The presentation of simple and multiple regression relationships to the evaluation of uniaxial compressive strength sedimentary and pyroclastic rocks with usage experimental of the Schmidt hammer
In engineering projects (dams, tunnels, and slope stability) the strength properties of the rocks affect the construction operations. In some cases, conducting field experiments is difficult, time-consuming, and expensive. Therefore, researchers have introduced practical relationships for predicting strength properties of rocks (e.g. uniaxial compressive strength (UCS)). Uniaxial compressive strength is one of the most important rock parameters in studies of rock mechanics. This parameter can be determined directly in the laboratory or can be estimated through indirect methods like the Schmidt hammer. The estimation of uniaxial compressive strength via the number of Schmidt hammer is easier, faster, and cheaper than a direct measurement. The major purpose of this study is to analyze the relationships between the uniaxial compressive strength of rocks with the Schmidt stiffness. In this research, three samples of rock have been studied including Aghajari sandstone, Qom marly formation, and Karaj tuff. With respect to the importance of this subject in this study, new practical relationships have been presented to calculate uniaxial compressive strength whose application show desired results. In order to achieve this aim, the most appropriate and logical relationships between Schmidt hardness tests with uniaxial compressive strength has been introduced by the regression method. The relationships between uniaxial compressive strength, the Schmidt hammer, and dry density of rock have been evaluated by simple and multiple regression (SR/ MR) techniques using Minitab 19 software. The statistical analyses revealed the existence of powerful correlations between the uniaxial compressive strength, Schmidt hardness features of rocks, and dry density in samples of sandstone, marl, and tuff. According to this study, multivariate regression presents more credible results.
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