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When examining the literature on the adhesion strength of impact ice, there have been a wide range of methodologies tried to measure the required stresses to induce interfacial delamination. Utilizing the Icing Research Tunnel at the NASA Glenn Research Center to generate the impact ice required for this work, several different mechanical tests have been and are being developed to determine the stresses along the interface between ice and coupon. This set of tests includes the technical mature modified lap joint test which has been used to conduct ice adhesion studies through a wide sweep of icing conditions. To conduct in situ ice adhesion measurements inside of the Icing Research Tunnel, several new experiments are currently being developed to make ice adhesion measurements during and immediately after ice accretion.

A process of using machine learning to segment impact ice microstructure is presented and analyzed. The microstructure of impact ice has been shown to correlate with the adhesion strength of ice. Machine vision techniques are explored as a method of decreasing analysis time. The segmentation was conducted with the goal of obtaining average grain size estimations. The model was trained on a set of micrographs of impact ice grown at NASA Glenn’s Icing Research Tunnel. The model leveraged a model pre-trained on a large set of micrographs of various materials as a starting point. Post-processing of the segmented images was done to connect broken boundaries. An automatic method of determining grain size following an ASTM standard was implemented. Segmentation results using different training sets as well as different encoder and decoder pairs are presented. Calculated sizes are compared to manual grain size measurement methods.

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.

An experimental research effort was begun to develop a database of airplane aerodynamic characteristics with simulated ice accretion over a large range of incidence and sideslip angles. Wind-tunnel testing was performed at the NASA Langley 12-ft Low-Speed Wind Tunnel using a 3.5% scale model of the NASA Langley Generic Transport Model. Aerodynamic data were acquired from a six-component force and moment balance in static-model sweeps from α = -5 to 85 deg. and β = -45 to 45 deg. at a Reynolds number of 0.24x10⁶ and Mach number of 0.06. The 3.5% scale GTM was tested in both the clean configuration and with full-span artificial ice shapes attached to the leading edges of the wing, horizontal and vertical tail. Aerodynamic results for the clean airplane configuration compared favorably with similar experiments carried out on a 5.5% scale GTM.

Tests designed to quantify the gravitational effects on thermal mixing and reactant injection in a Supercritical Water Oxidation (SCWO) reactor have recently been performed in the Zero Gravity Facility (ZGF) at NASA's Glenn Research Center. An artificial waste stream, comprising aqueous mixtures of methanol, was pressurized to approximately 250 atm and then heated to 450°C. After uniform temperatures in the reactor were verified, a controlled injection of air was initiated through a specially designed injector to simulate diffusion limited reactions typical in most continuous flow reactors. Results from a thermal mapping of the reaction zone in both 1-g and 0-g environments are compared. Additionally, results of a numerical model of the test configuration are presented to illustrate first order effects on reactant mixing and thermal transport in the absence of gravity.

NASA and the FAA are funding the development of ground-based remote sensing systems specifically designed to detect and quantify the icing environment aloft. The goal of the NASA activity is to develop a relatively low cost stand-alone system that can provide practical icing information to the flight community. The goal of the FAA activity is to develop more advanced systems that can identify supercooled large drop (SLD) as well as general icing conditions and be integrated into the existing weather information infrastructure. Both activities utilize combinations of sensing technologies including radar, radiometry, and lidar, along with Internet-available external information such as numerical weather model output where it is found to be useful. In all cases the measured data of environment parameters will need to be converted into a measure of icing hazard before it will be of value to the flying community.

NASA, the FAA, DoD, and NOAA have teamed with industry and academia to develop a capability to detect icing conditions ahead of aircraft using onboard or ground-based remote sensing systems. The goal of the program is to provide pilots with sufficient information to allow avoidance of icing. Information displayed to the pilot, as a measure of icing potential, will be useful in assessing the risk of entering the sensed conditions. This requires measurement and mapping of cloud microphysical parameters, especially cloud and precipitation liquid water content, droplet size and temperature, with range. Remote measurement of cloud microphysical conditions has been studied for years. However, this is the largest focused program devoted to remotely detect aircraft icing conditions. Primary funding sources are NASA Aerospace Operations Systems, the FAA Aviation Weather Research Program and William J.

Refractive secondary concentrators are being considered for solar thermal applications because of their ability to achieve maximum efficiency through the use of total internal reflection for the concentration and distribution of solar energy. A prototype refractive secondary concentrator was built based on ray tracing analysis to demonstrate this collection and distribution concept. The design included a conical secondary concentrator and a faceted extractor. The objective of this effort was to functionally evaluate the performance of the refractive secondary concentrator/extractor prototype and to compare the results with modeling. Most of the light was found to exit the refractive secondary concentrator through the extractor. In addition, the degree of attenuation encountered by the light as it passed through the refractive secondary concentrator was of interest.