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At least 1,135 records · Page 63

Large-Drop Ice Accretion Test Results for a Large Scale Swept Wing Section

In-flight icing is an important consideration that affects aircraft design, performance and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of ice accretion testing conducted in the NASA Icing Research Tunnel on a large swept wing typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small MVD = 25 μm and a large MVD = 110 μm. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. The results for the small MVD cloud conditions were consistent with previous work and showed the changing ice morphology from rime ice at colder temperatures to highly 3D scallop ice in the range of -8.7 ˚C to -3.8 ˚C. The results for the large MVD cloud conditions exhibited some differences in the ice accretion morphology. Scallop-like ice features were observed at total temperature of -3.8˚C. The large MVD ice accretion at lower temperatures tended to be smoother than the corresponding ice accretion for small MVD. The thickness of the main ice shape tended to be larger for the small MVD conditions compared to the corresponding large MVD ice shape while the latter had more ice farther downstream. The measured ice mass was approximately equal between the corresponding small and large MVD ice shapes up to a freezing fraction of 0.6. For higher freezing fraction, the large MVD ice shapes weighed more. Cloud MVD variation from 50 μm to 230 μm while holding the scaling parameters constant resulted in very minor differences in the ice shapes, mostly in the upper and lower surface chordwise extents. Ice volume was computed from 3D scan data and used to calculate a ratio of ice mass to volume. The resulting values were in the range of 240 to 455 Kg/m3. While this is consistent with analogous values previously reported in the literature, more data are needed to determine a specific trend in this ratio as a function of freezing fraction and the corresponding governing physical phenomena. This work has resulted in a significant experimental database of ice accretion for small and large MVD conditions applicable to large-scale swept wings.

Icing↗

ISRU Pilot Excavator: Bucket Drum Scaling Experimental Results

NASA’s Space Technology Mission Directorate (STMD) is funding the development of a robotic excavator called the “ISRU Pilot Excavator” which will be a technology demonstration of excavating and transporting 10 metric tons of lunar regolith on the surface of the moon with a 30k-class robotic excavator. ISRU Pilot Excavator will be the next generation of robotic excavator to use bucket drums as excavation tools. This is an evolution of the Regolith Advanced Surface Systems Operations Robot (RASSOR) developed at NASA’s Kennedy Space Center. Bucket drums are hollow cylinders with regularly spaced scoops around the perimeter. The drums rotate in one direction to collect regolith with the scoops. The regolith slides down an internal baffling system inside the drum which prevents the regolith from falling back out of the scoops. The captured regolith can then be transported while held in the drum and then deposited by rotating the drum in the opposite direction allowing the regolith to slide back down the baffling and out of the excavation scoops. Bucket drums were developed by Lockheed Martin in 2008 and used on multiple robotic excavator prototypes ever since. However the forces on a bucket drum and considerations for scaling have not been measured in detail. Bucket drums are challenging to model using classical blade\bucket equations because of their unique geometry. Therefore this experiment was performed to measure the forces on three bucket drums of the same geometry at different scales. Small: 9.4” (239mm) dia. x 8.1” (206mm) width, Medium: 11.6” (294mm) dia. x 10” (254mm) width, and Large: 17” (432mm) dia. x 14.1”(358mm) width. The test stand consisted of an actuated gantry with controlled motion in the vertical (Z) and horizontal (X) axes and a single rotation axis (R). The bucket drums were individually mounted to the rotary axis of the test stand and translated across a prepared bed of BP-1 lunar regolith simulant at a specified linear speed and cutting depth. The test stand was outfitted with a torque sensor in line with the rotation of the drum (R) and a 3 axis (X, Y, and Z) load cell. In addition to the three sizes of bucket drums the linear excavation speed and cutting depth were test variables. The results of these experiments show the relationship between the three scales of bucket drums for factors such as: excavation force, torque due to regolith rotation inside the drum, excavation energy, time to fill, etc. and will be discussed in detail in this paper. This fundamental data will be used in the design of the ISRU Pilot Excavator and can inform the design of future bucket drum excavators.

