Multicriteria decision-making analysis based methodology for predicting carbonate rocks' uniaxial compressive strength

Uniaxial compressive strength (UCS) deals with materials' to ability to withstand axially-directed pushing forces and especially considered to be rock materials' most important mechanical properties. However, the UCS test is an expensive, very time-consuming test to perform in the laboratory and requires high-quality core samples having regular geometry. Empirical equations were thus proposed for predicting UCS as a function of rocks' index properties. Analytical hierarchy process and multiple regression analysis based methodology were used (as opposed to traditional linear regression methods) on data-sets obtained from carbonate rocks in NE Turkey. Limestone samples ranging from Devonian to late Cretaceous ages were chosen; travertine-onyx samples were selected from morphological environments considering their surface environmental conditions. Test results from experiments carried out on about 250 carbonate rock samples were used in deriving the model. While the hierarchy model focused on determining the most important index properties affecting on UCS, regression analysis established meaningful relationships between UCS and index properties; 0.85 and 0.83 positive coefficient correlations between the variables were determined by regression analysis. The methodology provided an appropriate alternative to quantitative estimation of UCS and avoided the need for tedious and time consuming laboratory testing.