Application of neuro-fuzzy estimation in prediction of shear bond strength between concrete layers through the efficient laser roughness analyzer

To ensure the monolithic behavior of reinforced concrete composite parts, the bond strength at the interface between concrete layers cast at various ages must be high. Reinforced concrete composite members include precast beams with cast-in-place slabs, bridge decks strengthened by adding a new concrete layer, and repair and strengthening of existing concrete structural members by adding a new concrete layer. in this study, the shear bond strength (SBS) of reinforcing steel on Portland cement and a hybrid cement including slag and Portland cement activated with sodium carbonate is investigated. The pull-out test was used to determine SBS; also a subsequent test data is evaluated using ANFIS, as well as surface classification utilizing a laser roughness analyzer designed particularly to assess the roughness of the concrete substrate. As a result, this research tried to create an in situ non-destructive approach for assessment of concrete surfaces and its influence on shear bond strength measurement of the concrete layers. All test data is analyzed using an adaptive neural fuzzy inference system (ANFIS) to classify the different input variables for determining the shear bond strength between concrete layers using the mean and maximum surface roughness (SR) height parameters Ra and Rt in X and Y direction. ANFIS was used to optimize the process based on five processing parameters. Skillful prediction could play a pivotal role in the optimal conditions during laser cutting process. Based on results, laser speed is the most influential on the Ra in X and Y direction (RMSE: 0.3255, RMSE: 0.6869, respectively). The most influential parameter on the Rt in X direction is laser power (RMSE: 1.5611), while the most influential parameter on the Rt in Y direction is laser speed (RMSE: 2.0781), resulting that the roughness of the substrate surface highly affects the shear bond strength of concrete interfaces.