S-ST-1-17 Using Neural Networks for Predicting Nusselt Number for Intube Laminar Flows
July 25, 2022Neural networks can be used to predict the Nusselt number for intube laminar flow. In addition to describing the architecture of a neural network, this report discusses the application of a neural network to a manufactured data set, open literature data, HTRI data, and CFD simulation results. Our results illustrate the...
AC-19 Mixed Convection Heat Transfer Outside High-finned Tube Bundles in Low Airflow
June 23, 2022Modeling natural-draft air coolers requires accurate prediction of airside heat transfer coefficients at low airflow rates. HTRI has collected additional data from the Air-cooled Unit (ACU) to develop a correlation for mixed convection that predicts low airflow heat transfer. The improved correlation, based on Rayleigh and Reynolds numbers, results in an...
S-SS-3-29: CFD Simulations of Diabatic Shellside Viscous Flows
January 16, 2017For shellside diabatic flows of highly viscous fluids, Xist can predict inconsistent pressure drops and heat transfer coefficients. HTRI examined the transition between forced and natural convection in single-segmental and double-segmental exchangers with Alta-Vis oil and an asphalt blend as test fluids. Comparisons were made between experimental data, open literature, computational...