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

Dincer K., Tasdemir S., Baskaya Ş., Uysal B. Z.

APPLIED THERMAL ENGINEERING, cilt.28, ss.2380-2390, 2008 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 28
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1016/j.applthermaleng.2008.01.016
  • Dergi Adı: APPLIED THERMAL ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2380-2390
  • Anahtar Kelimeler: Ranque-Hilsch vortex tube, Performance, Artificial neural network, MEASUREMENT UNCERTAINTY, HEAT-TRANSFER, TEMPERATURE, PREDICTION, SYSTEMS
  • Gazi Üniversitesi Adresli: Evet

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 Delta T has been determined using inlet parameters P, L/D, N and xi. 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 Lis a reliable modeling method for similar Studies. (C) 2008 Elsevier Ltd. All rights reserved.