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Large icing wind tunnels typically have sufficient distance for drops from spray nozzles to spread evenly producing small spatial variations of cloud properties at the wind tunnel test section. As the size of a wind tunnel gets smaller, producing clouds with uniform properties becomes challenging because of 1) the reduced distance from the spray bar system to the test section and 2) the spray characteristics of most air-assisted nozzles used for spray generation. For this paper, discrete-phase simulations using FLUENT were used to explore droplet collection on a partial NACA 0012 model at different angles of attack in the Baylor Liquid Film and Cloud Tunnel (LFACT). McClain et al. (2022) used the LFACT to validate a new microwave sensor system to measure collection efficiency variations along the surface of a wind tunnel model. However, the sensors used in the investigation were essentially the same size as the measured non-uniform cloud features in the wind tunnel test section.

Many studies have been performed to quantify the formation and evolution of roughness on ice shapes created in Appendix C icing conditions, which exhibits supercooled liquid droplets ranging from 1-50 µm. For example Anderson and Shin (1997), Anderson et al. (1998), and Shin (1994) represent early studies of ice roughness during short-duration icing events measured in the Icing Research Tunnel at the NASA Glenn Research Center. In the historical literature, image analysis techniques were employed to characterize the roughness. Using multiple images of the roughness elements, these studies of roughness focused on extracting parametric representations of ice roughness elements. While the image analysis approach enabled many insights into icing physics, recent improvements in laser scanning approaches have revolutionized the process of ice accretion shape characterization.

Changes in convection coefficient caused by the changes in surface roughness characteristics along an iced NACA 0012 airfoil were investigated in the 61-cm by 61-cm (24 in. by 24 in.) Baylor Subsonic Wind Tunnel using a 91.4-cm (36-in.) long heated aerodynamic test plate and infrared thermometry. A foam insert was constructed and installed on the wind tunnel ceiling to create flow acceleration along the test plate replicating the scaled flow acceleration the along the leading 17.1% (3.6 in.) of a 53.3-cm (21-in.) NACA 0012 airfoil. Two sets of rough surface panels were constructed for the study, and each surface used the same basic random droplet pattern created using the Lagrangian droplet simulator of Tecson and McClain (2013). For the first surface, the roughness pattern was replicated with the same geometry over the plate following a smooth-to-rough transition location noted in historical literature for the case being replicated.

During aircraft design and certification, in-flight ice accretions are simulated using ice prediction codes. LEWICE, the ice accretion prediction code developed by NASA, employs a time-stepping procedure coupled with a thermodynamic model to calculate the location, size and shape of an ice accretion. LEWICE has been extensively validated for a wide range of icing conditions. However, continuing improvements to LEWICE predictive capabilities require better understandings of 1) the fundamental physics of turbulent flow generated by ice accretion roughness during an icing event and 2) the mechanisms responsible for convective enhancement of real ice accretion roughness. Recent experiments in the Icing Research Tunnel (IRT) at NASA Glenn Research Center have enabled significant insights into the nature of ice accretion roughness spatial and temporal variations.

The influence of freestream static temperature on roughness temporal evolution and spatial variation was investigated in the Icing Research Tunnel (IRT) at NASA Glenn Research Center. A 53.34 cm (21-in.) NACA 0012 airfoil model and a 152.4 cm (60-in.) HAARP-II business jet airfoil model were exposed to Appendix C clouds for fixed exposure times and thus fixed ice accumulation parameter. For the base conditions, the static temperature was varied to produce different stagnation point freezing fractions. The resulting ice shapes were then scanned using a ROMER Absolute Arm system and analyzed using the self-organizing map approach of McClain and Kreeger. The ice accretion prediction program LEWICE was further used to aid in interrogations of the ice accretion point clouds by using the predicted surface variations of local collection efficiency.