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An approximate method to identify torsion caused by infill walls through geometric specifications of architectural plans

Noorifard, A ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1016/j.jobe.2020.101799
  3. Publisher: Elsevier Ltd , 2020
  4. Abstract:
  5. A significant part of torsional effects in buildings is due to disregarding the arrangement of infill walls during the design. This is a challenging issue since on the one hand the structural engineers do not usually consider infill walls in modeling a structure, while on the other hand the architects do not pay attention to the seismic behavior of infill walls during architectural design. In this research, an approximate method for identifying the torsion caused by infill walls was proposed to be used at the final stages of basic architectural design, which is based on the geometric specifications of architectural plans and does not require structural specifications. For this purpose, through a typological study of common mid-rise residential buildings in Tehran, 20 buildings were selected, modeled, and analyzed, with 117 different layouts of infill walls, and their torsional behavior was evaluated based on criteria of seismic codes. Finally, according to the obtained results, an approximate method was developed. Evaluation of this method on the analyzed models showed that 96% of them with a risk of torsion were identifiable by this method, and in 98% of models the results were reliable, so the proposed method has a high degree of accuracy. © 2020 Elsevier Ltd
  6. Keywords:
  7. Approximate method ; Infill wall ; Seismic codes ; Torsion ; Approximation theory ; Infill drilling ; Seismic design ; Seismology ; Specifications ; Torsional stress ; Walls (structural partitions) ; Approximate methods ; High degree of accuracy ; Residential building ; Seismic behavior ; Seismic code ; Structural engineer ; Torsional behaviors ; Torsional effect ; Architectural design
  8. Source: Journal of Building Engineering ; Volume 32 , 2020
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S235271022033432X