화학공학소재연구정보센터
Chinese Journal of Chemical Engineering, Vol.12, No.4, 582-585, 2004
Prediction of pulsation frequency of pulsing flow in trickle beds based on artificial neural network
An extensive database (946 measurements) for the frequency of pulsing flow in trickle beds was established by collecting the experimental results published over past 30 years. A new correlation based on artificial neural network (ANN) to predict the pulsation frequency was developed. Seven dimensionless numbers (groups) employed in the proposed correlation were liquid and gas Reynolds, liquid Weber, liquid Eotvos, gas Froude, and gas Stokes numbers and a bed correction factor. The comparisons of performance reported in the of literature and present correlations show that ANN correlation is a significant improvement in predicting pulsation frequency with an average absolute relative error (AARE) of 10% and a standard deviation less than 18%.