Application of the output dependent feature scaling in modeling and prediction of performance of counter flow vortex tube having various nozzles numbers at different inlet pressures of air, oxygen, nitrogen and argon

In this study, the performance of the counter flow type vortex tube with the input parameters including the nozzle number (N), the densities of inlet gases (air, oxygen, nitrogen, and argon) and the inlet pressure (Pinlet) has been modeled with the proposed hybrid method combining a novel data preprocessing called output dependent feature scaling (ODFS) and adaptive network based fuzzy inference system (ANFIS) by using the experimentally obtained data. In the developed system, output parameter temperature gradient between the cold and hot outlets has been determined using input parameters comprising (Pinlet), (N), and the density of gases. In order to evaluate the performance of hybrid method, the mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), determination coefficient (R2), and Index of Agreement (IA) values have been used. The obtained results are 9.0670e-004 (MAE), 5.8563e-006 (MSE), 0.0024 (RMSE), 1.00 (R2), and 1.00 (IA) using the hybrid method.