@article { author = {Ilkhani, M.H. and Naderpour, H. and Kheyroddin, A.}, title = {Soft computing-based approach for capacity prediction of FRP-strengthened RC joints}, journal = {Scientia Iranica}, volume = {26}, number = {5}, pages = {2678-2688}, year = {2019}, publisher = {Sharif University of Technology}, issn = {1026-3098}, eissn = {2345-3605}, doi = {10.24200/sci.2018.20177}, abstract = {Shear failure of the RC beam-column joints is a brittle failure which has no priorwarning and can induce tremendous damages because of collapse of column and joint before theconnected beam. This paper is focused on one particular method of strengthening the RC joints,that is, the use of FRP composites as confining element. The results of previous studies have shownthat strengthening the RC beam-column joints with FRP composites can improve their shearcapacity. In this study, the data collected from the existing standards and studies regarding the FRp strengthened RC joints were used to develop an artificial neural network model for predicting theshear strength contribution of FRP jacket. The developed model was then used to evaluate the roleof different parameters on this contribution, and finally derive a formula for contribution of FRp jacket to the shear strength of the RC beam-column joints.}, keywords = {RC Joint,FRP,Capacity,ANN}, url = {https://scientiairanica.sharif.edu/article_20177.html}, eprint = {https://scientiairanica.sharif.edu/article_20177_705835a5fbe4da66c4233b88466ea75e.pdf} }