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A detailed survey of ice mold and evaporator metal surfaces, physical structures, operational conditions, materials of construction, design of different equipment was reviewed and analyzed. The key objective was to identify different ice related processes’ materials, structures, and operating conditions for designing, optimizing, and applying advance materials to lower ice adhesion strength.
The primary objective of this project was to facilitate the dislocation of the interfacial ice layer by employing advanced materials and ultrasonic vibration to reduce ice adhesion strength. This work employed two technical approaches that were thoroughly investigated and previously reported. The effectiveness of these approaches, both individually and in combination, has been quantified, demonstrating notable energy savings. The projected payback period for these enhancements is approximately 2.2 years or less, contingent upon specific energy costs. Furthermore, these advancements hold significant promise for reducing carbon emissions across various equipment scales. This study particularly focused on the ultrasonic deicing technique for diverse structures, utilizing numerical simulations to evaluate performance and potential benefits.
Dynamic Coatings, Inc., wanted to test coating products that would enable the company to approach new markets. A Space Act Agreement with NASA Lewis Research Center afforded them this opportunity. They used Lewis' Icing Research Tunnel to test coating products for reduced ice adhesion, industrial and aerospace lubrication applications, a tiremold release coating now used in the production of tires for the Boeing 777, and a product that solidifies asbestos fibers (which is being tested as an insulator in a power plant in Iowa). Not only was the testing a success, but during these activities, Dynamic Coatings met another coating company with whom they now have a joint venture offering a barnacle-repellent coating for marine applications, now on the market in Florida.
Topics covered include: Control Architecture for Robotic Agent Command and Sensing; Algorithm for Wavefront Sensing Using an Extended Scene; CO2 Sensors Based on Nanocrystalline SnO2 Doped with CuO; Improved Airborne System for Sensing Wildfires; VHF Wide-Band, Dual-Polarization Microstrip-Patch Antenna; Onboard Data Processor for Change-Detection Radar Imaging; Using LDPC Code Constraints to Aid Recovery of Symbol Timing; System for Measuring Flexing of a Large Spaceborne Structure; Integrated Formation Optical Communication and Estimation System; Making Superconducting Welds between Superconducting Wires; Method for Thermal Spraying of Coatings Using Resonant-Pulsed Combustion; Coating Reduces Ice Adhesion; Hybrid Multifoil Aerogel Thermal Insulation; SHINE Virtual Machine Model for In-flight Updates of Critical Mission Software; Mars Image Collection Mosaic Builder; Providing Internet Access to High-Resolution Mars Images; Providing Internet Access to High-Resolution Lunar Images; Expressions Module for the Satellite Orbit Analysis Program Virtual Satellite; Small-Body Extensions for the Satellite Orbit Analysis Program (SOAP); Scripting Module for the Satellite Orbit Analysis Program (SOAP); XML-Based SHINE Knowledge Base Interchange Language; Core Technical Capability Laboratory Management System; MRO SOW Daily Script; Tool for Inspecting Alignment of Twinaxial Connectors; An ATP System for Deep-Space Optical Communication; Polar Traverse Rover Instrument; Expert System Control of Plant Growth in an Enclosed Space; Detecting Phycocyanin-Pigmented Microbes in Reflected Light; DMAC and NMP as Electrolyte Additives for Li-Ion Cells; Mass Spectrometer Containing Multiple Fixed Collectors; Waveguide Harmonic Generator for the SIM; Whispering Gallery Mode Resonator with Orthogonally Reconfigurable Filter Function; Stable Calibration of Raman Lidar Water-Vapor Measurements; Bimaterial Thermal Compensators for WGM Resonators; Root Source Analysis/ValuStream[Trade Mark] - A Methodology for Identifying and Managing Risks; Ensemble: an Architecture for Mission-Operations Software; Object Recognition Using Feature-and Color-Based Methods; On-Orbit Multi-Field Wavefront Control with a Kalman Filter; and The Interplanetary Overlay Networking Protocol Accelerator.
