Modeling of the effects of plug tip angle on the performance of counter-flow Ranque-Hilsch vortex tubes using artificial neural networks [Karş?t ak?şl? Ranque-Hilsch vorteks tüpünün performans?na tapa aç?s? etkisinin yapay sinir a?lar? yöntemi Ile modellenmesi]
Küçük Resim Yok
Tarih
2008
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, by making use of experimental data, the effect of plug tip angle at the hot outlet section of a counter flow Ranque-Hilsch vortex tube (RHVT) on performance has been modeled using artificial neural network (ANN). In the modeling, data which were obtained from experimental studies in a laboratory environment have been used. In the system developed, ANN apply input parameters are P, ? and ?, output parameter is ?T. When the results obtained from ANN and statistical analyses of experimental data have been compared, it has been determined that the two groups of data are coherent, and that there is not a significant difference between them. As a result, this study indicates that ANN can be safely used for RHVTs and thus it can decrease many experimental disadvantages to a minimum level. © 2008 TIBTD.
Açıklama
Anahtar Kelimeler
Artificial neural network, Performance, Ranque-Hilsch vortex tube
Kaynak
Isi Bilimi Ve Teknigi Dergisi/ Journal of Thermal Science and Technology
WoS Q Değeri
Scopus Q Değeri
Q4
Cilt
28
Sayı
2
