Evaluation of capability of blast-induced ground vibration predictors considering measurement distance and different error measures

Turker Hudaverdi*, Ozge Akyildiz

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Araştırma sonucu: ???type-name???Makalebilirkişi

6 Atıf (Scopus)

Özet

This study aims to investigate capability of the vibration prediction approaches, comprehensively. Field investigations were performed in a sandstone quarry. All the main conventional scaled distance equations were evaluated. A multivariate equation that contains blast design parameters was created by stepwise regression. A robust artificial neural network model was constructed. Effect of the additional parameters on success of the vibration estimation was examined. The success of the equations was evaluated considering the measurement distance. Evaluation of vibrations based on the measurement distance provided an opportunity to examine effectiveness of the equations that contains inelastic attenuation factor. Suitable error measures were investigated to examine the precision of vibration estimation. Both percentage errors and symmetric errors were found to be useful. Increase in the measurement distance was resulted in increase in prediction error. The classical scaled distance equations were found to be quite successful. The multivariate equation and artificial neural network model did not made better predictions than the scaled distance equations for long distance. The equations with inelastic attenuation formula do not have any advantage over classical scaled distance equations.

Orijinal dilİngilizce
Makale numarası421
DergiEnvironmental Earth Sciences
Hacim78
Basın numarası14
DOI'lar
Yayın durumuYayınlandı - 1 Tem 2019

Bibliyografik not

Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Finansman

This study was supported by the Research Fund of the Istanbul Technical University (No: MGA-2017-40581), and partially supported by The Scientific and Technological Research Council of Turkey—TUBİTAK—(No: 217M071). The authors are grateful to the Istanbul Technical University and TUBITAK for their financial support.

FinansörlerFinansör numarası
TUBITAK
TUBİTAK217M071
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu
Istanbul Teknik ÜniversitesiMGA-2017-40581

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