Scopus
YÖKSİS ISSN Eşleşti
SJR Q1
Modeling of the effects of length to diameter ratio and nozzle number on the performance of counterflow Ranque-Hilsch vortex tubes using artificial neural networks
Applied Thermal Engineering · Aralık 2008
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Makale Bilgileri
ISSN13594311
Yayın TarihiAralık 2008
Cilt / Sayfa28 · 2380-2390
Scopus ID2-s2.0-48849104204
Özet
In this study, the effect of length to diameter ratio and nozzle number on the performance of a counterflow Ranque-Hilsch vortex tube has been modeled with artificial neural networks (ANN), by using experimental data. In the modeling, experimental data, which were obtained from experimental studies in a laboratory environment have been used. ANN has been designed by MATLAB 6.5 NN toolbox software in a computer environment working with Windows XP operating system and Pentium 4 2.4 GHz hardware. In the developed system outlet parameter ΔT has been determined using inlet parameters P, L/D, N and ξ. When experimental data and results obtained from ANN are compared by statistical independent t-test in SPSS, it was determined that both groups of data are consistent with each other for P > 0.05 confidence interval, and differences were statistically not significant. Hence, ANN can be used as a reliable modeling method for similar studies. © 2008 Elsevier Ltd. All rights reserved.
Yazarlar (4)
1
Kevser Dincer
2
Şakir Taşdemir
3
S. Baskaya
4
B. Zühtü Uysal
Anahtar Kelimeler
Artificial neural network
Performance
Ranque-Hilsch vortex tube
Kurumlar
Gazi Üniversitesi
Ankara Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Applied Thermal Engineering
Q1
SJR Skoru1,579
H-Index224
YayıncıElsevier Ltd
ÜlkeUnited Kingdom
Energy Engineering and Power Technology (Q1)
Fluid Flow and Transfer Processes (Q1)
Industrial and Manufacturing Engineering (Q1)
Mechanical Engineering (Q1)
Metrikler
101
Atıf
4
Yazar
3
Anahtar Kelime