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Spacecraft radiators reject heat to their surroundings. Radiators can be deployable or mounted on the body of the spacecraft. NASA's Crew Exploration Vehicle is to use body mounted radiators. Coatings play an important role in heat rejection. The coatings provide the radiator surface with the desired optical properties of low solar absorptance and high infrared emittance. These specialized surfaces are applied to the radiator panel in a number of ways, including conventional spraying, plasma spraying, or as an appliqué. Not specifically designed for a weathering environment, little is known about the durability of conventional paints, coatings, and appliqués upon exposure to weathering and subsequent exposure to solar wind and ultraviolet radiation exposure. In addition to maintaining their desired optical properties, the coatings must also continue to adhere to the underlying radiator panel.

The airworthiness authorities (FAA, JAA, Transport Canada) will be releasing a draft rule in the 2006 timeframe concerning the operation of aircraft in a Supercooled Large Droplet (SLD) environment aloft. The draft rule will require aircraft manufacturers to demonstrate that their aircraft can operate safely in an SLD environment for a period of time to facilitate a safe exit from the condition. It is anticipated that aircraft manufacturers will require a capability to demonstrate compliance with this rule via experimental means (icing tunnels or tankers) and by analytical means (ice prediction codes). Since existing icing research facilities and analytical codes were not developed to account for SLD conditions, current engineering tools are not adequate to support compliance activities in SLD conditions. Therefore, existing capabilities need to be augmented to include SLD conditions.

This paper reports on temperature and humidity measurements from a series of ice-crystal icing tunnel experiments conducted in June 2018 at the Propulsion Systems Laboratory at the NASA Glenn Research Center. The tests were fundamental in nature and were aimed at investigating the icing processes on a two-dimensional NACA0012 airfoil subjected to artificially generated icing clouds. Prior to the tests on the airfoil, a suite of instruments, including total temperature and humidity probes, were used to characterize the thermodynamic flow and icing cloud conditions of the facility. Two different total temperature probes were used in these tests which included a custom designed rearward facing probe and a commercial self-heating total temperature probe. The rearward facing probe, the main total temperature probe, is being designed to reduce and mitigate the contaminating effects of icing and ingestion of ice crystals and water droplets at the probe’s inlet.

The Vapor Phase Catalytic Ammonia Removal (VPCAR) system is being developed to recycle water for future NASA Exploration Missions [1,2,3,4,5]. Reduced gravity testing of the VPCAR System has been initiated to identify any potential problems with microgravity operation. Two microgravity testing campaigns have been conducted on NASA's C-9B Reduced Gravity Aircraft. These tests focused on the fluid dynamics of the unit's Wiped-Film Rotating Disk (WFRD) evaporator. The experiments used a simplified system to study the process of forming a thin film on a rotating disk. The configuration simulates the application of feed in the VPCAR's WFRD evaporator. The first round of aircraft testing, which was completed in early 2006, indicated that a problem with microgravity operation of the WFRD existed. It was shown that in reduced gravity the VPCAR wiper did not produce a uniform thin film [6]. The film was thicker near the axis of rotation where centrifugal forces are small.

The NASA Glenn Research Center has been developing a spacecraft open loop spray evaporative heat sink for use in pressure environments near sea-level, where evaporative cooling of water is not effective. The working fluid is R134a, a common refrigerant used in household appliances, considered safe and non-toxic for humans. The concept uses an open loop spray of R134a impinging on a heated flat plate, through which a closed loop of hot coolant flows, having acquired the heat from spacecraft electronics boxes, the cabin heat exchanger, and other heat sources. The latent heat of evaporation cools the outside of the hot plate, and through heat conduction, reduces the temperature of the coolant. The testing at NASA Glenn has used an electrically heated cylindrical copper target to simulate the hot plate. This paper will discuss the R134a feed system, the test matrix, and test results.

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding of high ice water content (HIWC) and develop onboard weather radar processing techniques to detect regions of HIWC ahead of an aircraft to enable tactical avoidance of the potentially hazardous conditions. Both HIWC RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory equipped with a Honeywell RDR-4000 weather radar and in-situ microphysical instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results. The first campaign was conducted in August 2015 with a base of operations in Ft. Lauderdale, Florida.

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.

Numerical solutions have been generated which simulate flow inside an aircraft engine flying at altitude through an ice crystal cloud. The geometry used for this study is the Honeywell Uncertified Research Engine (HURE) which was recently tested in the NASA Propulsion Systems Laboratory (PSL) in January 2018. The simulations were carried out at predicted operating points with a potential risk of ice accretion. The extent of the simulation is from upstream of the engine inlet to downstream past the strut in the core and bypass. The flow solution is produced using GlennHT, a NASA in-house code. A mixing plane approximation is used upstream and downstream of the fan. The use of the mixing plane allows for steady state solutions in the relative frame. The flow solution is then passed on to LEWICE3D for particle trajectory, impact and breakup prediction. The LEWICE3D code also uses a mixing plane approximation at the boundaries upstream and downstream of the fan.

A high-fidelity simulation model for icing effects flight training was developed from wind tunnel data for the DeHavilland DHC-6 Twin Otter aircraft. First, a flight model of the un-iced airplane was developed and then modifications were generated to model the icing conditions. The models were validated against data records from the NASA Twin Otter Icing Research flight test program with only minimal refinements being required. The goals of this program were to demonstrate the effectiveness of such a simulator for training pilots to recognize and recover from icing situations and to establish a process for modeling icing effects to be used for future training devices.

