Results for “ice physics” — Page 3

DOE OSTI2022

Sea Ice Rheology Experiment (SIREx): 1. Scaling and Statistical Properties of Sea-Ice Deformation Fields

As the sea-ice modeling community is shifting to advanced numerical frameworks, developing new sea-ice rheologies, and increasing model spatial resolution, ubiquitous deformation features in the Arctic sea ice are now being resolved by sea-ice models. Initiated at the Forum for Arctic Modeling and Observational Synthesis, the Sea Ice Rheology Experiment (SIREx) aims at evaluating state-of-the-art sea-ice models using existing and new metrics to understand how the simulated deformation fields are affected by different representations of sea-ice physics (rheology) and by model configuration. Part 1 of the SIREx analysis is concerned with evaluation of the statistical distribution and scaling properties of sea-ice deformation fields from 35 different simulations against those from the RADARSAT Geophysical Processor System (RGPS). For the first time, the viscous-plastic (and the elastic-viscous-plastic variant), elastic-anisotropic-plastic, and Maxwell-elasto-brittle rheologies are compared in a single study. We find that both plastic and brittle sea-ice rheologies have the potential to reproduce the observed RGPS deformation statistics, including multi-fractality. Model configuration (e.g., numerical convergence, atmospheric representation, spatial resolution) and physical parameterizations (e.g., ice strength parameters and ice thickness distribution) both have effects as important as the choice of sea-ice rheology on the deformation statistics. It is therefore not straightforward to attribute model performance to a specific rheological framework using current deformation metrics. In light of these results, we further evaluate the statistical properties of simulated Linear Kinematic Features in a SIREx Part 2 companion paper.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗

NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗

NASA NTRSDate not supplied

Utilization of Streamtubes to Analyze the Physical Interaction of a Dispersed Cloud with the CRM65 Hybrid Midspan Model

Recently there have been numerous efforts to identify the relevant icing physics related to the formation of complex three dimensional features, sometimes referred to as ’scallops’, on swept wings. However, much of the physics is still not well understood. This paper computationally investigates the interaction of the icing cloud with the 65 percent Common Research Model (CRM65). Both the interaction with an uniced model, and the interaction with a representative simulated three dimensional ice accretion are analyzed. Preliminary results suggest that the liquid water content increases near the aerodynamic body. For small droplets on the uniced geometry, the particle velocity vector becomes nearly parallel with the aerodynamic model resulting in a low value of collection efficiency. When a three dimensional feature with a length scale much smaller than the leading edge of the airfoil is introduced into the flow, the impingement of small particles can become significantly more perpendicular to the particle velocity vector in the region of these features. Since the liquid water content near the body has increased due to the interaction with the larger scale features of the aerodynamic model, i.e. the leading edge of the swept wing, extremely high collection efficiency is observed. These results suggest that three dimensional features are likely a significant physical driver that should be modeled in some capacity when simulating the impingement of a cloud on an aerodynamic model.

Icing↗

NASA NTRSDate not supplied

Utilization of Streamtubes to Analyze the Physical Interaction of a Dispersed Cloud with the CRM65 Hybrid Midspan Model

Recently there have been numerous efforts to identify the relevant icing physics related to the formation of complex three dimensional features, sometimes referred to as ’scallops’, on swept wings. However, much of the physics is still not well understood. This paper computationally investigates the interaction of the icing cloud with the 65 percent Common Research Model (CRM65). Both the interaction with an uniced model, and the interaction with a representative simulated three dimensional ice accretion are analyzed. Preliminary results suggest that the liquid water content increases near the aerodynamic body. For small droplets on the uniced geometry, the particle velocity vector becomes nearly parallel with the aerodynamic model resulting in a low value of collection efficiency. When a three dimensional feature with a length scale much smaller than the leading edge of the airfoil is introduced into the flow, the impingement of small particles can become significantly more perpendicular to the particle velocity vector in the region of these features. Since the liquid water content near the body has increased due to the interaction with the larger scale features of the aerodynamic model, i.e. the leading edge of the swept wing, extremely high collection efficiency is observed. These results suggest that three dimensional features are likely a significant physical driver that should be modeled in some capacity when simulating the impingement of a cloud on an aerodynamic model.

Icing↗

NASA NTRS2017

Comparisons of Mixed-Phase Icing Cloud Simulations with Experiments Conducted at the NASA Propulsion Systems Laboratory

This paper builds on previous work that compares numerical simulations of mixed-phase icing clouds with experimental data. The model couples the thermal interaction between ice particles and water droplets of the icing cloud with the flowing air of an icing wind tunnel for simulation of NASA Glenn Research Centers (GRC) Propulsion Systems Laboratory (PSL). Measurements were taken during the Fundamentals of Ice Crystal Icing Physics Tests at the PSL tunnel in March 2016. The tests simulated ice-crystal and mixed-phase icing that relate to ice accretions within turbofan engines.

