Estimation of tensile capacity of single anchors including edge effect using neural networks
Küçük Resim Yok
Tarih
2013
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The demand for more flexibility in the design and strengthening of concrete structures has resulted in an increased use of anchoring systems. Adhesive anchors are widely used in seismic strengthening applications to add new structural members or sections to existing concrete members. To safely design such anchors, it is very important to know their tensile capacity under axial tensile forces. This paper explores the pullout capacity of single adhesive anchors loaded in tension in uncracked concrete. To this end 142 single anchor tests including edge effect (located near a concrete edge) were obtained from literature. The formulated three-layered artificial neural network method (ANN) was trained using 75% of the data set by using different learning algorithms. The methods were tested with the remaining 25% of the data set. The variables taken into account in this study are anchor diameter, embedment length, concrete body height and edge distance. It was determined that experimental data can be estimated to a notably close extent via the ANN model. © (2013) Trans Tech Publications, Switzerland.
Açıklama
KMUTT;SCG;Global Connections;VP Wood
4th International Conference on Multi-Functional Materials and Structures, MFMS 2013 -- 14 July 2013 through 17 July 2013 -- Sathorn-Taksin, Bangkok -- 99778
4th International Conference on Multi-Functional Materials and Structures, MFMS 2013 -- 14 July 2013 through 17 July 2013 -- Sathorn-Taksin, Bangkok -- 99778
Anahtar Kelimeler
Anchor, Neural network method, Tensile capacity
Kaynak
Advanced Materials Research
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
747
