Evaluation and monitoring of impact resistance of fiber reinforced concrete by adaptive neuro fuzzy algorithm

Since there is no comprehensive research of the impact resistance of fiber reinforced concrete structure, the main goal of the study was to investigate the most influential parameters for impact resistance of fiber reinforced concrete structure. For such an investigation different parameter were taken into account. For example, the parameters are fly ash, cement ratio, aggregate to binder ratio etc. In order to investigate the impact resistance, beams are created by fiber reinforced concrete and afterwards they are dropped for free fall test. During the test displacement and impact were evaluated based on different impact parameters. In order to investigate the parameters, influence on the impact resistance of the fiber reinforced concrete, neuro fuzzy logic approach was implemented since the approach is suitable for highly nonlinear systems. The neuro fuzzy models are established as predictive approach in order to solve complicated mathematical relations of the impact resistance. Finite element method procedure was performed for dataset extraction for training of neuro-fuzzy networks. Results shown that the combination of fly ash and water is the most influential combination for impact resistance (RMSE = 0.0023) and residual displacement (RMSE = 0.0073) on the fiber reinforced structure. The results could be used in practical applications for resistance loading prediction before experimental procedure.