Simplified seismic axial collapse capacity prediction model for moderately compressed reinforced concrete shear walls adjacent to transfer structure in tall buildings. (27th May 2020)

• Record Type: Journal Article
• Authors: Shan, Zhiwei; Looi, Daniel T. W.; Cheng, Bei; Su, Ray K. L.
• Is Part Of: Structural design of tall and special buildings. Volume 29:Number 12(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-05-27
• Subjects: Mohr's stress circle -- out‐of‐plane buckling failure -- RC shear walls -- seismic axial collapse -- shear failure -- transfer structure; Tall buildings -- Design and construction -- Periodicals; Structural design -- Periodicals; 690.1
• DOI: 10.1002/tal.1752
• Languages: English
• ISSNs: 1541-7794

Abstract

Summary: Nonseismically detailed reinforced concrete (RC) shear walls adjacent to transfer structure in tall buildings are found to have short shear spans and designed to hold considerable axial load. In a previous paper, a Modified Mohr's Axial Capacity Model was developed by the authors to estimate the axial collapse of these RC walls in seismic events, which is expressed as an axial load ratio devised based on classical Mohr's circle framework. It was noted that the previous model can be complicated and appears not suitable for direct adoption in engineering design check. Hence, in this paper, a new simplified seismic axial collapse capacity prediction model is formulated to improvise the previous model. This simplified model typifies the practical range of shear wall geometry, concrete strength, steel reinforcement stress and strain and reinforcement ratio. Simplified charts to estimate maximum shear stress are presented for quicker design check. The complex inelastic buckling stress calculation is simplified into graphs and design equations. A knife‐edge feasible solutions zone is defined, expressed as an inequality function of axial‐to‐shear capacity ratio and additional axial stress induced by lateral shear. Recommendations are made based on results obtained from Genetic Algorithm search and further justified by parametric studies.