Prediction of uniaxial compressive strength of the Kızılkaya ignimbrite with variable properties using MRA and ANN, Cappadocia (Turkey)

Abstract

Cappadocia in Turkey is an important region with emphasis on ethnic and historic structures and geological features. Because of volcanic eruptions, ash flow materials deposited at different levels. These different colored ignimbrite levels have a wide range of geomechanical properties. In the region, the Kızılkaya ignimbrite covers a very large area and is frequently used as building dimension stone in for the restoration of old historical buildings such as churches, caravansaries and mosques as well as new buildings. It contains tuffaceous matrix with some minerals and rock fragments. The rock has variable character. In this study, the relationship between petrographic and physico-mechanical properties of the Kızılkaya ignimbrite was investigated. Rate of change between uniaxial compressive strength and the other index properties of the rock was statistically examined utilizing multiple regression analysis (MRA) and Artificial Neural Network (ANN) methods. The study has shown that uniaxial compressive strength (UCS) of the ignimbrite can be successfully estimated by the use of dry unit weight, effective porosity, sonic velocity, and grain matrix ratio (GMR) parameters. A new UCS prediction equation is proposed in this paper for the ignimbrite with variable character. Since properties of the ignimbrite at different distances from the eruption area changes significantly, the approach presented in this study can be considered for the ignimbrites especially covering a large area with different welding degrees and grains.