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

被引：89

作者：

Dincer, K. ^{[1
]}

Tasdemir, S. ^{[2
]}

Baskaya, S. ^{[3
]}

Uysal, B. Z. ^{[4
]}

机构：

[1] Selcuk Univ, Fac Engn & Architecture, Dept Mech Engn, Konya, Turkey

[2] Selcuk Univ, Tech Sci Coll, Konya, Turkey

[3] Gazi Univ, Fac Engn & Architecture, Dept Mech Engn, Ankara, Turkey

[4] Gazi Univ, Fac Engn & Architecture, Dept Chem Engn, Ankara, Turkey

来源：

APPLIED THERMAL ENGINEERING | 2008年 / 28卷 / 17-18期

关键词：

Ranque-Hilsch vortex tube; Performance; Artificial neural network;

D O I：

10.1016/j.applthermaleng.2008.01.016

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

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.

引用

页码：2380 / 2390

页数：11

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