Jason Michael Schuler↗

ISRU Pilot Excavator: Bucket Drum Scaling Experimental Results

NASA’s Space Technology Mission Directorate (STMD) is funding the development of a robotic excavator called the “ISRU Pilot Excavator” (IPEx) which will be a technology demonstration of excavating and transporting 10 metric tons of lunar regolith on the surface of the moon with a 30kg-class robotic excavator. IPEx will be the next generation of robotic excavators to use bucket drums as excavation tools. This is an evolution of the Regolith Advanced Surface Systems Operations Robot (RASSOR) developed at NASA’s Kennedy Space Center (KSC). Bucket drums are hollow cylinders with regularly spaced scoops around the perimeter. The drums rotate in one direction to collect regolith with the scoops. The regolith slides down an internal baffling system inside the drum which prevents the regolith from falling back out of the scoops (see Figure 1). The captured regolith can then be transported while held in the drum and then deposited by rotating the drum in the opposite direction allowing the regolith to slide back down the baffling and out of the excavation scoops. Bucket drums were developed by Lockheed Martin in 2008 and used on multiple robotic excavator prototypes ever since. However, the forces on a bucket drum and considerations for scaling have not been measured in detail. Bucket drums are challenging to model using classical blade\bucket equations because of their unique geometry. Therefore, this experiment was performed to measure the forces on three bucket drums of the same geometry at different scales. Small: 9.4” (239mm) dia. x 8.1” (206mm) width, Medium: 11.6” (294mm) dia. x 10” (254mm) width, and Large: 17” (432mm) dia. x 14.1” (358mm) width. The test stand consisted of an actuated gantry with controlled motion in the vertical (Z) and horizontal (X) axes and a single rotation axis (R). The bucket drums were individually mounted to the rotary axis of the test stand and translated across a prepared bed of BP-1 lunar regolith simulant at a specified linear speed and cutting depth. The test stand was outfitted with a torque sensor in line with the rotation of the drum (R) and a 3 axis (X, Y, and Z) load cell. In addition to the three sizes of bucket drums the linear excavation speed and cutting depth were test variables. The results of these experiments show the relationship between the three scales of bucket drums for factors such as: excavation force, torque due to regolith rotation inside the drum, excavation energy, time to fill, etc. and will be discussed in detail in this paper. This fundamental data will be used in the design of IPEx and can inform the design of future bucket drum excavators.

RASSOR↗

The Earth Model Column Collaboratory (EMC2) v1.1: An Open-Source Ground-Based Lidar and Radar Instrument Simulator and Subcolumn Generator for Large-Scale Models

Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

Earth Model Column Collaboratory↗

Satellites quantify the spatial extent of cyanobacterial blooms across the United States at multiple scales

