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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9

Measurement of local convective heat transfer coefficients from a smooth and roughened NACA-0012 airfoil - Flight test data

Wind tunnels typically have higher free stream turbulence levels than are found in flight. Turbulence intensity was measured to be 0.5 percent in the NASA Lewis Icing Research Tunnel (IRT) with the cloud making sprays off and around 2 percent with cloud making equipment on. Turbulence intensity for flight conditions was found to be too low to make meaningful measurements for smooth air. This difference between free stream and wind tunnel conditions has raised questions as to the validity of results obtained in the IRT. One objective of these tests was to determine the effect of free stream turbulence on convective heat transfer for the NASA Lewis LEWICE ice growth prediction code. These tests provide in-flight heat transfer data for a NASA-0012 airfoil with a 533 cm chord. Future tests will measure heat transfer data from the same airfoil in the Lewis Icing Research Tunnel. Roughness was obtained by the attachment of small, 2 mm diameter hemispheres of uniform size to the airfoil in three different patterns. Heat transfer measurements were recorded in flight on the NASA Lewis Twin Otter Icing Research Aircraft. Measurements were taken for the smooth and roughened surfaces at various aircraft speeds and angles of attack up to four degrees. Results are presented as Frossling number versus position on the airfoil for various roughnesses and angles of attack.

Van Fossen, G. James↗

Assessment of the Pan-Arctic Accelerated Rate of Sea Ice Decline in CMIP6 Historical Simulations

Abstract Arctic sea ice loss in response to a warming climate is assessed in 42 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Sea ice observations show a significant acceleration in the rate of decline commencing near the turn of the twenty-first century. It is our assertion that state-of-the-art climate models should qualitatively reflect this accelerated trend within the limitations of internal variability and observational uncertainty. Our analysis shows that individual CMIP6 simulations of sea ice depict a wide range of model spread on biases and anomaly trends both across models and among their ensemble members. While the CMIP6 multimodel mean captures the observed sea ice area (SIA) decline relatively well, an individual model’s ability to represent the acceleration in sea ice decline remains a challenge. Seventeen (40%) out of 42 CMIP6 models and 37 (13%) out of the total 286 ensemble members reasonably capture the observed trends and acceleration in SIA decline. In addition, a larger ensemble size appears to increase the odds for a model to include at least one ensemble member skillfully representing the accelerated SIA trends. Simulations of sea ice volume (SIV) show much larger spread and uncertainty than SIA; however, due to limited availability of sea ice thickness data, these are not as well constrained by observations. Finally, we find that models with more ocean heat transport simulate larger sea ice declines, which suggests an emergent constraint in CMIP6 ensembles. This relationship points to the need for better understanding and modeling of ice–ocean interactions, especially with respect to frazil ice growth.

54 ENVIRONMENTAL SCIENCES↗

Improvements of an ice-phase microphysics parameterization for use in numerical simulations of tropical convection

It is important to properly simulate the extent and ice water content of tropical anvil clouds in numerical models that explicitly include cloud formation because of the significant effects that these clouds have on the radiation budget. For this reason, a commonly used bulk ice-phase microphysics parameterization was modified to more realistically simulate some of the microphysical processes that occur in tropical anvil clouds. Cloud ice growth by the Bergeron process and the associated formation of snow were revised. The characteristics of graupel were also modified in accord with a previous study. Numerical simulations of a tropical squall line demonstrate that the amount of cloud ice and the extent of anvil clouds are increased to more realistic values by the first two changes.

Krueger, Steven K.↗

Fundamental Ice Crystal Accretion Physics Studies

Due to numerous engine power-loss events associated with high-altitude convective weather, ice accretion within an engine due to ice-crystal ingestion is being investigated. The National Aeronautics and Space Administration (NASA) and the National Research Council (NRC) of Canada are starting to examine the physical mechanisms of ice accretion on surfaces exposed to ice-crystal and mixed-phase conditions. In November 2010, two weeks of testing occurred at the NRC Research Altitude Facility utilizing a single wedge-type airfoil designed to facilitate fundamental studies while retaining critical features of a compressor stator blade or guide vane. The airfoil was placed in the NRC cascade wind tunnel for both aerodynamic and icing tests. Aerodynamic testing showed excellent agreement compared with CFD data on the icing pressure surface and allowed calculation of heat transfer coefficients at various airfoil locations. Icing tests were performed at Mach numbers of 0.2 to 0.3, total pressures from 93 to 45 kPa, and total temperatures from 5 to 15 C. Ice and liquid water contents ranged up to 20 and 3 grams per cubic meter, respectively. The ice appeared well adhered to the surface in the lowest pressure tests (45 kPa) and, in a particular case, showed continuous leading-edge ice growth to a thickness greater than 15 millimeters in 3 minutes. Such widespread deposits were not observed in the highest pressure tests, where the accretions were limited to a small area around the leading edge. The suction surface was typically ice-free in the tests at high pressure, but not at low pressure. The icing behavior at high and low pressure appeared to be correlated with the wet-bulb temperature, which was estimated to be above 0 C in tests at 93 kPa and below 0 C in tests at lower pressure, the latter enhanced by more evaporative cooling of water. The authors believe that the large ice accretions observed in the low pressure tests would undoubtedly cause the aerodynamic performance of a compressor component such as a stator blade to degrade significantly, and could damage downstream components if shed.

