Using artificial neural network for predicting performance of the Ranque–Hilsch vortex tube
作者： Murat Eray Korkmaz , Levent Gümüşel , Burak Markal
DOI: 10.1016/J.IJREFRIG.2012.04.013
关键词:
摘要: Abstract In this study, effects of conical valve angle and length to diameter ratio on the performance a counter flow Ranque–Hilsch vortex tube are predicted with artificial neural networks (ANNs) by using experimental data. model, inlet pressure ( P i ), ϕ L / D ) cold mass fraction y c used as input parameters while total temperature difference (Δ T is chosen output parameter. The multilayer feed forward model Levenberg–Marquardt learning algorithm in network hyperbolic tangent function transfer function. designed via NeuroSolutions 6.0 software. Finally, it’s disclosed that ANN can be successfully predict geometrical good accuracy.
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