Determination of drilling rate index based on mineralogical and textural properties of natural stones

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dc.authoridShaterpour Mamaghani, Aydin/0000-0001-7751-4796
dc.authoridER, Selman/0000-0001-6341-5463
dc.authoridCopur, Hanifi/0000-0003-0458-9898;
dc.authorwosidShaterpour Mamaghani, Aydin/G-5623-2015
dc.authorwosidER, Selman/R-8367-2018
dc.authorwosidCopur, Hanifi/W-9323-2018
dc.authorwosidTumac, Deniz/U-1794-2017
dc.contributor.authorTumac, Deniz
dc.contributor.authorShaterpour-Mamaghani, Aydin
dc.contributor.authorHojjati, Shahabedin
dc.contributor.authorPolat, Can
dc.contributor.authorEr, Selman
dc.contributor.authorCopur, Hanifi
dc.contributor.authorBalci, Cemal
dc.date.accessioned2024-08-04T20:54:27Z
dc.date.available2024-08-04T20:54:27Z
dc.date.issued2023
dc.departmentİnönü Üniversitesien_US
dc.description.abstractOver the last few decades, researchers have focused on developing models that aim to predict the drillability of natural stones based on their physicomechanical properties using regression analyses. This study aims to investigate the relationships between the drilling rate index (DRI) of natural stones and their mineralogical and textural properties. A database composed of 37 natural stone samples was used to develop new DRI estimation models using regression analysis and the application of an evolutionary algorithm. The results revealed that the DRI could be predicted based on the texture coefficient, Shore scleroscope hardness, and the product of the uniaxial compressive strength and Brazilian tensile strength based on an analysis of the combined dataset consisting of natural stones of metamorphic, sedimentary, and magmatic origins. The non-linear models developed by the evolutionary computation algorithm revealed that the texture coefficient, mean grain size, uniaxial compressive strength, and Brazilian tensile strength could be used to predict the DRI of metamorphic natural stones. This study differs from previous studies through its use of a novel evolutionary algorithm based on a combination of gene expression programming and particle swarm optimization, which was used to perform a non-linear regression analysis to identify models that could accurately predict DRI. To improve the generalizability of the proposed models, more types of natural stones, especially those with magmatic origins, should be included in the database analyzed in this study.en_US
dc.identifier.doi10.1007/s10064-023-03279-0
dc.identifier.issn1435-9529
dc.identifier.issn1435-9537
dc.identifier.issue7en_US
dc.identifier.scopus2-s2.0-85162654136en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1007/s10064-023-03279-0
dc.identifier.urihttps://hdl.handle.net/11616/101420
dc.identifier.volume82en_US
dc.identifier.wosWOS:001012476500002en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofBulletin of Engineering Geology and The Environmenten_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDrilling rate indexen_US
dc.subjectMineralogical propertiesen_US
dc.subjectTextural propertiesen_US
dc.subjectRegression analysisen_US
dc.subjectGEP-PSO algorithmen_US
dc.titleDetermination of drilling rate index based on mineralogical and textural properties of natural stonesen_US
dc.typeArticleen_US

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