Previous studies indicate that cyanobacterial harmful algal bloom (cyanoHAB) frequency, extent, and magnitude have increased globally over the past few decades. However, little quantitative capability is available to assess these metrics of cyanoHABs across broad geographic scales and at regular intervals. Here, the spatial extent was quantified from a cyanobacteria algorithm applied to two European Space Agency satellite platforms—the MEdium Resolution Imaging Spectrometer (MERIS) onboard Envisat and the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3. CyanoHAB spatial extent was defined for each geographic area as the percentage of valid satellite pixels that exhibited cyanobacteria above the detection limit of the satellite sensor. This study quantified cyanoHAB spatial extent for over 2,000 large lakes and reservoirs across the contiguous United States (CONUS) during two time periods: 2008–2011 via MERIS and 2017–2020 via OLCI when cloud-, ice-, and snowfree imagery was available. Approximately 56% of resolvable lakes were glaciated, 13% were headwater, isolated, or terminal lakes, and the rest were primarily drainage lakes. Results were summarized at national-, regional-, state-, and lake-scales, where regions were defined as nine climate regions which represent climatically consistent states. As measured by satellite, changes in national cyanoHAB extent did have a strong increase of 6.9% from 2017 to 2020 (|Kendall’s tau (τ)| = 0.56; gamma (γ) = 2.87 years), but had negligible change (|τ| = 0.03) from 2008 to 2011. Two of the nine regions had moderate (0.3 ≤ |τ| < 0.5) increases in spatial extent from 2017 to 2020, and eight of nine regions had negligible (|τ| < 0.2) change from 2008 to 2011. Twelve states had a strong or moderate increase from 2017 to 2020 (|τ| ≥ 0.3), while only one state had a moderate increase and two states had a moderate decrease from 2008 to 2011. A decrease, or no change, in cyanoHAB spatial extent did not indicate a lack of issues related to cyanoHABs. Sensitivity results of randomly omitted daily CONUS scenes confirm that even with reduced data availability during a short four-year temporal assessment, the direction and strength of the changes in spatial extent remained consistent. We present the first set of national maps of lake cyanoHAB spatial extent across CONUS and demonstrate an approach for quantifying past and future changes at multiple spatial scales. Results presented here provide water quality managers information regarding current cyanoHAB spatial extent and quantify rates of change.

Harmful algal blooms↗

Characteristics of Multi-scale Current Sheets in the Solar Wind at 1 au Associated with Magnetic Reconnection and the Case for a Heliospheric Current Sheet Avalanche

Wind spacecraft measurements are analyzed to obtain a current sheet (CS) normal width dcs-distribution of 3374 confirmed magnetic reconnection exhausts in the ecliptic plane of the solar wind at 1 AU. The dcs-distribution displays a nearly exponential decay from a peak at dcs=25 di to a median at dcs=85 di and a 95th percentile at dcs=905 di with a maximum exhaust width at dcs=8077 di. A magnetic field ϴ-rotation angle distribution increases linearly from a relatively few high-shear events toward a broad peak at 35o<ϴ<65o. The azimuthal φ-angles of the CS normal directions of 430 thick dcs≥500 di exhausts are consistent with a dominant Parker-spiral magnetic field and a CS normal along the ortho-Parker direction. The CS normal orientations of 370 kinetic-scale dcs<25 di exhausts are isotropic in contrast, and likely associated with Alfvénic solar wind turbulence. We propose that the alignment of exhaust normal directions from narrow dcs~15-25 di widths to well beyond dcs~500 di with an ortho-Parker azimuthal direction of a large-scale HCS is a consequence of CS bifurcation and turbulence within the HCS exhaust that may trigger reconnection of the adjacent pair of bifurcated CSs. The proposed HCS-31 avalanche scenario suggests that the underlying large-scale parent HCS closer to the Sun evolves with heliocentric distance to fracture into many, more or less aligned, secondary current sheets due to reconnection. A few wide exhaust-associated HCS-like CSs could represent a population of HCSs that failed to reconnect as frequently between the Sun and 1 AU as other HCSs.

Stefan Eriksson↗

Cross-Scale and Cross-Interface Processes and Arctic Amplification

The Arctic is a dynamic region, demonstrated by its remarkable internal variability and rapid response to anthropogenic climate change over the last 40 years. Actionable predictions and projections hold significant value for managing both natural and human systems. The value of these model outputs only grows in a warmer, less icy Arctic. However, substantial gaps exist in our understanding of cross-scale and cross-interface (air-sea ice-ocean) interactions that limit our predictive capabilities. Studies dating back at least 40 years provide evidence that the evolution of the Arctic climate system is sensitive to these cross-scale and cross-interface interactions. This presentation summarizes our understanding of cross-scale and cross-interface interactions relevant to the Arctic’s response to anthropogenic climate change—Arctic Amplification. The presentation emphasizes the influence of surface-type dependent turbulent flux exchanges of heat and moisture, the rectification of episodic atmospheric heat transport events on time-averaged changes, local and remote feedback interactions, and cross-seasonal energy transfers. The presentation concludes with a summary of knowledge gaps and discusses potential pathways for accelerating our understanding of the Arctic climate system.

