateral behaviour of the precast shear wall is similar to that of cast-in-situ shear walls with openings. Compared with the cast-in-situ shear wall with opening, the load-carrying capacity and stiffness of the precast shear wall similarly decreased with the increasing opening area ratio; and the stiffness of the precast wall decreased up to 47.6%. The wall beneath the window opening can slightly compensate for the weakening effect of the unspliced vertical bars on cracking, but the vertical location of the opening had little effect on the lateral behaviour of the precast shear wall with unspliced vertical distribution bars. Finally, the length of the cast-in-situ boundary elements of the precast shear wall was more influential in the stiffness rather than the load-carrying capacity of the shear walls.

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Metadaten
Titel
Numerical Analysis of Precast Shear Wall with Opening and Unspliced Vertical Distribution Bars
verfasst von
Qi Cai
Xiaobin Song
Xuwen Xiao
Copyright-Jahr
2023
Verlag
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-19-7331-4_51