Bartkus, Tadas↗

NASA NTRS2017

Comparisons of Mixed-Phase Icing Cloud Simulations with Experiments Conducted at the NASA Propulsion Systems Laboratory

This paper builds on previous work that compares numerical simulations of mixed-phase icing clouds with experimental data. The model couples the thermal interaction between ice particles and water droplets of the icing cloud with the flowing air of an icing wind tunnel for simulation of NASA Glenn Research Centers (GRC) Propulsion Systems Laboratory (PSL). Measurements were taken during the Fundamentals of Ice Crystal Icing Physics Tests at the PSL tunnel in March 2016. The tests simulated ice-crystal and mixed-phase icing that relate to ice accretions within turbofan engines. Experimentally measured air temperature, humidity, total water content, liquid and ice water content, as well as cloud particle size, are compared with model predictions. The model showed good trend agreement with experimentally measured values, but often over-predicted aero-thermodynamic changes. This discrepancy is likely attributed to radial variations that this one-dimensional model does not address. One of the key findings of this work is that greater aero-thermodynamic changes occur when humidity conditions are low. In addition a range of mixed-phase clouds can be achieved by varying only the tunnel humidity conditions, but the range of humidities to generate a mixed-phase cloud becomes smaller when clouds are composed of smaller particles. In general, the model predicted melt fraction well, in particular with clouds composed of larger particle sizes.

Thermal model↗

NASA NTRS1988

The condensation and vaporization behavior of H2O:CO ices and implications for interstellar grains and cometary activity

IR spectroscopy has been used to ascertain several parameters associated with CO, H2O, and H2O:CO ices' physical behavior. Since CO is noted to be capable of condensing into H2O-rich ices at temperatures that are twice as high as those required for condensation in pure CO, CO is able to condense onto H2O-rich ice grains at temperatures of up to 50 K. CO's presence in H2O ice modestly enhances the effective volatility of the H2O. Attention is given to the implications of these results for cometary models generally and the question of cometary formation specifically.

Sandford, Scott A.↗

NASA NTRS1981

Satellite-derived ice data sets no. 1: Antarctic monthly average microwave brightness temperatures and sea-ice concentrations, 1973 - 1976

A summary data set concerning 4 years of Antarctic sea-ice conditions was created and is available on magnetic tape. The data were derived from electrically scanning microwave radiometer brightness temperatures and were mapped into a polar stereographic grid enclosing the 50 deg S latitude circle. The grid size varies from about 32 by 32 sq km at the poles to about 28 by 28 sq km at 50 deg S. The microwave brightness temperatures of Antarctic sea ice are predominantly characteristic of first-year ice with an emissivity of 0.92 at 19 GHz frequency. Sea ice concentrations were calculated from the brightness temperature data for each grid element with an algorithm that uses an emissivity value of 0.92 and an ice physical temperature estimate from climatological surface air temperatures. Monthly, multiyear monthly, and yearly maps of brightness temperatures and sea ice concentrations were created for the 4 years, except for 7 months for which useable data were insufficient.

Zwally, H. J.↗

NASA NTRS1982

The seasonal and global behavior of water vapor in the Mars atmosphere - Complete global results of the Viking atmospheric water detector experiment

A key question regarding the evolution of Mars is related to the behavior of its volatiles. The present investigation is concerned with the global and seasonal abundances of water vapor in the Mars atmosphere as mapped by the Viking Mars Atmospheric Water Detector (MAWD) instrument for almost 1-1/2 Martian years from June 1976 to April 1979. Attention is given to the implications of the observed variations for determining the relative importance of those processes which may be controlling the vapor cycle on a seasonal basis. The processes considered include buffering of the atmosphere water by a surface or subsurface reservior of ground ice, physically adsorbed water, or chemically bound water. Other processes are related to the supply of water from the residual or seasonal north polar ice cap, the redistribution of the vapor resulting from atmospheric circulation, and control of the vapor holding capacity of the atmosphere by the local atmospheric temperatures.

Jakosky, B. M.↗

NASA NTRS1990

The extraordinary radar echoes from Europa, Ganymede, and Callisto - A geological perspective

Electromagnetic echo-scattering models, empirical and theoretical considerations on regolith formation, and ice physics, are presently invoked in a geologic treatment of the anomalous radar properties of the icy Galilean satellites. These are held to arise because of the electrical differences between ice and silicates, and the absence of icy regoliths' ice-density structures in silicate regoliths. Icy regoliths may uniquely smooth out discontinuities between solid ejecta fragments and more porous surroundings, forming refraction-scattering 'lenses'; high-order multiple scatterings will thereby become more likely responsible for the echoes than low-order scattering.