Patrick C. Taylor↗

Space Weather Modeling and Prediction for Intermediate Time-scales

Much of solar activity within a sunspot cycle occurs as bursts, or 'seasons' of strong activity over several months, separated by periods of much less activity. The most important space weather effects occur during these bursts. Previous modeling and forecasting efforts have focused on time-scales of hours-to-days and decades-to-centuries. The recent discovery of Rossby waves in the Sun, together with recently developed global models of solar MHD Rossby waves and their interactions with differential rotation and spot-producing magnetic fields, reveal the opportunity to simulate and predict the occurrence, strength and location of enhanced activity bursts a few weeks up to several months in advance. We now have a golden opportunity to fill in this gap in time-scales of forecasting space weather. This requires a) continuous observations of solar Rossby waves by various techniques; b) development of coupled nonlinear MHD models that simulate both global Rossby waves and the much smaller spatial scale emergence of new active regions; c) application of advanced data assimilation techniques to couple surface observations to update the model-system to integrate forward in time for creating forecasts months ahead. Then it will be possible to build operational prediction models to meet the needs of customers and stakeholders, including support of future NASA missions, regarding what kind and level of space weather to expect a few weeks to several months ahead.

SMD↗

The Importance of Cross-Scale and Cross-Interface Processes on Arctic Amplification

The Arctic is a dynamic region, demonstrated by its remarkable internal variability and rapid response to anthropogenic climate change over the last >40 years. Actionable predictions and projections hold significant value for managing both natural and human systems. The value of these model outputs only grows in a warmer, less icy Arctic. However, substantial gaps exist in our understanding of cross-scale and cross-interface (air-sea ice-ocean) interactions that limit our predictive capabilities. Studies dating back at least 40 years provide evidence that the evolution of the Arctic climate system is sensitive to these cross-scale and cross-interface interactions. This presentation summarizes our understanding of cross-scale and cross-interface interactions relevant to the Arctic’s response to anthropogenic climate change—Arctic Amplification. The presentation emphasizes the influence of surface-type dependent turbulent flux exchanges of heat and moisture, the rectification of episodic atmospheric heat transport events on time-averaged changes, local and remote feedback interactions, and cross-seasonal energy transfers. The presentation concludes with a summary of knowledge gaps and discusses potential pathways for accelerating our understanding of the Arctic climate system.

Patrick C Taylor↗

Numerical Study on the Aerodynamics of an Iced Airfoil With Scale-Resolving Simulations

Scale-resolving simulations of the NACA 23012 airfoil with horn ice accretion on the leading edge are conducted using the hybrid Reynolds-averaged Navier–Stokes/large-eddy simulation (hybrid RANS/LES) and wall-modeled large-eddy simulation (WMLES) approaches implemented in the Launch, Ascent, and Vehicle Aerodynamics (LAVA) framework. Aerodynamic results at the Reynolds number of 1.8 million show good comparison with the experimental measurements at different angles of attack from pre-stall to post-stall regimes. The pressure plateaus caused by the flow separation and the recovery of pressure inside the separation bubble around the iced leading edge are well predicted with the scale-resolving simulations when sufficient grid resolution is used around the accreted ice. The unsteadiness of the turbulent flows around the iced airfoil is also examined through the turbulent kinetic energy with the Reynolds normal stress anisotropy. Kelvin–Helmholtz instability (KHI) arises at the shear layer triggered by the upper ice horn and leads to rapid laminar-to-turbulent transition over a large range of angle of attack. With the increase of the angle of attack, the region with high turbulence intensity induced by the unstable shear layer spreads quickly over the entire upper surface of the airfoil. The coherent KHI modes from the upper and lower ice horns are extracted using the spectral proper orthogonal decomposition (SPOD) technique. The SPOD modes extracted from the upper shear layer have large-scale variations in the spanwise direction and low-rank behavior where the energy of the leading SPOD mode at each Strouhal number of the KHI largely represents the total energy when the mode number in the spanwise direction is small.