A review of various methods to prevent ice formation and adhesion to aircraft surfaces is given. It was concluded that the adhesion of ice to a surface may be reduced somewhat by the application of certain waxes and varnishes. In the experiments described, the varnishes containing calcium stearate and calcium oleate gave the best results. In wind tunnel tests, the adhesion was further reduced by the application of these waxes and varnishes to a thin, heat insulating layer of rubber. The adhesion of ice is greatly reduced when the surface consists of a vehicle which carries an oil in sufficient quantity so that the surface of the vehicle is self lubricating. Ice may be removed from wings, struts, wires and other parts of an airplane during flight by the inflation of properly constructed pneumatic rubber members, providing that these members have been previously treated with a suitable low adhesion oil.
Numerous methodologies have been utilized to measure the adhesion strength of impact ice, and the data reported in the literature varies significantly from test to test. In order to initiate an investigation to determine the cause of this disparity, a new test methodology has been developed and utilized in the Icing Research Tunnel at the NASA Glenn Research Center. Data was obtained while varying the temperature, test section velocity, and cloud droplet mean volumetric diameter. The first data set acquired using this new test method is presented. New trends demonstrate the effect of annealing ice samples, with temperature being a key variable. Observations during the test and analysis of the results suggest the presence of large residual stresses in the samples.
Aircraft icing has long presented a safety hazard to the aerospace industry. One problem inherent to aircraft icing is predicting the adhesive properties of the ice-aircraft interface; values commonly reported span multiple orders of magnitude, making shedding prediction and surface evaluation difficult. An effort has been undertaken at the NASA Glenn Research Center to understand the cause of the scatter in the data. Geometry dependencies, variation in testing procedures, and residual stresses in ice samples have previously been identified as significant contributors to the problem. Residual stresses were singled out for this study, which investigated the strains at the leading edge of a Common Research Model (CRM) wind tunnel model in the NASA Glenn Icing Research Tunnel. Sprays were conducted at a particle size median volumetric diameter (MVD) of 20 µm, with liquid water contents (LWC) spanning from 0.4 to 3.0 g/m3. Total temperatures were varied between 0 and -25 °C, and test section velocity between 51 and 118 m/s. The leading edge was instrumented with custom strain gages, resistance temperature detectors (RTDs), optical fibers, and a pressure mat. Results indicate Δ strains, which were the difference between recorded strains and those predicted from isotropic thermal expansion of aluminum, below -400 µε with consistent patterns of strain across a wide variety of tunnel conditions. Isotropic, linear elastic finite element analysis (FEA) was conducted by varying the temperature of simplified airfoil and ice geometries, producing similar strains to those observed in testing. This allowed induced stresses to be predicted. Predicted stresses were above the expected tensile strength for ice, and suggest a source for previously observed cracking in tunnel ice.
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To design effective anti-icing and de-icing technology for aircraft, scientists and engineers must obtain a fundamental understanding of the microstructural characteristics of impact ice. This study investigates the effects of icing parameters, such as airspeed and liquid water content (LWC), on impact ice microstructure near the interface to a metal substrate. Ice samples were accreted in the NASA Glenn Icing Research Tunnel and tested in the NASA Revolutionary Icing Materials Evaluation Laboratory. A microtome was used to shave down the ice to a thickness of < 1 mm for examination under a microscope. Samples were imaged at multiple magnifications using bright field imaging. The average grain size was determined for each sample in accordance with ASTM standard methods, and relationships between airspeed, LWC, and grain size were identified. It was observed that the average grain area in a given cross-section was linearly related to the distance of the cross-section from the metal surface. Finally, the effects of annealing and sublimation on the microstructure were also explored. Results show significant variation in the grain structure, suggesting a means by which icing condition influences adhesion strength.
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A process of using machine learning to segment impact ice microstructure is presented and analyzed. 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. Results show promise in accuracy as well as a possible improvement in repeatability and consistency. Next steps for improving the model are suggested.