Ostro, Steven J.↗

NASA NTRS2012

Simulation Tools Model Icing for Aircraft Design

Here s a simple science experiment to try: Place an unopened bottle of distilled water in your freezer. After 2-3 hours, if the water is pure enough, you will notice that it has not frozen. Carefully pour the water into a bowl with a piece of ice in it. When it strikes the ice, the water will instantly freeze. One of the most basic and commonly known scientific facts is that water freezes at around 32 F. But this is not always the case. Water lacking any impurities for ice crystals to form around can be supercooled to even lower temperatures without freezing. High in the atmosphere, water droplets can achieve this delicate, supercooled state. When a plane flies through clouds containing these droplets, the water can strike the airframe and, like the supercooled water hitting the ice in the experiment above, freeze instantly. The ice buildup alters the aerodynamics of the plane - reducing lift and increasing drag - affecting its performance and presenting a safety issue if the plane can no longer fly effectively. In certain circumstances, ice can form inside aircraft engines, another potential hazard. NASA has long studied ways of detecting and countering atmospheric icing conditions as part of the Agency s efforts to enhance aviation safety. To do this, the Icing Branch at Glenn Research Center utilizes a number of world-class tools, including the Center s Icing Research Tunnel and the NASA 607 icing research aircraft, a "flying laboratory" for studying icing conditions. The branch has also developed a suite of software programs to help aircraft and icing protection system designers understand the behavior of ice accumulation on various surfaces and in various conditions. One of these innovations is the LEWICE ice accretion simulation software. Initially developed in the 1980s (when Glenn was known as Lewis Research Center), LEWICE has become one of the most widely used tools in icing research and aircraft design and certification. LEWICE has been transformed over the years from strictly a research tool to one used routinely by industry and other government agencies. Glenn contractor William Wright has been the architect of this development, supported by a team of researchers investigating icing physics, creating validation data, and ensuring development according to standard software engineering practices. The program provides a virtual simulation environment for determining where water droplets strike an airfoil in flight, what kind of ice would result, and what shape that ice would take. Users can enter geometries for specific, two-dimensional cross sections of an airfoil or other airframe surface and then apply a range of inputs - different droplet sizes, temperatures, airspeeds, and more - to model how ice would build up on the surface in various conditions. The program s versatility, ease of use, and speed - LEWICE can run through complex icing simulations in only a few minutes - have contributed to it becoming a popular resource in the aviation industry.

Source record↗

NASA NTRSDate not supplied

Implementation of Interactive Sea Ice Radiative Transfer into the GISS GCM and Its Impact on Sea Ice Simulation

To improve the representation of solar radiation in sea ice in the Goddard Institute for Space Studies (GISS) climate model (ModelE), we have implemented an advanced radiative transfer (RT) scheme to interactively calculate the surface albedo and transmittance of the ice layer and the solar absorption within. The ice physical properties (temperature, salinity, and density), which are simulated by the thermodynamic module in ModelE, are directly used as the input of the RT scheme to determine the inherent optical properties (IOPs) of brine pockets and air bubbles in the ice layers. This provides a more sophisticated, accurate, and complete treatment of sea ice RT for ModelE. The sea ice RT model is also validated with measured spectral albedo and transmittance for different ice types. Compared with ModelE simulations with current radiative parameterization for sea ice, the new RT implementation will slightly increase the ice surface albedo in the summer in the Arctic and greatly increase the radiative transmittance. Consequently, the ice surface melting is reduced and the base melting is increased but the difference in the simulated ice area is small. The effect of this new RT implementation on the Antarctic ice is negligible. The observed decrease in Arctic sea ice extent is well captured by the ModelE simulation.

Sea ice↗

NASA NTRS2006

Microwave Signatures of Snow on Sea Ice: Observations

Part of the Earth Observing System Aqua Advanced Microwave Scanning Radiometer (AMSR-E) Arctic sea ice validation campaign in March 2003 was dedicated to the validation of snow depth on sea ice and ice temperature products. The difficulty with validating these two variables is that neither can currently be measured other than in situ. For this reason, two aircraft flights on March 13 and 19,2003, were dedicated to these products, and flight lines were coordinated with in situ measurements of snow and sea ice physical properties. One flight was in the vicinity of Barrow, AK, covering Elson Lagoon and the adjacent Chukchi and Beaufort Seas. The other flight was farther north in the Beaufort Sea (about 73 N, 147.5 W) and was coordinated with a Navy ice camp. The results confirm the AMSR-E snow depth algorithm and its coefficients for first-year ice when it is relatively smooth. For rough first-year ice and for multiyear ice, there is still a relationship between the spectral gradient ratio of 19 and 37 GHz, but a different set of algorithm coefficients is necessary. Comparisons using other AMSR-E channels did not provide a clear signature of sea ice characteristics and, hence, could not provide guidance for the choice of algorithm coefficients. The limited comparison of in situ snow-ice interface and surface temperatures with 6-GHz brightness temperatures, which are used for the retrieval of ice temperature, shows that the 6-GHz temperature is correlated with the snow-ice interface temperature to only a limited extent. For strong temperature gradients within the snow layer, it is clear that the 6-GHz temperature is a weighted average of the entire snow layer.