ARMD↗

Numerical Study on the Aerodynamics of an Iced Airfoil With Scale-Resolving Simulations

Scale-resolving simulations of the NACA 23012 airfoil with horn ice accretion on the leading edge are conducted using the hybrid Reynolds-averaged Navier–Stokes/large-eddy simulation (hybrid RANS/LES) and wall-modeled large-eddy simulation (WMLES) approaches implemented in the Launch, Ascent, and Vehicle Aerodynamics (LAVA) framework. Aerodynamic results at the Reynolds number of 1.8 million show good comparison with the experimental measurements at different angles of attack from pre-stall to post-stall regimes. The pressure plateaus caused by the flow separation and the recovery of pressure inside the separation bubble around the iced leading edge are well predicted with the scale-resolving simulations when sufficient grid resolution is used around the accreted ice. The unsteadiness of the turbulent flows around the iced airfoil is also examined through the turbulent kinetic energy with the Reynolds normal stress anisotropy. Kelvin–Helmholtz instability (KHI) arises at the shear layer triggered by the upper ice horn and leads to rapid laminar-to-turbulent transition over a large range of angle of attack. With the increase of the angle of attack, the region with high turbulence intensity induced by the unstable shear layer spreads quickly over the entire upper surface of the airfoil. The coherent KHI modes from the upper and lower ice horns are extracted using the spectral proper orthogonal decomposition (SPOD) technique. The SPOD modes extracted from the upper shear layer have large-scale variations in the spanwise direction and low-rank behavior where the energy of the leading SPOD mode at each Strouhal number of the KHI largely represents the total energy when the mode number in the spanwise direction is small.

ARMD↗

Satellites Quantify the Spatial Extent of Cyanobacterial Blooms Across the United States at Multiple Scales

Previous studies indicate that cyanobacterial harmful algal bloom (cyanoHAB) frequency, extent, and magnitude have increased globally over the past few decades. However, little quantitative capability is available to assess these metrics of cyanoHABs across broad geographic scales and at regular intervals. Here, the spatial extent was quantified from a cyanobacteria algorithm applied to two European Space Agency satellite platforms—the MEdium Resolution Imaging Spectrometer (MERIS) onboard Envisat and the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3. CyanoHAB spatial extent was defined for each geographic area as the percentage of valid satellite pixels that exhibited cyanobacteria above the detection limit of the satellite sensor. This study quantified cyanoHAB spatial extent for over 2,000 large lakes and reservoirs across the contiguous United States (CONUS) during two time periods: 2008–2011 via MERIS and 2017–2020 via OLCI when cloud-, ice-, and snow-free imagery was available. Approximately 56% of resolvable lakes were glaciated, 13% were headwater, isolated, or terminal lakes, and the rest were primarily drainage lakes. Results were summarized at national-, regional-, state-, and lake-scales, where regions were defined as nine climate regions which represent climatically consistent states. As measured by satellite, changes in national cyanoHAB extent did have a strong increase of 6.9% from 2017 to 2020 (|Kendall’s tau (τ)| = 0.56; gamma (γ) = 2.87 years), but had negligible change (|τ| = 0.03) from 2008 to 2011. Two of the nine regions had moderate (0.3 ≤ |τ| < 0.5) increases in spatial extent from 2017 to 2020, and eight of nine regions had negligible (|τ| < 0.2) change from 2008 to 2011. Twelve states had a strong or moderate increase from 2017 to 2020 (|τ| ≥ 0.3), while only one state had a moderate increase and two states had a moderate decrease from 2008 to 2011. A decrease, or no change, in cyanoHAB spatial extent did not indicate a lack of issues related to cyanoHABs. Sensitivity results of randomly omitted daily CONUS scenes confirm that even with reduced data availability during a short four-year temporal assessment, the direction and strength of the changes in spatial extent remained consistent. We present the first set of national maps of lake cyanoHAB spatial extent across CONUS and demonstrate an approach for quantifying past and future changes at multiple spatial scales. Results presented here provide water quality managers information regarding current cyanoHAB spatial extent and quantify rates of change.

