ORIGINAL ARTICLE Using non-destructive tests for estimating uniaxial compressive strength and static Young’s modulus of carbonate rocks via some modeling techniques Shekoufeh Aboutaleb 1 • Mahmoud Behnia 1 • Raheb Bagherpour 1 • Behzad Bluekian 2 Received: 25 October 2016 / Accepted: 24 March 2017 / Published online: 11 April 2017 Ó Springer-Verlag Berlin Heidelberg 2017 Abstract Prediction of elastic mechanical properties such as uniaxial compressive strength (UCS) and static Young’s modulus (E s ) is one of the main purposes of studies in geological, geotechnical, geophysical, petroleum, and rock engineering projects. The UCS test is applied to determine them. However, this test is destructive, expensive, time- consuming, and requires high-quality samples. Therefore, using indirect methods seems to be indispensable for esti- mating dynamic elastic properties. Consequently, the main intention of this study was to predict the relationship between UCS and E s with dynamic poisson ratio (# d ) and dynamic Young’s modulus (E d ), using simple and multi- variate regression analysis (SRA and MRA), an artificial neural network (ANN), and support vector regression (SVR), and to compare and evaluate these methods with each other. For this purpose, different intact limestone rock samples of Asmari formation (ranged from limestone to marl) were collected from five different dam sites located in the southwest of Iran. Following regression analysis, the best equations for estimating UCS and E s of these samples with high and acceptable accuracy in terms of coefficient of determination (R 2 ) and root mean square error (RMSE) are suggested. These equations are simple, practical, and accurate enough to apply for prediction purposes at pre- liminary design stages. Although ANN and SVR models are both powerful techniques, the SVR run time is con- siderably faster. Besides, when cocmparing the three models used, the SVR model was found more desirable and advantageous. Keywords Uniaxial compressive strength Á Static Young’s modulus Á Indirect methods Á Dynamic elastic properties Á Asmari formation Á Support vector regression Introduction Estimation of rock mechanical properties is considered one of the most important components in geotechnical, geo- logical and rock engineering projects. Two of the most commonly used and fundamental mechanical parameters are the uniaxial compressive strength (UCS) and the static modulus of elasticity (E s ). These are important input parameters for rock mass classification systems and char- acteristics, rock failure criteria, stability analysis of underground and surface structures, and analytical and numerical design approaches like the design of tunnel excavations (Jahed Armaghani et al. 2015). The method for measuring them has been standardized by both ASTM (1984) and ISRM (1981). This method is destructive, expensive, time-consuming, and needs a large number of well-prepared rock samples. In order to overcome these problems, many studies have considered the possibility of an easy and quick way to predict the UCS and E s based on indirect methods or nondestructive tests. The ultrasonic method offers the possibility of obtaining these parameters & Shekoufeh Aboutaleb Shekoufeh.aboutaleb@gmail.com Mahmoud Behnia Behnia@cc.iut.ac.ir Raheb Bagherpour Bagherpour@cc.iut.ac.ir Behzad Bluekian Behzad.bluekian@gmail.com 1 Department of Mining Engineering, Isfahan University of Technology, Isfahan 8415683111, Iran 2 Department of Computer Engineering, Islamic Azad University, Najafabad Branch, Isfahan, Iran 123 Bull Eng Geol Environ (2018) 77:1717–1728 https://doi.org/10.1007/s10064-017-1043-2