Prediction of unconfined compressive strength of rocks: a review paper

Abstract

Unconfined compressive strength (UCS) of rocks is a crucial parameter in designing geotechnical structures. Owing to difficulties in obtaining proper samples for UCS test as well as the point that conducting UCS is relatively expensive, the use of indirect methods for UCS estimation has drawn considerable attentions. This review paper is aimed to briefly highlight different proposed predictive models of UCS. In this regard, nearly 85 predictive models of UCS are listed in the paper which provides a good reference and database for geotechnical readers. The highlighted models are divided into two main sections. In the first section, UCS correlations with Brazilian tensile strength test, point load index test (Is(50)), Schmidt hammer and ultrasonic velocity tests are highlighted. In the second section, recently proposed artificial intelligence-based predictive models of UCS are underlined. Apart from that, using available data (106 rock specimens), which were previously published by authors, a new correlation between UCS and Is(50) is developed which can be useful for assessing the UCS of tropical rocks. Overall, although the paper suggests conducting direct UCS test for important projects, based on the region and type of rocks, employing the highlighted predictive models for assessing the UCS of rock can be advantageous.