Artificial neural network techniques for the determination of condensation heat transfer characteristics during downward annular flow of R134a inside a vertical smooth tube

Prediction of friction factor of pure water flowing inside vertical smooth and microfin tubes by using artificial neural networks

“…One may refer to a recent review on the topic presented by Cong et al [10] for more studies on the neural networks in fluid flow and heat transfer. Also, additional various information regarding with the application of artificial intelligence techniques to the in-tube flows can be seen authors' previous publications in the literature [11][12][13][14][15][16][17][18].…”

A correlation development for predicting the pressure drop of various refrigerants during condensation and evaporation in horizontal smooth and micro-fin tubes

“…The error analyses' calculation procedure for the average values of the experimental and calculated results of the two-phase pressure drops regarding with R 2 error, proportional error and mean square error (MSE) can be seen from authors' previous publication [1] and their results appear in Tables 1 and 2.…”

“…The detailed information on the ANN analyses of the determination condensation heat transfer coefficient, pressure drop and correlation development can be seen from the authors' previous publications [1][2][3][4]6,7]. It should be noted that the authors benefitted from their own experimental database in these publications.…”

“…Balcilar et al [1,2] numerically investigated the best artificial intelligence method among multi-layer perceptron (MLP), radial basis networks (RBFN), generalized regression neural network (GRNN) and adaptive neuro-fuzzy inference system (ANFIS) to estimate the experimentally measured convective heat transfer coefficient and pressure drop of R134a flowing downward inside a vertical tube during annular flow. Balcilar et al [3,4] of R134a during downward condensation both experimentally and numerically by using the genetic algorithm technique (GA), the unconstrained nonlinear minimization algorithm Nelder-Mead method (NM) and the non-linear least squares error method (NLS) for the optimization of the variables in the study.…”

Numerical investigation of mixed convection in a lid-driven triangular cavity with a circular cylinder using ANN modeling

“…A lot of work has been carried out to solve the problems of ground source heat pump and solar assisted heat pump by using the artificial neural networking [30][31][32][33][34][35]. ANN has also widely been used in several fields of heat transfer and fluid flow [36][37][38][39][40][41][42][43][44][45] like natural and forced convection, boiling and condensation, pipe flow etc.…”