Experimental Dataset for Predicting Concrete Compressive Strength Using Ultrasonic Pulse Velocity and Schmidt Rebound Hammer Tests

This dataset contains 208 experimental observations used for predicting the compressive strength of concrete based on non-destructive testing parameters. The dataset was obtained from the experimental database reported in the Ph.D. thesis of Logothetis (1978), entitled “Combination of Three Non-Destructive Methods for the Determination of the Strength of Concrete,” completed at the National Technical University of Athens (NTUA), Athens, Greece. The experimental program involved concrete specimens that were evaluated using ultrasonic pulse velocity (UPV) measurements and Schmidt hammer rebound tests before being subjected to destructive compressive strength testing. Each observation in the dataset includes the following variables: No.: Observation number Vp (km/s): Ultrasonic pulse velocity R: Schmidt hammer rebound number fc (MPa): Experimentally measured concrete compressive strength The complete set of 208 observations was used in the study without generating synthetic data. The dataset was used for the development and evaluation of an artificial neural network model and for deriving an explicit empirical equation for predicting concrete compressive strength. Source: Logothetis, L. A. (1978). Combination of three non-destructive methods for the determination of the strength of concrete. Ph.D. Thesis, National Technical University of Athens, Athens, Greece.