Currie, Tom↗

Fundamental Ice Crystal Accretion Physics Studies

Due to numerous engine power-loss events associated with high-altitude convective weather, ice accretion within an engine due to ice crystal ingestion is being investigated. The National Aeronautics and Space Administration (NASA) and the National Research Council (NRC) of Canada are starting to examine the physical mechanisms of ice accretion on surfaces exposed to ice-crystal and mixed-phase conditions. In November 2010, two weeks of testing occurred at the NRC Research Altitude Facility utilizing a single wedge-type airfoil designed to facilitate fundamental studies while retaining critical features of a compressor stator blade or guide vane. The airfoil was placed in the NRC cascade wind tunnel for both aerodynamic and icing tests. Aerodynamic testing showed excellent agreement compared with CFD data on the icing pressure surface and allowed calculation of heat transfer coefficients at various airfoil locations. Icing tests were performed at Mach numbers of 0.2 to 0.3, total pressures from 93 to 45 kPa, and total temperatures from 5 to 15 C. Ice and liquid water contents ranged up to 20 and 3 g/m3, respectively. The ice appeared well adhered to the surface in the lowest pressure tests (45 kPa) and, in a particular case, showed continuous leading-edge ice growth to a thickness greater than 15 mm in 3 min. Such widespread deposits were not observed in the highest pressure tests, where the accretions were limited to a small area around the leading edge. The suction surface was typically ice-free in the tests at high pressure, but not at low pressure. The icing behavior at high and low pressure appeared to be correlated with the wet-bulb temperature, which was estimated to be above 0 C in tests at 93 kPa and below 0 C in tests at lower pressure, the latter enhanced by more evaporative cooling of water. The authors believe that the large ice accretions observed in the low pressure tests would undoubtedly cause the aerodynamic performance of a compressor component such as a stator blade to degrade significantly, and could damage downstream components if shed.

Struk, Peter M.↗

The Secret of the Svalbard Sea Ice Barrier

An elongated sea ice feature called the Svalbard sea ice barrier rapidly formed over an area in the Barents Sea to the east of Svalbard posing navigation hazards. The secret of its formation lies in the bottom bathymetry that governs the distribution of cold Arctic waters masses, which impacts sea ice growth on the water surface.

Atlantic waters↗

Microphysical growth state of ice particles and large-scale electrical structure of clouds

Cloud temperature, liquid water content, and vertical air velocity are all considered in evaluating the microphysical growth state of ice phase precipitation particles in the atmosphere. The large-scale observations taken together with in situ measurements indicated that the most prevalent growth condition for large ice particles in active convection is sublimation during riming, whereas the most prevalent growth condition in stratiform precipitation is vapor deposition. The large-scale electrical observations lend further support to the idea that particles warmed by riming into sublimation charge negatively and particles in vapor deposition charge positively in collisions with small ice particles.

Williams, Earle↗

Comparison of LEWICE and GlennICE in the SLD Regime

A research project is underway at the NASA Glenn Research Center (GRC) to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from two different computer programs. The first program, LEWICE version 3.2.2, has been reported on previously. The second program is GlennICE version 0.1. An extensive comparison of the results in a quantifiable manner against the database of ice shapes that have been generated in the GRC Icing Research Tunnel (IRT) has also been performed, including additional data taken to extend the database in the Super-cooled Large Drop (SLD) regime. This paper will show the differences in ice shape between LEWICE 3.2.2, GlennICE, and experimental data. This report will also provide a description of both programs. Comparisons are then made to recent additions to the SLD database and selected previous cases. Quantitative comparisons are shown for horn height, horn angle, icing limit, area, and leading edge thickness. The results show that the predicted results for both programs are within the accuracy limits of the experimental data for the majority of cases.