Harmful Algal Blooms↗

Cross-Scale and Cross-Interface Processes and Arctic Amplification

The Arctic is a dynamic region, demonstrated by its remarkable internal variability and rapid response to anthropogenic climate change over the last >40 years. Actionable predictions and projections hold significant value for managing both natural and human systems. The value of these model outputs only grows in a warmer, less icy Arctic. However, substantial gaps exist in our understanding of cross-scale and cross-interface (air-sea ice-ocean) interactions that limit our predictive capabilities. Studies dating back at least 40 years provide evidence that the evolution of the Arctic climate system is sensitive to these cross-scale and cross-interface interactions. This presentation summarizes our understanding of cross-scale and cross-interface interactions relevant to the Arctic’s response to anthropogenic climate change—Arctic Amplification. The presentation emphasizes the influence of surface-type dependent turbulent flux exchanges of heat and moisture, the rectification of episodic atmospheric heat transport events on time-averaged changes, local and remote feedback interactions, and cross-seasonal energy transfers. The presentation concludes with a summary of knowledge gaps and discusses potential pathways for accelerating our understanding of the Arctic climate system.

Patrick C. Taylor↗

Additional Large-Drop Ice Accretion Test Results for a Large Scale Swept Wing Section from January 2022

In-flight icing is an important consideration that affects aircraft design, performance, certification and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of additional ice accretion testing conducted in the NASA Icing Research Tunnel in January 2022 with a large swept wing section typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small median volumetric diameter (MVD) = 25 μm cloud and a large MVD = 110 μm cloud. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. Another series of tests explored cloud MVD variations from 50 μm to 230 μm while holding constant certain scaling parameters. The variation in ice mass and scanned ice volume across repeat conditions was approximately 50% lower than the uncertainty in the cloud MVD and liquid water content. The measured ice mass and volume calculated from the 3D scans were used to compute the mass to volume ratio that is sometimes referred to as ice density or void fraction. When the ice volume based on the ice shape maximum combined cross section was used to determine this ratio, the resulting values were in the range of 240 to 455 kg/m 3 . This is consistent with analogous values previously reported in the literature. The ice shape mass and volume increased with MVD from 50 to 230 μm at fixed values of the scaling parameters. The ice mass to volume ratio was approximately constant for all of the cases which showed that the accreted mass and volume increased at approximately the same rate. These results demonstrate the significance of cloud MVD on ice shape mass and volume.

Ice accretion, Large drops, Wind tunnel↗

Additional Large-Drop Ice Accretion Test Results for a Large Scale Swept Wing Section from January 2022

In-flight icing is an important consideration that affects aircraft design, performance, certification and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of additional ice accretion testing conducted in the NASA Icing Research Tunnel in January 2022 with a large swept wing section typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small median volumetric diameter (MVD) = 25 μm cloud and a large MVD = 110 μm cloud. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. Another series of tests explored cloud MVD variations from 50 μm to 230 μm while holding constant certain scaling parameters. The variation in ice mass and scanned ice volume across repeat conditions was approximately 50% lower than the uncertainty in the cloud MVD and liquid water content. The measured ice mass and volume calculated from the 3D scans were used to compute the mass to volume ratio that is sometimes referred to as ice density or void fraction. When the ice volume based on the ice shape maximum combined cross section was used to determine this ratio, the resulting values were in the range of 240 to 455 kg/m3. This is consistent with analogous values previously reported in the literature. The ice shape mass and volume increased with MVD from 50 to 230 μm at fixed values of the scaling parameters. The ice mass to volume ratio was approximately constant for all of the cases which showed that the accreted mass and volume increased at approximately the same rate. These results demonstrate the significance of cloud MVD on ice shape mass and volume.

