Experimental study and artificial neural network modeling of unsteady laminar forced convection in a rectangular duct

Abstract

In this study, an artificial neural network (ANNs) for the prediction of unsteady heat transfer in a rectangular duct was studied. The ANNs has been applied for the unsteady heat transfer in a rectangular duct. An experimental study has been carried out to investigate the axial variation of inlet temperature and the impact of inlet frequency on decay indices in the thermal entrance region of a parallel plate channel. The investigation was conducted with laminar forced flows for Reynolds numbers ranging from 1,120 to 2,200 while the inlet heat input frequency varied from 0.02 to 0.24 Hz. The results revealed that the ANNs can be used for modeling unsteady heat transfer in the duct. The accuracy between experimental and ANNs approach results was achieved with a mean absolute relative error less than 39%.