An alternative approach to predict human response to blast induced ground vibration

Turker Hudaverdi*, Ozge Akyildiz

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMakalebilirkişi

8 Atıf (Scopus)

Özet

The aim of this study is to create alternative approaches to predict human response to ground vibration. Site measurements were conducted in an urban quarry. The multiple discriminant analysis technique was used to develop classification models. The measured ground vibration values were grouped based on the limit values appearing in the literature. Two classification models were created to predict human response to ground vibration. In addition, classical predictor equations were developed to compare to the classification models. The best equations were chosen considering several error measures. All the models were tested on the independent data. The prediction accuracy of the discriminant analysis models is quite promising. Nearly eighty-nine percent of the test data were correctly classified. The classification models have a combined structure. The results of the models can be directly presented to the neighbors of the studied quarry. The models are not complex. They do not require additional software or information to practice and can be easily used by site engineers.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)257-273
Sayfa sayısı17
DergiEarthquake Engineering and Engineering Vibration
Hacim20
Basın numarası1
DOI'lar
Yayın durumuYayınlandı - Oca 2021

Bibliyografik not

Publisher Copyright:
© 2021, Institute of Engineering Mechanics, China Earthquake Administration.

Finansman

Supported by: Research Fund of the Istanbul Technical University under Grant No. MGA-2017-40581, and the Scientific and Technological Research Council of Turkey—TUBİTAK— under Grant No. 217M071 Acknowledgement 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?TUB?TAK? (No. 217M071). The authors are grateful for their financial support. 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 for their financial support.

FinansörlerFinansör numarası
Scientific and Technological Research Council
TUBİTAK217M071
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu
Istanbul Teknik ÜniversitesiMGA-2017-40581

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