Turbulent forced convection correlations are available in the literature for gases (Pr ∼ 0.7), but the test data leave a gap in the range of Prandtl (Pr) number between 0.1 and 0.7 occupied by binary gas mixtures. In this paper we develop a turbulent forced convection correlation for the Nusselt (Nu) number of in-tube binary gas mixtures for the ranges of Reynolds (Re) number between 104 and 106 and Prandtl (Pr) number between 0.1 and 0.7. A fully connected back-propagation Artificial Neural Network (ANN) is used to learn the pattern of Nu as a function of Re and Pr. Available test data in the range of 0.001 < Pr < 0.1 and 0.7 < Pr < 1000 are provided to the ANN. The test data are separated in two sets to train and test the neural network. A training set with 80% of the data is used to predict a testing set with the remaining 20% of the data. After the network is trained, we make use of the excellent nonlinear interpolation capabilities of ANNs, to predict values of Nu for the sought range 0.1 < Pr < 0.7. These predictions are later used to generate a correlation that aptly covers the complete range of Prandtl numbers.
- Heat Transfer Division
Turbulent Forced Convection Correlation for the In-Tube Flow of Binary Gas Mixtures With 0.1<Pr<0.7
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Diaz, G, & Campo, A. "Turbulent Forced Convection Correlation for the In-Tube Flow of Binary Gas Mixtures With 0.1<Pr<0.7." Proceedings of the ASME/JSME 2007 Thermal Engineering Heat Transfer Summer Conference collocated with the ASME 2007 InterPACK Conference. ASME/JSME 2007 Thermal Engineering Heat Transfer Summer Conference, Volume 1. Vancouver, British Columbia, Canada. July 8–12, 2007. pp. 389-394. ASME. https://doi.org/10.1115/HT2007-32355
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