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The Icing Research Tunnel at NASA Glenn follows the recommended practice for calibration outlined in SAE’s ARP5905. The calibration team has followed the schedule of a full calibration every five years with a check calibration done every six months following. The liquid water content of the IRT has maintained stability within the stated specifications of variation within +/- 10% of the curve fit equation generated from calibration data. Using past measurements and data trends, IRT characterization engineers wanted to develop methods for the ability to know when data were not within variation. Trends can be observed in the liquid water content measurement process by constructing statistical process control charts. This paper describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, process for rejection of data, and construction of control charts.

Smoke detection experiments were conducted in the Microgravity Science Glovebox (MSG) on the International Space Station (ISS) during Expedition 15 in an experiment entitled Smoke Aerosol Measurement Experiment (SAME). The preliminary results from these experiments are presented. In order to simulate detection of a prefire overheated-material event, samples of five different materials were heated to temperatures below the ignition point. The smoke generation conditions were controlled to provide repeatable sample surface temperatures and air flow conditions. The smoke properties were measured using particulate aerosol diagnostics that measure different moments of the size distribution. These statistics were combined to determine the count mean diameter which can be used to describe the overall smoke distribution.

Using a new fiber electrode technology, currently developed and produced by Bekaert Corporation (Bekaert), Electro Energy, Inc., (EEI) Mobile Energy Products Group (formerly, Eagle-Picher Technologies, LLC, Power Systems Department) in Colorado Springs, CO has demonstrated that it is feasible to manufacture flight weight nickel hydrogen cells having about twice the specific energy (80 vs. 40 watt-hr./kg) as state-of-the-art nickel hydrogen cells that are currently flown on geosynchronous communications satellites. Although lithium-ion battery technology has made large in-roads to replace the nickel alkaline technology (nickel-cadmium, nickel-metal hydride), the technology offered here competes with lithium-ion weight and offers alternatives not present in the lithium-ion chemistry such as: ability to undergo a continuous overcharge, reversal on discharge, and sustain rate capability sufficient to start automotive and aircraft engines at subzero temperatures.

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.

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.

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.

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.

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.

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.