Coating materials consisting mostly of modified polyphosphazene (Class FZ) elastomers provide better protection against icing than fluorocarbon polymers and silicone elastomers. Reduces adhesive force between ice and surface. As consequence, increasing weight of ice, wind loading, or vibration of surface causes ice to be shed. New icephobic coats reduce accumulation of ice on aircraft, radomes, antennas, ships, and power-transmission lines.
A thermodynamic model describing ice crystal icing is evaluated using experimental data collected at NASA Propulsion Systems Laboratory. The model makes the distinction between ice accretions that are "freeze-dominated" and "melt-dominated". Freeze-dominated icing occurs when partially melted ice crystals impact a surface and freeze. This type of icing is characterized by strong adhesion. This contrasts with melt-dominated icing, where un-melted ice crystals adhere to a surface. This type of icing is characterized by weak adhesion. In this paper, the thermodynamic model is used to analyze the ice growth rates and facility conditions to explain possible phenomena such as mass loss as well as the melting and freezing fractions. Previous analyses assumed a collection efficiency of unity at the leading edge of the experimental model. LEWICE is used to determine a better estimate of the collection efficiency at the model leading edge as ice accretion grows in time. The result shows that the sticking efficiency could change in a greater percent with time than previously reported.
This paper presents the evaluation of a thermodynamic ice crystal icing model, previously presented to describe the possible mechanisms of icing within the core of a turbofan jet engine. It has been proposed that there are two types of distinct ice accretions based on a surface energy balance: freeze-dominated icing and melt-dominated icing. In the former, ice accretion occurs where a freeze fraction (0 to 1) of melted ice crystals freezes on a surface, along with the existing ice of the impinging water and ice mass. This freeze-dominated icing is characterized by having strong adhesion to the surface. In the latter, icing occurs from accumulated unmelted ice on a surface, where a melt fraction (0 to 1) dictates the amount of unmelted impinged ice. This melt-dominated icing is characterized by weakly bonded surface adhesion. The experimentally observed ice growth rates suggest that only a small fraction of the impinging ice remains on the surface, implying a mass loss mechanism such as splash, runback, bounce, or erosion. This mass loss parameter must be determined in conjunction with the fraction of freezing liquid water or fraction of melting ice on an icing surface. This loss parameter, however, along with the freeze and melt fraction, are the only experimental parameters that are currently not measured directly. Using reported icing growth rates from published ice crystal icing experiments, a methodology is proposed to determine these unknown parameters. This work takes reported ice accretion data from tests conducted by the National Aeronautics and Space Administration (NASA) in 2016 and tests NASA collaborated on with the National Research Council (NRC) of Canada in 2012 that examined the fundamental physics of ice crystal icing. Those research efforts sought to generate icing conditions representative of those that occur inside a jet engine when ingesting ice crystals. This paper presents the fundamental equations of the thermodynamic model, the methodology used to determine the aforementioned unknown icing parameters, and results from model evaluation using experimental data. In addition, this paper builds on the previously proposed model by adding a transient conduction term to explain ice growth behavior at the onset of experimental tests that was observed to be different from steady-state ice growth that occurred later in the test run.With the addition of this energy term, this becomes a quasi-steady model. A key finding from this work suggests that mass loss fractions can exceed 0.90 for steady ice growth periods. In addition, due to conductive heat fluxes when using a warmer-than-freezing airfoil, lower mass loss fraction values were calculated during the initial transient period.
