Investigation of the effects of blasting design parameters and rock properties on blast-induced ground vibrations

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dc.authoridARPAZ, ERCAN -- 0000-0002-6309-5356en_US
dc.contributor.authorGorgulu, Kazim
dc.contributor.authorArpaz, Ercan
dc.contributor.authorUysal, Onder
dc.contributor.authorDuruturk, Y. Selim
dc.contributor.authorYuksek, A. Gurkan
dc.contributor.authorKocaslan, Arzu
dc.contributor.authorDilmac, M. Kursat
dc.date.accessioned2019-07-27T12:10:23Z
dc.date.accessioned2019-07-28T09:48:38Z
dc.date.available2019-07-27T12:10:23Z
dc.date.available2019-07-28T09:48:38Z
dc.date.issued2015
dc.department[Gorgulu, Kazim -- Duruturk, Y. Selim -- Dilmac, M. Kursat] Cumhuriyet Univ, Min Engn Dept, Sivas, Turkey -- [Arpaz, Ercan] Kocaeli Univ, Kocaeli Vocat Sch, Izmit, Kocaeli, Turkey -- [Uysal, Onder] Dumlupinar Univ, Min Engn Dept, Kutahya, Turkey -- [Yuksek, A. Gurkan] Cumhuriyet Univ, Dept Comp Engn, Sivas, Turkey -- [Kocaslan, Arzu] Cumhuriyet Univ, Insurance & Risk Adm, Sivas, Turkey -- [Dilmac, M. Kursat] Ataturk Univ, Min Engn Dept, Erzurum, Turkeyen_US
dc.description.abstractThis study addresses the effects of rock characteristics and blasting design parameters on blast-induced vibrations in the Kangal open-pit coal mine, the Tulu open-pit boron mine, and the Kirka open-pit boron mine. In this study, multiple vibration measurements have been conducted, and the related data have been analyzed and evaluated. Several artificial neural network (ANN) and regression models based on the same blasting design parameters, resistivity, and P-wave and S wave velocities of the surrounding rocks have been constructed to estimate the peak particle velocities and the frequencies of related blast-induced vibrations. The data derived from these models and the classical evaluations indicate that ANNs provide more reliable results than the other methods.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [110M294]en_US
dc.description.sponsorshipThis study is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) project No. 110M294. The authors would also like to thank the staff of the Electricity Generation Company, Demir Export, and Eti Mine for their assistance during the field work.en_US
dc.identifier.doi10.1007/s12517-014-1477-9en_US
dc.identifier.endpage4278en_US
dc.identifier.issn1866-7511
dc.identifier.issn1866-7538
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-84930178517en_US
dc.identifier.scopusqualityN/A
dc.identifier.startpage4269en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s12517-014-1477-9
dc.identifier.urihttps://hdl.handle.net/20.500.12418/7828
dc.identifier.volume8en_US
dc.identifier.wosWOS:000355336800071en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGER HEIDELBERGen_US
dc.relation.ispartofARABIAN JOURNAL OF GEOSCIENCESen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBlastingen_US
dc.subjectGround vibrationsen_US
dc.subjectRock propertiesen_US
dc.subjectArtificial neural networksen_US
dc.titleInvestigation of the effects of blasting design parameters and rock properties on blast-induced ground vibrationsen_US
dc.typeArticleen_US

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