Debonding of the fiber-reinforced polymer (FRP) reinforcement due to shear stresses is a very significant issue in design of concrete structures. Several experimental and theoretical investigations have been carried out to produce a relationship between the shear bond strength and the governing variables. However, existing empirical models do not provide an accurate prediction due to the complexity of the debonding process. In the present study, group method of data handling (GMDH) network as a novel machine learning approach was employed to predict the externally bond strength between FRP composites and concrete structures. The GMDH model was developed based on a reliable database including 342 experimental tests obtained from literature. The GMDH results were compared to the most common existing equations and also to the regression approaches developed in this study through statistical error parameters. Furthermore, some correction factors for four well-known equations were suggested based on regression approaches to improve their accuracy. Results indicated that the developed GMDH model outperformed the existing equations and also the developed regression-based equations in terms of both accuracy and safety aspects. Finally, parametric and sensitivity analyses were performed for further verification of the developed GMDH model in capturing the underlying physical behaviors of bond strength.
The durability performance of palm oil fuel ash engineered alkali-activated cementitious composite (POFA-EACC) mortar exposed to different acid solutions is assessed in this study. 50 mm cubic specimens used for the study were prepared from 100% POFA, alkali-activator (Na2SiO3(aq)/NaOH(aq)) ratios of 2.5, different molarities (10, 12 and 14 M) of NaOH(aq) and 2% volume fraction of polyvinyl alcohol (PVA) fibres. Specimens were exposed to 10% H2SO4(aq), 10% HNO3(aq) and 10% HCl(aq) at pH of 0.56, 0.52 and 0.42 respectively for 3, 6 and 9 months, with unexposed specimens as control. Small changes in compressive strength were identified with POFA mortar specimens during exposure to H2SO4(aq), while exposure to HNO3(aq) and HCl(aq) greatly reduced the strength of the POFA mortar specimens. The results were supported through microstructural examinations using SEM, while the characterization was done using XRD and FTIR. The high resistance of POFA-EACC mortar to H2SO4(aq) is the contribution received through the formation of gypsum, which hinders the infiltration of more acids into the matrix microstructure.