Prediction of Rock Abrasivity Index (RAI) and Uniaxial Compressive Strength (UCS) of Granite Building Stones Using Nondestructive Tests

Rock abrasivity index (RAI) and uniaxial compressive strength (UCS) are two key parameters for assessing abrasivity and durability of building stones, respectively. Direct determination of these parameters is a time-consuming, tedious and costly task. Hence, indirect and nondestructive tests such as P-wave velocity (Vp) and Schmidt hammer rebound (SHR) are good alternative for prediction of RAI and UCS. This study mainly focuses on developing fast and reliable correlations for predicting RAI and UCS of Iranian granite building stones using Vp and SHR. For this purpose, 15 types of commercial granite building stones were collected from different regions of Iran. After preparing the required samples, petrographic studies and physico-mechanical tests were performed. Then, using simple and multiple regression analysis, various empirical correlations for RAI and UCS prediction based on Vp and SHR were developed. The coefficient of determination (R2), the variance account for (VAF), the normalized root mean square error (NRMSE) and the performance index (PI) were calculated to check the prediction performance of the correlations. The results showed that the proposed correlations derived from nonlinear multiple regression have more prediction capability than the others. These correlations can be applied for fast prediction of RAI and UCS with acceptable error for practical applications in building stone industry.