| Title |
Estimation of Bond Strength of Reinforcing Bars in Reinforced Concrete Members Using ANFIS |
| Authors |
Kim, Minsu ; Cho, Hae-Chang ; Lee, Kyung Jin ; Hahm, Kyung Won ; Han, Sun-Jin ; Kim, Kang Su |
| DOI |
http://dx.doi.org/10.5659/JAIK_SC.2016.32.9.27 |
| Keywords |
ANFIS ; Fuzzy ; Bond Strength ; Neuro-Fuzzy ; Reinforced Concrete Member |
| Abstract |
In reinforced concrete members, bond strength of reinforcing bars shall be ensured to resist external forces. The lack of bond strength may lead to failures of the structural members, and thus, an accurate calculation of the bond strength is essential. However, due to its complex mechanism and many influential factors, most bond strength models were empirically formed based on experimental results, and they often do not provide accurate estimation. In this study, therefore, Adaptive Neuro-Fuzzy Inference System (ANFIS) was applied to estimate the bond strength accurately for reinforced concrete members. A total of 439 test data was collected for training and validation of the ANFIS model, and the trained ANFIS model estimated the bond strength very accurately and reflected the effects of key variables without bias. |