Application of intelligent methods for the prediction and optimization of thermal characteristics in a tube equipped with perforated twisted tape

作者：Shabanian Seyed Reza^*; Lashgari Shiva; Hatami Tahma**

来源：Numerical Heat Transfer Part A-Applications, 2016, 70(1): 30-47.

DOI：10.1080/10407782.2016.1139982

In the present study, a feed-forward artificial neural network (ANN) was developed to estimate the Nusselt number (Nu), friction factor (f), and thermal performance (eta) in a tube equipped with perforated twisted tape. The MSE and R-2 values of the best network (4-10-3-3) are 0.04 and 0.9965, respectively. In addition, empirical equations were developed using the genetic algorithm. The MSE values of power-law equations for Nu, f and eta are 2.7369, 4.13E-06, and 5.09E-05, respectively. Estimation of the developed ANN was found to be superior in comparison with the corresponding power-law equations.

• 出版日期2016