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Statistical models for predicting the mechanical properties of limestone aggregate by simple test methods

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EN
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EN
The prediction of strength properties is a topic of interest in many engineering fields. The common tests used to evaluate rock strength include the uniaxial compressive strength test ( UCS), Brazilian tensile strength ( BTS) and flexural strength ( FS). These tests can only be carried out in the laboratory and involve some difficulties such as preparation of the samples according to standards, amount of samples, and the long duration of test phases. This article aims to suggest equations for the prediction of mechanical properties of aggregates as a function of the P-wave velocity ( Vp) and Schmidt hammer hardness ( SHH) value of intact or in-situ rocks using regression analyses. Within the scope of the study, 90 samples were collected in the south of Türkiye. The mechanical properties, such as uniaxial compressive strength, Brazilian tensile strength and flexural strength of specimens, were determined in the laboratory and investigated in relation to P-wave velocity, and Schmidt hardness. Using regression techniques, various models were developed, and comparisons were made to find the optimum models using a coefficient of determination (R2) and p value (sig) performance indexes. Simple and multiple regression analysis found powerful correlations between mechanical properties and P-wave velocity and Schmidt hammer hardness. In addition, the prediction equations were compared with previous studies. The results obtained from this study indicate that the results of simple test methods, such as Vp or SHH values, of rock used for aggregate could be used to predict some mechanical properties. Thus, it will be possible to obtain information about the mechanical properties of aggregates in the study area in a faster and more practical way by using predictive models.
Rocznik
Strony
393--407
Opis fizyczny
Bibliogr. 47 poz., fot., rys., tab., wykr.
Bibliografia
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Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6b2e81d3-bd79-4774-99ea-b6f533a113d7
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