In this study, to observe the behavior of chemical anchors embedded in concrete under the tensile effect,108 different anchor specimens were prepared with different parameters as concrete compressivestrength, reinforcement bar diameters, anchor depths, sizes of drilled holes, cleanliness of the drilledholes. Pull-out tests were conducted and obtained data were examined with the axial-load capacitiesand the failure situations. Finally, the depth of anchors, compressive strength and reinforcement diame-ter were observed to increase the axial-load-bearing capacity. The specimens cleaned with water couldbear more axial loads than cleaned using air. For the anchors installed without cleaning the holes, a sig-nificant decrease was observed in the axial-load carrying capacities compared to the other two condi-tions. The ANN algorithm exhibited a 78.3% prediction success compared with other algorithms. Theempirical relations in the literature were found to have limited level of prediction success rates accordingto the ANN’s results
Eser Adı (dc.title) | Experimental and analytical investigation of chemical anchors’s behaviour under axial tensile |
Yayın Türü (dc.type) | Makale |
Yazar/lar (dc.contributor.author) | MÜSEVİTOĞLU, Abdullah |
Yazar/lar (dc.contributor.author) | ARSLAN, Musa Hakan |
Yazar/lar (dc.contributor.author) | AKSOYLU, Ceyhun |
Yazar/lar (dc.contributor.author) | ÖZKIŞ, Ahmet |
Atıf Dizini (dc.source.database) | Wos |
Atıf Dizini (dc.source.database) | Scopus |
Konu Başlıkları (dc.subject) | Adherence |
Konu Başlıkları (dc.subject) | Pull-out Tests |
Konu Başlıkları (dc.subject) | Experimental Setup |
Konu Başlıkları (dc.subject) | Chemical Anchorage |
Konu Başlıkları (dc.subject) | Artificial Intelligence |
Yayın Tarihi (dc.date.issued) | 2020 |
Kayıt Giriş Tarihi (dc.date.accessioned) | 2021-01-22T07:38:45Z |
Açık Erişim tarihi (dc.date.available) | 2021-01-22T07:38:45Z |
Özet (dc.description.abstract) | In this study, to observe the behavior of chemical anchors embedded in concrete under the tensile effect,108 different anchor specimens were prepared with different parameters as concrete compressivestrength, reinforcement bar diameters, anchor depths, sizes of drilled holes, cleanliness of the drilledholes. Pull-out tests were conducted and obtained data were examined with the axial-load capacitiesand the failure situations. Finally, the depth of anchors, compressive strength and reinforcement diame-ter were observed to increase the axial-load-bearing capacity. The specimens cleaned with water couldbear more axial loads than cleaned using air. For the anchors installed without cleaning the holes, a sig-nificant decrease was observed in the axial-load carrying capacities compared to the other two condi-tions. The ANN algorithm exhibited a 78.3% prediction success compared with other algorithms. Theempirical relations in the literature were found to have limited level of prediction success rates accordingto the ANN’s results |
Yayın Dili (dc.language.iso) | en |
Sponsor-Yayıncı (dc.description.sponsorship) | Scientific Research Coordination of Konya Technical University |
Tek Biçim Adres (dc.identifier.uri) | http://hdl.handle.net/20.500.12498/4922 |