This paper evaluates a thermodynamic ice crystal icing model that has been previously presented to describe the possible mechanisms of icing within the core of a turbofan jet engine. The model functions between two distinct ice accretions based on a surface energy balance: freeze-dominated icing and melt-dominated icing. Freeze-dominated icing occurs when liquid water (from melted ice crystals) freezes and accretes on a surface along with the existing ice of the impinging water and ice mass. This freeze-dominated icing is characterized as having strong adhesion to the surface. The amount of ice accretion is partially dictated by a freeze fraction, which is the fraction of impinging liquid water that freezes. Melt-dominated icing occurs as unmelted ice on a surface accumulates. This melt-dominated icing is characterized by weakly bonded surface adhesion. The amount of ice accumulation is partially dictated by a melt fraction, which is the fraction of impinging ice crystals that melts. Experimentally observed ice growth rates suggest that only a small fraction of the impinging ice remains on the surface, implying a mass loss mechanism such as splash, runback, bounce, or erosion. The fraction of mass loss must be determined in conjunction with the fraction of freezing liquid water or fraction of melting ice on an icing surface for a given ice growth rate. This mass loss parameter, however, along with the freeze fraction and melt fraction, are the only experimental parameters that are currently not measured directly. Using icing growth rates from ice crystal icing experiments, a methodology that has been previously proposed is used to determine these unknown parameters. This work takes ice accretion data from tests conducted by the National Aeronautics and Space Administration (NASA) at the Glenn Research Center in 2018 that examined the fundamental physics of ice crystal icing. This paper continues evaluation of the thermodynamic model from a previous effort, with additions to the model that account for sub-freezing temperatures that have been observed at the leading edge of the airfoil during icing. The predicted temperatures were generally in good agreement with measured temperatures. Other key findings include the total wet-bulb temperature being a good first order indicator of whether icing is freeze-dominated (sub-freezing values) or melt-dominated (above freezing). Maximum sticking efficiency values, the fraction of impinging mass that adheres to a surface, was calculated to be about 0.2, and retained this maximum value for a range of melt ratios (0.3 to 0.65 and possibly higher), which is defined as the ratio of liquid water content to total water content. Higher air velocities reduced the maximum sticking efficiency and shifted the icing regime to higher melt ratio values. Finally, the leading edge ice accretion angle was found to be related to ice growth (lower growth rates for smaller angles) and melt ratio (smaller melt ratios resulted in smaller angles, likely due to erosion effects).
Calculations for ice accretion and shedding are presented for a model scale rotor in hover. The aerodynamic characteristics of the rotor are first computed using a combined blade element-momentum theory. The effective angles of attack, and the local flow velocity are used within the NASA Glenn solver LEWICE to estimate the collection efficiency. The computed convection efficiency and the surface pressure distribution from a panel method within LEWICE are used to estimate the ice accretion over the rotor blades over an elapsed time interval. Finally, a force balance approach is used to establish shedding events where the centrifugal force over the ice mass exceeds the adhesive forces at the rotor surface and the cohesive forces between adjacent masses of ice. Preliminary comparisons with test data acquired at the Pennsylvania State Icing Research Tunnel are presented. Sensitivity of the ice shedding events to surface roughness, adhesive strength, cohesive strength, and ambient conditions is discussed.
NASA’s approach to computational materials modeling is detailed in the NASA Vision 2040 Roadmap for Multiscale Modeling and Simulation of Materials and Systems. This report is in the spirit of national initiatives such as the Material Genome Initiative (MGI), Integrated Computational Materials Engineering (ICME), and others. We utilize a combination of fundamental modeling, computational high-throughput screening, and data science methods, e.g., machine learning, are used to find innovative solutions to NASA or national technology challenges. Applications of interest are wide ranging from advanced alloys to batteries to coatings, among others. In this talk, we present three examples for recent work related to NASA applications. First, doping advanced sulfur battery cathodes with selenium boosts electrical conductivity important for electric aircraft applications. First principles calculations will be discussed that result in compositional design maps for these materials. Second, development of icephobic coatings is important to mitigate safety hazards associated with icing for aircraft. Molecular dynamics simulations are reported for ice-surface interfaces to understand adhesion mechanisms and help screen optimal ice-phobic coatings. Third, shape memory alloys have numerous applications as actuators, superelastic materials, etc. for aerospace. We report machine learning models that predict martensitic transition temperatures across a broad swath of compositional space.