Ice accretion↗

Top‐Down Regulation by a Reindeer Herding System Limits Climate‐Driven Arctic Vegetation Change at a Regional Scale

Warming-driven growth of tall woody vegetation in the Arctic has the potential to accelerate climate change through multiple positive feedbacks. Local-scale evidence suggests that large herbivores limit this vegetation shift, but there is uncertainty at larger, regional scales whether current herbivory pressure is a major top-down control on ecosystem structure and functioning. Across a 67,000 km2 region of the Yamal Peninsula in West Siberia, we integrated satellite remote sensing with a novel data set mapping the migrations of herds comprising 151,000 domesticated reindeer. Where reindeer numbers varied over space, higher reindeer herbivory pressure was consistently linked with lower coverage of tall woody vegetation. Within areas dominated by this vegetation type, productivity and climate were increasingly decoupled where reindeer density was higher. Our spaceborne fingerprint detection suggests that large herbivores, at current population densities, counteract Arctic vegetation responses to climate change over large spatial scales.

Reindeer Herding System↗

Experimental Characterization of an Electric Ducted Fan for the SUSAN 25% Scale Research Vehicle

An electric ducted fan (EDF) was tested in the NASA Langley 12-Foot Low-Speed Tunnel for the SUbsonic Single Aft eNgine (SUSAN) Electrofan 25% scale research vehicle, which incorporates distributed electric fans along the wings and serves as a scaled electrified transport aircraft testbed. The commercial-off-the-shelf EDF was selected as a propulsor that can meet the 25% scale vehicle geometry constraints, along with the performance requirements throughout the flight profile. The test included a series of one-factor-at-a-time (OFAT) and design of experiments (DOE) approaches that were implemented across a range of fan speed, voltage, freestream dynamic pressure, and incidence angle settings to characterize the performance of the EDF. Several test matrix designs and modeling approaches were considered. System identification methods were used to develop a static motor model, a dynamic motor model, an EDF thrust model, and a power consumption model. The model predictive capabilities were then evaluated with validation data not used in the modeling process. The results provide a comprehensive set of models developed to characterize the fan, and offer general insight into EDF modeling approaches.

electric ducted fan↗

Data Fusion and Mining Techniques to Map Water Use and Drought across Spatial and Temporal Scales

As the world’s water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Remote sensing methods for monitoring consumptive water use (e.g, ET) are becoming increasingly important, especially in areas of significant water and food insecurity. One method to estimate ET from satellite-based methods, the Atmosphere Land Exchange Inverse (ALEXI) model uses the change in mid-morning land surface temperature to estimate the partitioning of sensible and latent heat fluxes which are then used to estimate daily ET. This presentation will outline several recent enhancements to the ALEXI modeling system, with a focus on global ET and drought monitoring. Until recently, ALEXI has been limited to areas with high resolution temporal sampling of geostationary sensors. The use of geostationary sensors makes global mapping a complicated process, especially for real-time applications, as data from as many as five different sensors are required to be ingested and harmonized to create a global mosaic. However, our research team has developed a new and novel method of using twice-daily observations from polar-orbiting sensors such as MODIS and VIIRS to estimate the mid-morning rise in LST that is used to drive the energy balance estimations within ALEXI. This allows the method to be applied globally using a single sensor (in this case, initially MODIS with a planned transition to VIIRS) rather than a global compositing of all available geostationary data. Other advantages of this new method include the higher spatial resolution provided by MODIS and VIIRS and the increased sampling at high latitudes where oblique view angles limit the utility of geostationary sensors. This presentation will focus on global applications for mapping water use and drought using data mining and data fusion across spatial scales extending from 5-km to 30-m “field-scale” estimates.

Christopher Hain↗