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Original Articles

Analytical Model for Shear-critical Reinforced Concrete Interior Beam-column Joints

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Pages 1205-1221 | Received 05 May 2017, Accepted 12 Mar 2018, Published online: 06 Feb 2019
 

ABSTRACT

An analytical model based on the strut-and-tie method for predicting the shear strength of reinforced concrete (RC) interior beam–column joints is introduced in this paper. Both contributions from truss and strut mechanisms are included in the analytical model. The contributions of concrete and transverse reinforcements based on EC2 [2004] are incorporated in the truss mechanism, whereas the strut mechanism is calculated based on the effective compressive strength of concrete. The deformation compatibility between the truss and strut mechanisms is also incorporated in the proposed model. The proposed model is validated by comparison with available experimental database. The validated results show a satisfactory correlation between the proposed model and available experimental database. The proposed model is also compared with the NZS 3101 [1998]; ACI 318 [2002]; and Hwang and Lee [2000]’s joint shear strength model and an improved performance is found.

Notations

vjh=

joint shear stress

bj=

effective joint shear width

hc=

column depth

fyh=

yielding strength of joint reinforcement

Ash=

total cross-sectional area of joint reinforcement

fyb=

yielding strength of longitudinal reinforcement in beam

P=

column axial load

Ag=

cross sectional area of columns

k=

size effect factor

ρl=

longitudinal reinforcement ratio of column

dv=

effective depth of column

Asv=

cross-sectional area of transverse joint reinforcement at spacing s

θ=

angle of inclined compression strut

Ktruss=

shear stiffness of the truss mechanisms

Kstrut=

shear stiffness of the strut mechanisms

ρv=

volumetric ratio of transverse reinforcement to concrete

Es=

elastic modulus of steel reinforcement.

Ec=

elastic modulus of concrete

fc=

compressive strength of concrete

Additional information

Funding

The research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under the grant number 107.01-2016.04.

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