Wright, William B.↗

User Manual for the NASA Glenn Ice Accretion Code LEWICE. Version 2.2.2

A research project is underway at NASA Glenn to produce a computer code which can accurately predict ice growth under a wide range of meteorological conditions for any aircraft surface. This report will present a description of the code inputs and outputs from version 2.2.2 of this code, which is called LEWICE. This version differs from release 2.0 due to the addition of advanced thermal analysis capabilities for de-icing and anti-icing applications using electrothermal heaters or bleed air applications. An extensive effort was also undertaken to compare the results against the database of electrothermal results which have been generated in the NASA Glenn Icing Research Tunnel (IRT) as was performed for the validation effort for version 2.0. This report will primarily describe the features of the software related to the use of the program. Appendix A of this report has been included to list some of the inner workings of the software or the physical models used. This information is also available in the form of several unpublished documents internal to NASA. This report is intended as a replacement for all previous user manuals of LEWICE. In addition to describing the changes and improvements made for this version, information from previous manuals may be duplicated so that the user will not need to consult previous manuals to use this code.

Wright, William B.↗

User's Manual for LEWICE Version 3.2

A research project is underway at NASA Glenn to produce a computer code which can accurately predict ice growth under a wide range of meteorological conditions for any aircraft surface. This report will present a description of the code inputs and outputs from version 3.2 of this software, which is called LEWICE. This version differs from release 2.0 due to the addition of advanced thermal analysis capabilities for de-icing and anti-icing applications using electrothermal heaters or bleed air applications, the addition of automated Navier-Stokes analysis, an empirical model for supercooled large droplets (SLD) and a pneumatic boot option. An extensive effort was also undertaken to compare the results against the database of electrothermal results which have been generated in the NASA Glenn Icing Research Tunnel (IRT) as was performed for the validation effort for version 2.0. This report will primarily describe the features of the software related to the use of the program. Appendix A has been included to list some of the inner workings of the software or the physical models used. This information is also available in the form of several unpublished documents internal to NASA. This report is intended as a replacement for all previous user manuals of LEWICE. In addition to describing the changes and improvements made for this version, information from previous manuals may be duplicated so that the user will not need to consult previous manuals to use this software.

Wright, William↗

GlennICE 2.2 Capabilities and Results

GlennICE (Glenn Icing Computational Environment) 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 NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations. This paper will document the current capabilities for version 2.1 of this software and provide example cases with comparison to available experimental data.

Icing↗

GlennICE 2.2 Capabilities and Results

GlennICE (Glenn Icing Computational Environment) 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 NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations. This paper will document the current capabilities for version 2.1 of this software and provide example cases with comparison to available experimental data.

Icing↗

GlennICE Manual 4.1.0

GlennICE (Glenn Icing Computational Environment) 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 NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations.

Icing↗

Improvements to GlennICE Collection Efficiency Algorithm

GlennICE (Glenn Icing Computational Environment) 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 NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations. This paper will document recent improvements that reduce the number of trajectories needed to converge on collection efficiency. These improvements are documented using example cases with complex geometries.

Aircraft Icing↗

Improvements to GlennICE Collection Efficiency Algorithm

GlennICE (Glenn Icing Computational Environment) 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 NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations. This paper will document recent improvements that reduce the number of trajectories needed to converge on collection efficiency. These improvements are documented using example cases with complex geometries.

Aircraft Icing↗

Evaluation of a Thermodynamic Ice Crystal Accretion Model using Experimental Data from NASA’s 2nd Fundamental Ice Crystal Icing Test

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.

Ice Crystal Icing↗

Sea Ice Drift Tracks From Autonomous Buoys in the MOSAiC Distributed Network

A network of autonomous, ice-tethered buoys was deployed around the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) experiment in late September 2019 for a year-long drift in the Arctic Transpolar Drift Stream. The buoys were deployed as part of the MOSAiC distributed network (DN) which included 12 multi-instrumented ice stations and an additional 116 GPS buoys distributed primarily within a 40 km radius of the MOSAiC Central Observatory. Buoy coverage within the DN was maintained with additional deployments throughout the year-long drift allowing for collection of data over a full sea ice growth and melt cycle. All GPS position data from buoys deployed within the DN have been assembled and processed into the collection of 216 quality-controlled buoy drift tracks presented in this dataset covering the period 26 September 2019 – 23 May 2021. The drift tracks in this collection are ideal for studies of dynamic sea ice motion around the MOSAiC experiment at cascading spatial scales ranging from 100s of meters to 100s of km.

Angela C. Bliss↗

Three Dimensional Surface Redefinition Method for Computational Ice Accretion Solvers

Computational tools have been increasing in maturity and are thus commonly used in the engineering design process. Advancements in NASA’s current state of the art computational ice accretion tool are required to tackle the icing challenges of tomorrow. GlennICE, a next generation ice accretion solver, is under development at NASA to tackle these challenges. One of the elements of this migration is transitioning from a quasi-three dimensional strip theory based ice accretion methodology to a fully three dimensional methodology. This requires construction of a method to redefine or extrude a discretized or tessellated surface geometry based on the predicted volumetric ice growth for each tessellated surface triangle. This paper describes the methodology that is employed in the GlennICE software, and assesses the performance of the method in replicating a well definied analytical test case.

Computational↗