The prediction of heat transfer and fluid characteristics for equilateral triangular bodies in tandem arrangement by artificial neural networks
Küçük Resim Yok
Tarih
2012
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The objective of this study is to investigate the effect of the spacing between equilateral dual triangular bodies symmetrically placed into the channel axis under steady state conditions on heat transfer and fluid characteristics by using artificial neural networks (ANN). The Back Propagation (BP) training algorithm was applied to train the model. The successful application proved that ANN model can be used for predicting the Nusselt number and skin friction coefficient as a convenient and effective method. The distribution of local Nusselt number, skin friction coefficient along the channel wall and overall enhancement ratio of all investigated cases are presented.
Açıklama
Anahtar Kelimeler
Artificial neural network, Heat transfer enhancement, Tandem arrangement, Triangular body, Bodies in tandem, Channel axis, Channel wall, Enhancement ratios, Heat Transfer enhancement, Local Nusselt number, Skin friction coefficient, Steady-state condition, Tandem arrangement, Training algorithms, Triangular body, Friction, Nusselt number, Pipe flow, Skin friction, Neural networks, Artificial neural network, Heat transfer enhancement, Tandem arrangement, Triangular body, Bodies in tandem, Channel axis, Channel wall, Enhancement ratios, Heat Transfer enhancement, Local Nusselt number, Skin friction coefficient, Steady-state condition, Tandem arrangement, Training algorithms, Triangular body, Friction, Nusselt number, Pipe flow, Skin friction, Neural networks
Kaynak
Gazi University Journal of Science
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
25
Sayı
2
