Computers and Concrete

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Thickness of shear flow path in RC beams at maximum torsional strength

  • Kim, Hyeong-Gook (Department of Architectural and Urban System Engineering, Kongju National University) ;
  • Lee, Jung-Yoon (School of Civil and Architectural Engineering, Sungkyunkwan University) ;
  • Kim, Kil-Hee (Department of Architectural and Urban System Engineering, Kongju National University)
  • Received : 2022.01.10
  • Accepted : 2022.04.28
  • Published : 2022.05.25
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Abstract

The current design equations for predicting the torsional capacity of RC members underestimate the torsional strength of under-reinforced members and overestimate the torsional strength of over-reinforced members. This is because the design equations consider only the yield strength of torsional reinforcement and the cross-sectional properties of members in determining the torsional capacity. This paper presents an analytical model to predict the thickness of shear flow path in RC beams subjected to pure torsion. The analytical model assumes that torsional reinforcement resists torsional moment with a sufficient deformation capacity until concrete fails by crushing. The ACI 318 code is modified by applying analytical results from the proposed model such as the average stress of torsional reinforcement and the effective gross area enclosed by the shear flow path. Comparison of the calculated and observed torsional strengths of existing 129 test beams showed good agreement. Two design variables related to the compressive strength of concrete in the proposed model are approximated for design application. The accuracy of the ACI 318 code for the over-reinforced test beams improved somewhat with the use of the approximations for the average stresses of reinforcements and the effective gross area enclosed by the shear flow path.

Keywords

Acknowledgement

This work was supported by the Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2019R1A6A1A03032988); This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1A2B3001656); This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2019R1I1A3A01058156); This research was supported by UNDERGROUND CITY OF THE FUTURE program funded by the Ministry of Science and ICT.

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