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Comparative investigation of Shore, Schmidt, and Leeb hardness tests in the characterization of rock materials

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Prediction of physical and mechanical properties of rock materials using rebound-based hardness test methods is widely preferred in many fields of engineering and in the characterization of rock materials, because… Click to show full abstract

Prediction of physical and mechanical properties of rock materials using rebound-based hardness test methods is widely preferred in many fields of engineering and in the characterization of rock materials, because they are non-destructive, practical, and economical. In this study, 40 types of rocks with magmatic, metamorphic, and sedimentary origins, represented by travertine, limestone, marble, dolomite, granite, syenite, dunite, andesite, schist, gabbro, tuff, and ignimbrite were selected. First, dry unit weight (γd), open porosity (no), water absorption by weight (WAW), wide wheel abrasion (WA), and uniaxial compressive strength values were determined. After that, Shore C-2 scleroscope (HSC), L-type Schmidt hammer (HSL), and Leeb (HLD) rebound-based hardness tests were carried out on all samples, and then, hardness values by three methods were compared with the obtained parameters. The Leeb hardness test, which is more recent and innovative than the Shore and Schmidt hardness tests, was initially developed for metallic materials. However, the method has become increasingly popular in the determination of hardness of rock materials in laboratory as well as in field. In this study, the Leeb hardness test was found to be more useful due to its quick and precise measurement capabilities compared to Shore and Schmidt hardness tests. The results of the study reveal that the prediction of physical and mechanical properties of rocks can more precisely be determined by the HLD method than the HSL and HSC methods using the proposed equations.

Keywords: hardness tests; shore schmidt; rock materials; hardness; leeb hardness

Journal Title: Environmental Earth Sciences
Year Published: 2019

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