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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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NASA NTRS1973

Low-speed wind tunnel investigation of the lateral-directional characterisitcs of a large-scale variable wing-sweep fighter model in the high-lift configuration

The low-speed characteristics of a large-scale model of the F-14A aircraft were studied in tests conducted in the Ames Research Center 40- by 80-Foot Wind Tunnel. The primary purpose of the present tests was the determination of lateral-directional stability levels and control effectiveness of the aircraft in its high-lift configuration. Tests were conducted at wing angles of attack between minus 2 deg and 30 deg and with sideslip angles between minus 12 deg and 12 deg. Data were taken at a Reynolds number of 8.0 million based on a wing mean aerodynamic chord of 2.24 m (7.36 ft). The model configuration was changed as required to show the effects of direct lift control (spoilers) at yaw, yaw angle with speed brake deflected, and various amounts and combinations of roll control.

Eckert, W. T.↗

NASA NTRS2009

Determining Surface Roughness in Urban Areas Using Lidar Data

An automated procedure has been developed to derive relevant factors, which can increase the ability to produce objective, repeatable methods for determining aerodynamic surface roughness. Aerodynamic surface roughness is used for many applications, like atmospheric dispersive models and wind-damage models. For this technique, existing lidar data was used that was originally collected for terrain analysis, and demonstrated that surface roughness values can be automatically derived, and then subsequently utilized in disaster-management and homeland security models. The developed lidar-processing algorithm effectively distinguishes buildings from trees and characterizes their size, density, orientation, and spacing (see figure); all of these variables are parameters that are required to calculate the estimated surface roughness for a specified area. By using this algorithm, aerodynamic surface roughness values in urban areas can then be extracted automatically. The user can also adjust the algorithm for local conditions and lidar characteristics, like summer/winter vegetation and dense/sparse lidar point spacing. Additionally, the user can also survey variations in surface roughness that occurs due to wind direction; for example, during a hurricane, when wind direction can change dramatically, this variable can be extremely significant. In its current state, the algorithm calculates an estimated surface roughness for a square kilometer area; techniques using the lidar data to calculate the surface roughness for a point, whereby only roughness elements that are upstream from the point of interest are used and the wind direction is a vital concern, are being investigated. This technological advancement will improve the reliability and accuracy of models that use and incorporate surface roughness.

Holland, Donald↗

DOE OSTI2024

Atmospheric Variability Drives Anomalies in the Bering Sea Air–Sea Heat Exchange

Abstract High latitudes, including the Bering Sea, are experiencing unprecedented rates of change. Long-term Bering Sea warming trends have been identified, and marine heatwaves (MHWs), event-scale elevated sea surface temperature (SST) extremes, have also increased in frequency and longevity in recent years. Recent work has shown that variability in air–sea coupling plays a dominant role in driving Bering Sea upper-ocean thermal variability and that surface forcing has driven an increase in the occurrence of positive ocean temperature anomalies since 2010. In this work, we characterize the drivers of the anomalous surface air–sea heat fluxes in the Bering Sea over the period 2010–22 using ERA5 fields. We show that the surface turbulent heat flux dominates the net surface heat flux variability from September to April and is primarily a result of near-surface air temperature and specific humidity anomalies. The airmass anomalies that account for the majority of the turbulent heat flux variability are a function of wind direction, with southerly (northerly) wind advecting anomalously warm (cool), moist (dry) air over the Bering Sea, resulting in positive (negative) surface turbulent flux anomalies. During the remaining months of the year, anomalies in the surface radiative fluxes account for the majority of the net surface heat flux variability and are a result of anomalous cloud coverage, anomalous lower-tropospheric virtual temperature, and sea ice coverage variability. Our results indicate that atmospheric variability drives much of the Bering Sea upper-ocean temperature variability through the mediation of the surface heat fluxes during the analysis period. Significance Statement A long-term ocean warming trend and a recent increase in marine heatwaves in the Bering Sea have been identified. Previous work showed that anomalies in the exchange of heat between the ocean and the atmosphere were the primary driver of Bering Sea temperature variability, but the processes responsible for the heat exchange anomalies were unknown. In this work, we show that the atmosphere is the primary driver of anomalies in the Bering Sea air–sea heat exchange and therefore plays an important role in altering the thermal state of the Bering Sea. Our results highlight the importance of understanding more about how the ocean and the atmosphere interact at high latitudes and how this relationship will be affected by future climate change.

Hayden, Emily E. [a College of Earth, Ocean, and A↗

NASA NTRS1977

Simulation model of erosion and deposition on a barchan dune

Erosion and deposition over a barchan dune near the Salton Sea, California, are modeled by bookkeeping the quantity of sand in saltation following streamlines of transport. Field observations of near surface wind velocity and direction plus supplemental measurements of the velocity distribution over a scale model of the dune are combined as input to Bagnold type sand transport formulas corrected for slope effects. A unidirectional wind is assumed. The resulting patterns of erosion and deposition compare closely with those observed in the field and those predicted by the assumption of equilibrium (downwind translation of the dune without change in size or geometry). Discrepancies between the simulated results and the observed or predicted erosional patterns appear to be largely due to natural fluctuations in the wind direction. The shape of barchan dunes is a function of grain size, velocity, degree of saturation of the oncoming flow, and the variability in the direction of the oncoming wind. The size of the barchans may be controlled by natural atmospheric scales, by the age of the dunes, or by the upwind roughness. The upwind roughness can be controlled by fixed elements or by sand in the saltation. In the latter case, dune scale is determined by grain size and wind velocity.

