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High performance turbine airfoils are typically cooled with a combination of internal cooling channels and impingement. In such applications, the jets impinge against a target surface, and then exit along the channel formed by the jet plate, target plate, and side walls. Local convection coefficients are the result of both the jet impact, as well as the channel flow produced from the exiting jets. Numerous studies have explored the effects of jet array and channel configurations on both target and jet plate heat transfer coefficients. However, most current studies use the plenum temperature as the reference temperature in heat transfer calculations. This presents some difficulty to designers who need to determine heat transfer rates based on the local bulk temperatures. This paper examines three different methods to determining the local bulk temperature in a steady state impingement channel heat transfer experiment. The various methods will be compared based on their ease of application as well as their accuracy in describing the results. One method proves to be the most accurate, while another proves to be more easily implemented. The methods are compared for a single case previously studied, on a 15 hole, single row impingement channel, with dimensions of X/D=5, Y/D=4, Z/D=1 and 3, and an average jet based Reynolds number of 17,000 and 45,000. Effects due to the choice of the reference temperature in heat transfer calculations are shown to cause significant variations in the calculated heat transfer coefficients. These results point to a transition between different flow regimes in the post-impingement flow. [ABSTRACT FROM AUTHOR]

In the literature, numerical heat transfer analysis of supercritical carbon dioxide (sCO 2) is often conducted in idealized tubular geometries to better understand its fundamental properties. Its sensitivity to temperature and pressure variations at supercritical conditions indicates that, unlike traditional subcritical turbulent flows in tubes, the thermal boundary condition (TBC) will have a noticeable influence on heat transfer trends. Despite this, it has become standard practice to validate sCO 2 numerical models without considering the TBCs. In this work, local heat transfer and flow characteristics of sCO 2 in cooled horizontal tubes under all three TBCs were investigated numerically. Five configurations were considered: a conjugate tube-in-tube heat exchanger, a single tube with constant wall heat flux, a walled tube with constant wall heat flux, a single tube with constant wall temperature, and a walled tube with constant wall temperature. Heat transfer coefficients along the tube axis were analyzed using local temperature and heat flux. Circumferential distributions of temperature and heat flux were assessed. Temperature, density, and velocity profiles within the flow were also considered. Despite being the most commonly compared in the literature, the heat exchanger and single tube with a uniform wall heat flux materialized the largest heat transfer coefficient difference (10%–12%) between configurations. Furthermore, the single tube with constant heat flux exhibits variations in circumferential wall temperature of up to 9 K when contrasted with the heat exchanger, which demonstrates nearly uniform trends in circumferential wall temperature. The results holistically indicate that the TBC significantly influences heat transfer trends in supercritical fluids and that careful consideration must be taken when validating numerical models involving supercritical fluids. • Thermal boundary condition (TBC) type strongly impacts supercritical fluid heat transfer. • TBCs used in supercritical CO 2 models and experiments rarely match during validation. • Careful consideration of TBC is needed for supercritical fluid model validation [ABSTRACT FROM AUTHOR]

An exhaustive review was undertaken to assemble all available correlations for supercritical CO2 in straight, round tubes of any orientation, with special attention paid to how the wildly varying fluid properties near the critical point are handled. The assemblage of correlations, along with subsequent discussion, is presented from a historical perspective, starting from pioneering work on the topic in the 1950s to the modern day. Despite the growing sophistication of sCO2 heat transfer correlations, modern correlations are still only generally applicable over a relatively small range of operating conditions, and there has not been a substantial increase in predictive capabilities. Recently, researchers have turned to machine learning as a tool for next-generation heat transfer prediction. An overview of the state-of-the-art predicting sCO2 heat transfer using machine learning methods, such as artificial neural networks, is also presented. [ABSTRACT FROM AUTHOR]