Predicting of Torsional Strength of RC Beams by Using Different Artificial Neural Network Algorithms and Building Codes
Yükleniyor...
Dosyalar
Tarih
2010
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Sci Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this study, the efficiency of different artificial neural networks (ANNs) in predicting the torsional strength of reinforced concrete (RC) beams is firstly explored. Experimental data of 76 rectangular RC beams from an existing database in the literature were used to develop ANN model. The input parameters affecting the torsional strength were selected as cross-sectional area of beams, dimensions of closed stirrups, spacing of stirrups, cross-sectional area of one-leg of closed stirrup, yield strength of stirrup and longitudinal reinforcement, steel ratio of stirrups, steel ratio of longitudinal reinforcement and concrete compressive strength. Each parameter was arranged in an input vector and a corresponding output vector that includes the torsional strength of RC beam. For all outputs, the ANN models were trained and tested using three layered 11 back-propagation methods. The initial performance evaluation of 11 different back propagations was compared with each other. In addition to these, the paper presents a short review of the well-known building codes provisions for the design of RC beams under pure torsion. The accuracy of the codes in predicting the torsional strength of RC beams was also examined with comparable way by using same test data. The study shows that the ANN models give reasonable predictions of the ultimate torsional strength of RC beams (R-2 approximate to 0.988). Moreover, the study concludes that all ANN models predict the torsional strength of RC beams better than existing building code equations for torsion.
Açıklama
Anahtar Kelimeler
Reinforced concrete beam, Artificial neural network, Torsional strength, Building code, Theoretical model, Back-propagation algorithm
Kaynak
Advances in Engineering Software
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
41
Sayı
Künye
Arslan, M. H., (2010). Predicting of Torsional Strength of RC Beams by Using Different Artificial Neural Network Algorithms and Building Codes. Advances in Engineering Software, (41), 946-955. Doi: 10.1016/j.advengsoft.2010.05.009
