Title: An overview of the applications of soft computing methods for predicting the physico-mechanical properties of rocks from indirect methods

Authors: Sahas; Bijay Mihir Kunar; Karra Ram Chandar

Addresses: National Institute of Technology Karnataka, Surathkal, Karnataka – 575025, India ' National Institute of Technology Karnataka, Surathkal, Karnataka – 575025, India ' National Institute of Technology Karnataka, Surathkal, Karnataka – 575025, India

Abstract: Rocks are widely used in infrastructure constructions like roads, tunnels, buildings, and dams. Understanding physico-mechanical properties of rocks is vital for selecting suitable rocks, yet some properties pose challenges in determination. High-quality core samples and precise instruments are necessary for accurate assessment. Predicting the physico-mechanical properties of rocks is a key research area in rock mechanics. Researchers have employed diverse methods, including laboratory tests, non-destructive tests, and mineralogical and petrographical characteristics, to determine rock properties. This article reviews the use of soft computing methods, artificial intelligence, and machine learning to predict rock properties through indirect methods. Indirect methods involve engineering indices tests, mineralogical and petrographical characteristics, and additional approaches such as electrical properties, crushability indices, thermal characteristics, and grinding characteristics. The article also proposes various artificial intelligence and machine learning techniques as potential future directions in prediction of rock properties.

Keywords: physico-mechanical properties; rock; indirect methods; traditional methods; artificial intelligence; machine learning techniques.

DOI: 10.1504/IJMME.2023.133651

International Journal of Mining and Mineral Engineering, 2023 Vol.14 No.2, pp.124 - 156

Received: 13 Dec 2022
Accepted: 02 May 2023
Published online: 27 Sep 2023 *

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