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The most significant developments in the advancement of GlennICE have been investigating the convergence of the collection efficiency, efficiently finding trajectories, and improving the refinement methodology. Such developments have increased the efficiency of GlennICE for practical engineering application. With the increasing demand for applying GlennICE for more memory-intensive problems, the scalability of GlennICE has yet to be investigated. This paper is aimed at presenting a method to benchmark the scalability of GlennICE utilizing a relevant engineering problem within a parallel environment.

This paper reviews work conducted in the UK aimed at developing validated methods to simulate ice accretion formed in super-cooled large droplet (SLD) icing conditions. To date, QinetiQ has completed one theoretical and three experimental programmes of work. Two further studies are currently in progress within UK universities. This paper provides results from the third test conducted by QinetiQ and NASA in the GKN Aerospace Composite Technologies Icing Research Wind Tunnel, Luton UK, to measure the mass loss through droplet splash during an SLD encounter. A description of the test procedures and the results obtained are provided. Future work on SLD methods development in progress in the UK is then briefly outlined.

This work presents the development of a Rotating Rig Facility by the Instituto Nacional de Técnica Aeroespacial (INTA) in cooperation with the NASA Glenn Research Center. The facility is located at the INTA installations near Madrid, Spain. It has been designed to study the deformation, breakup and impact of large droplets induced by aerodynamic bodies. The importance of these physical phenomena is related to the effects of Supercooled Large Droplets in icing clouds on the impinging efficiency of the droplets on the body that may change should these phenomena not be taken into account. The important variables and the similarity parameters that enter in this problem are presented. The facility's components are described and some possible setups are explained. Application examples from past experiments are presented in order to indicate the capabilities of the new facility.

This paper presents a review of our current experimental and theoretical understanding of icing feathers and the role that they play in the formation of ice accretions. It covers the following areas: a short review of past research work related to icing feathers; a discussion of the physical characteristics and terminology used in describing icing feathers; the presence of feathers on ice accretions formed in unswept airfoils, especially at SLD conditions; the role that icing feathers play in the formation of ice accretion shapes on swept wings; the formation of icing feathers from roughness elements; theoretical considerations regarding feather formation, feather interaction to form complex icing structures, the role of film dynamics in the formation of roughness elements and the formation of feathers. Hypotheses related to feather formation and feather growth are discussed.

Computational ice shapes were generated on the boundary layer ingesting engine nacelle of the D8 Double Bubble aircraft. The computations were generated using LEWICE3D, a well-known CFD icing post processor. A 50-bin global drop diameter discretization was used to capture the collection efficiency due to the direct impingement of water onto the engine nacelle. These discrete results were superposed in a weighted fashion to generate six drop size distributions that span the Appendix C and O regimes. Due to the presence of upstream geometries, i.e. the fuselage nose, the trajectories of the water drops are highly complex. Since the ice shapes are significantly correlated with the collection efficiency, the upstream fuselage nose has a significant impact on the ice accretion on the engine nacelle. These complex trajectories are caused by the ballistic nature of the particles and are thus exacerbated as particle size increases.

An experiment was conducted in the Icing Research Tunnel (IRT) at NASA Glenn Research Center to study the effect of sweep angle and temperature on the formation of ice accretions on a NACA 0012 swept wing at SLD conditions. From a baseline Appendix-C condition with a MVD of 20m the drop size was changed to 110 and 200m for the SLD cases. Casting data, ice shape tracings, time-sequence and photographic data were obtained. Time-sequence photography was taken during each run to capture in real time the formation of the ice accretion. Measurements of the critical distance were obtained.

To support NASA's goal to improve aviation safety, the Aircraft Icing Project of the Aviation Safety Program has developed a number of education and training aids for pilots and operators on the hazards of atmospheric icing. A review of aircraft incident and accident investigations has revealed that flight crews have not always understood the effects of ice contamination on their aircraft. To increase this awareness, NASA has partnered with regulatory agencies and pilot trade organizations to assure relevant and practical materials that are focused toward the intended pilot audience. A number of new instructional design approaches and media delivery methods have been introduced to increase the effectiveness of the training materials by enhancing the learning experience, expanding user interactivity and participation, and, hopefully, increasing learner retention rates.

The International Space Station Carbon Dioxide Removal Assembly (CDRA) uses regenerable adsorption technology to remove carbon dioxide (CO2) from cabin air. CO2 product water vapor measurements from a CDRA test bed unit at the NASA Marshall Space Flight Center were made using a tunable infrared diode laser differential absorption spectrometer (TILDAS) provided by NASA Glenn Research Center. The TILDAS instrument exceeded all the test specifications, including sensitivity, dynamic range, time response, and unattended operation. During the CO2 desorption phase, water vapor concentrations as low as 5 ppmv were observed near the peak of CO2 evolution, rising to levels of ∼40 ppmv at the end of a cycle. Periods of high water concentration (>100 ppmv) were detected and shown to be caused by an experimental artifact.

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.

From November 2010 until May of 2011, NASA's Icing Remote Sensing System was positioned at Platteville, Colorado between the National Science Foundation's S-Pol radar and Colorado State University's CHILL radar (collectively known as FRONT, or ‘Front Range Observational Network Testbed’). This location was also underneath the flight-path of aircraft arriving and departing from Denver's International Airport, which allowed for comparison to pilot reports of in-flight icing. This work outlines how the NASA Icing Remote Sensing System's derived liquid water content and in-flight icing hazard profiles can be used to provide in-flight icing verification and validation during icing and non-icing scenarios with the purpose of comparing these times to profiles of polarized moment data from the two nearby research radars.

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.