Modeling Of Heat Transfer Coefficients During Condensation At Low Mass Fluxes Inside Horizontal And Inclined Smooth Tubes

Abstract

In this study, in-tube condensation was conducted for mass fluxes of 100, 75 and 50 kg/m 2 s, and temperature differences of 1, 3, 5, 8 and 10 C. Measurements and flow regimes were captured at various mean vapor qualities between 0.1 and 0.9 inside an inclined smooth tube with an inside diameter of 8.38 mm and 1.49 m long. Fifteen distinct inclination angles from -90 to 90 were considered while the condensation temperature was always maintained at 40 C. The experimental results showed that the inclination angle significantly influenced the flow patterns and the heat transfer coefficients. It was also shown that the heat transfer coefficient was dependent on the temperature difference, even though this dependency was greater for downward flows than for upward flows. By using the experimental data and fuzzy C-means clustering adaptive neuro-fuzzy inference system (FCM-ANFIS) technique, a model was proposed for the prediction of heat transfer coefficients during condensation of low mass fluxes inside inclined smooth tubes. By using three statistical criteria, the performance of the proposed model was examined against experimental data and it was found that FCM-ANFIS was a strong tool for the prediction of the heat transfer coefficient based on the effective parameters of vapor quality, temperature difference and inclination angle.

Single phase nanofluid thermal conductivity and viscosity prediction using neural networks and its application in a heated pipe of a circular cross section

“…Numerical studies of nanofluids pose a serious challenge to nanotechnology researchers, this challenge has hampered progress in nanofluids applications by limiting the number of trusted and verified simulation results. However, numerical studies are very important in the product development process 1–13 . The inconsistent numerical findings by different researchers are also a challenge since they use different formulations to represent nanofluids and hence obtain differing results.…”

“…However, numerical studies are very important in the product development process. [1][2][3][4][5][6][7][8][9][10][11][12][13] The inconsistent numerical findings by different researchers are also a challenge since they use different formulations to represent nanofluids and hence obtain differing results. To overcome these challenges, costly experiments must be carried out and repeated many times.…”