Markus, Thorsten↗

NASA NTRSDate not supplied

Aircraft Icing Analysis of Alternatives

This paper provides a description of a recent comprehensive Analysis of Alternatives (AoA) for icing research. A team of NASA icing subject matter experts (SMEs) was assembled from NASA’s Glenn and Langley Research Centers, which began by gathering inputs from icing stakeholders in industry, Government, and academia. Those inputs, which were grouped into a number of themes, were used by the SMEs to identify needed icing technical elements. Each of these high-level technical elements included the icing physics, modeling capabilities, and experimental capabilities needed to address a particular element. A multivariable analysis technique called TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions) was then applied to prioritize the technical elements for several potential future realities. A large number of icing research needs were identified and analyzed to determine the highest priorities for NASA key focus areas and those that will endure into the future. The primary outcome of the AoA is the identification of legacy and newly identified capability areas in priority order to guide future investment.

Icing↗

NASA NTRSDate not supplied

Aircraft Icing Analysis of Alternatives

This paper provides a description of a recent comprehensive Analysis of Alternatives (AoA) for icing research. A team of NASA icing subject matter experts (SMEs) was assembled from NASA’s Glenn and Langley Research Centers, which began by gathering inputs from icing stakeholders in industry, Government, and academia. Those inputs, which were grouped into a number of themes, were used by the SMEs to identify needed icing technical elements. Each of these high-level technical elements included the icing physics, modeling capabilities, and experimental capabilities needed to address a particular element. A multivariable analysis technique called TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions) was then applied to prioritize the technical elements for several potential future realities. A large number of icing research needs were identified and analyzed to determine the highest priorities for NASA key focus areas and those that will endure into the future. The primary outcome of the AoA is the identification of legacy and newly identified capability areas in priority order to guide future investment

Icing, Rotorcraft↗

NASA NTRSDate not supplied

Cloud Uniformity Measurement from NASA's 2nd Fundamental Ice Crystal Icing Test Part 1 (Water Content & PSD)

This paper presents water content and particle measurements from the second Fundamental Ice Crystal Icing Physics test conducted in the NASA Propulsion Systems Laboratory. The water content measurements came from the Science Engineering Associates Multi-Element Probe and the Isokinetic Probe whereas the Artium Technologies, Inc. Phase Doppler Interferometer and High Speed Imaging instruments measured the particle size distribution. Ice particle accretion due to the ingestion of ice-crystals is attributed to numerous jet engine powerloss events. The NASA PSL is an altitude jet-engine test facility which has recently added a capability to inject ice particles into the flow. This work focuses on characterizing the icing cloud by traversing the instruments across the test section at four different conditions where velocity and water content were varied. For this test, the nozzle patterns were selected to make a uniform cloud in the center 6-inch diameter of the test section. Radial trends for the ice and water content measurements are presented and the melt ratio is calculated at the measurement locations. Particle size distributions are also presented. The measured water content, melt ratio, and particle size decreased moving out radially. Measured water content trends show uniformity to within 19.2% for the center 6 inches of the cloud, as intended. In addition, the total water content increased at centerline with velocity, whereas the melt ratio decreased.

Ice-Crystal Icing↗

NASA NTRSDate not supplied

Cloud Uniformity Measurements from NASA's 2nd Fundamental Ice Crystal Icing Test Part 1 (Water Content & PSD)

This paper presents water content and particle measurements from the second Fundamental Ice Crystal Icing Physics test conducted in the NASA Propulsion Systems Laboratory. The water content measurements came from the Science Engineering Associates Multi-Element Probe and the Isokinetic Probe whereas the Artium Technologies, Inc. Phase Doppler Interferometer and High Speed Imaging instruments measured the particle size distribution. Ice particle accretion due to the ingestion of ice-crystals is attributed to numerous jet engine powerloss events. The NASA PSL is an altitude jet-engine test facility which has recently added a capability to inject ice particles into the flow. This work focuses on characterizing the icing cloud by traversing the instruments across the test section at four different conditions where velocity and water content were varied. For this test, the nozzle patterns were selected to make a uniform cloud in the center 6-inch diameter of the test section. Radial trends for the ice and water content measurements are presented and the melt ratio is calculated at the measurement locations. Particle size distributions are also presented. The measured water content, melt ratio, and particle size decreased moving out radially. Measured water content trends show uniformity to within 19.2% for the center 6 inches of the cloud, as intended. In addition, the total water content increased at centerline with velocity, whereas the melt ratio decreased.

Ice-Crystal Icing↗