Predicting the moment capacity of RC beams exposed to fire using ANNs
Küçük Resim Yok
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ELSEVIER SCI LTD
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This research investigates the implementation of artificial neural networks (ANNs) to estimate the moment capacity (M-r) of reinforced concrete (RC) beams under rising temperatures due to fire. 280 data were obtained for ANN model. Input layer in ANN model consisted of eight input parameters; the beam width (b(w)), the beam depth (d), the ratio of (b(w)/d), distance from the beam edge to the center of the rebar (d'), the ratio of (d'/d), fire time (t(exposure)), the reinforcement area (A(st)), and concrete compressive strength (f(c)). It is shown that the ANN model can be used to predict the M-r of RC beams exposed to fire with high accuracy. The predicted M-r by ANN are consistent with the results obtained using M-r equation. It was observed from the results the ANN model reduces the computational complexity problem in determining M-r. Consequently, the ANN model was used to examine the effects of the inputs parameters on M-r. (C) 2015 Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
Reinforced concrete, Fire, Beam, Moment capacity, Artificial neural network
Kaynak
CONSTRUCTION AND BUILDING MATERIALS
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
101
