Title of article :
Soft computing-based approach for capacity prediction of FRP-strengthened RC joints
Author/Authors :
Ilkhani, M.H Faculty of Civil Engineering - Semnan University, Semnan , Naderpour, H Faculty of Civil Engineering - Semnan University, Semnan , Kheyroddin, A Faculty of Civil Engineering - Semnan University, Semnan
Abstract :
Shear failure of RC beam-column joints is a brittle failure that occurs with no
prior warning and induces tremendous damages due to collapse of column and joint before
the connected beam. This paper is focused on one particular method of strengthening the
RC joints, that is, the use of FRP composites as a connifing element. The results of previous
studies have shown that strengthening the RC beam-column joints with FRP composites
could improve their shear capacity. In this study, the data collected from the existing
standards and studies regarding the FRP strengthened RC joints were used to develop an
articifial neural network model to predict the shear strength contribution of FRP jacket.
The developed model was then used to evaluate the role of different parameters in this
contribution and, finally, derive a formula to contribute FRP jacket to the shear strength
of the RC beam-column joints.
Keywords :
RC Joint , FRP , Capacity , ANN
Journal title :
Scientia Iranica(Transactions A: Civil Engineering)