Howard, A. D.↗

NASA NTRS2017

Aeolus -A Mission to Study the Thermal and Wind Environment of Mars

Aeolus is a small satellite mission to observe surface and atmospheric forcing and general circulation of Mars, by measuring surface energy balance, atmospheric temperatures, aerosols and clouds, and winds. Critically, Aeolus will make these measurements at all local times of day, providing information on both seasonal and diurnal variability. To date, direct measurements of Martian wind speeds have only been possible at the surface, only during daylight hours, and over small areas limited by rover traverse capabilities. From orbit, thermal measurements (e.g., estimates from assumed geostrophic balance) as well as images of dust storms and dune migration have provided inputs to derive current data sets on Martian winds. However, Mars General Circulation models demonstrate that wind speeds derived from these indirect measurements may be in error by 50 to 100%. For this reason, direct wind velocity measurements have been deemed "High Priority" by MEPAG (Mars Exploration Program Analysis Group); measuring wind speeds and corresponding thermal data is vital to understanding the climate of Mars. Aeolus will carry four Spatial Heterodyne Spectrometers (SHS), coupled to two orthogonal viewing telescopes. These high-resolution near-infrared spectrometers will measure CO2 (daytime absorption) and O2 (day and night emission) lines in the Martian atmosphere. Doppler shifts in these lines can be measured during Martian day and night, resolving wind speeds down to ~5 m/s. Orthogonal views allow the spectrometers to capture wind vectors over all observation locations. Aeolus will also carry the atmospheric limb-viewing Thermal Limb Sounder (TLS) to measure atmospheric temperatures, water ice clouds, and dust abundances across all altitudes where winds are measured. Finally, the Surface Radiometric Sensor Package (SuRSeP), a nadir viewing radiometer, will measure the total reflected solar and emitted thermal radiance, surface temperature, and water cloud and dust total column abundances. The combined spectral and thermal measurements will provide a new understanding of the global energy balance, dust transport processes, and climate cycles in the Martian atmosphere. Aeolus will consist of a single satellite in a near-polar orbit, allowing it to pass over all local times, with the baseline mission observing all seasons of an entire Martian year (two Earth years). Aeolus was one of two Martian smallsat concepts selected for study through the Planetary Science Deep Space SmallSat Studies program. This talk will provide an overview of the mission, including science rationale, instruments, spacecraft, and mission operations concept.

and winds↗

NASA NTRS2022

Wind-Optimal Lateral Trajectories for a Multirotor Aircraft in Urban Air Mobility

The primary motivation for this paper is to quantify the operational benefits (energy consumption and flight duration) of flying wind-optimal lateral trajectories for short flights (less than 60 miles) anticipated in the urban environment. The optimal control model presented includes a wind model for quantifying the effect of wind on the lateral trajectory. The optimal control problem is numerically solved using the direct collocation method. Energy consumption and flight duration flying wind-optimal lateral trajectories are compared with corresponding values obtained flying great-circle paths between the same origin and destination pairs to determine the operational benefits of wind-optimal routing for short flights. The flight duration results for different scenarios are validated using a simulation tool designed and developed at NASA for exploring advanced air traffic management concepts. This research study suggests that for short flights in an urban environment, operational benefits of the wind-optimal lateral trajectories over the corresponding great-circle trajectories in terms of energy consumption and flight duration per flight are dependent on: i) wind field’s spatial variability, ii) wind magnitude, iii) the direction of route relative to the wind field, and iv) cruise segment length. The operational benefits observed in realistic flyable wind scenarios are less than 2.5%; these could be translated to an equivalent of a maximum of 2 min of cruise flight duration savings in the urban air mobility environment. As expected, headwinds and tailwinds along the flight route most significantly impact energy consumption and flight duration.

Wind-Optimal Trajectory, Lateral Path, Urban Air M↗

DOE OSTI2022

Tracking westerly wind directions over Europe since the middle Holocene

The variability of the northern westerlies has been considered as one of the key elements for modern and past climate evolution. Their multiscale behavior and underlying control mechanisms, however, are incompletely understood, owing to the complex dynamics of Atlantic sea-level pressures. Here, we present a multi-annually resolved record of the westerly drift over the past 6,500 years from northern Italy. In combination with more than 20 other westerly-sensitive records, our results depict the non-stationary westerly-affected regions over mainland Europe on multi-decadal to multi-centennial time scales, showing that the direction of the westerlies has changed with respect to the migrations of the North Atlantic centers of action since the middle Holocene. Our findings suggest the crucial role of the migrations of the North Atlantic dipole in modulating the westerly-affected domain over Europe, possibly modulated by Atlantic Ocean variability.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Inlet Performance of the NFAC 1/50th-scale 80- by 120- Foot Wind Tunnel

The National Full-Scale Aerodynamics Complex 80- by 120-Foot Wind Tunnel (80x120) was dedicated in 1987 and rated at 100 knots for full-scale aircraft testing at NASA Ames Research Center. The 80x120 is the world’s largest wind tunnel, designed as an open circuit tunnel with a large aerodynamically treated inlet open to the ambient atmospheric air. In 2017, damage was sustained within the wind tunnel drive system, opening a window to do testing using the existing 1/50th-scale model of the 80- by 120-Foot Wind Tunnel within the full-scale 80- by 120-Foot Wind tunnel test section. The objective of the research was to quantify the turbulence levels within the 1/50th-scale test section as a function of onset atmospheric wind direction (± 90 deg from tunnel center-line), variable test section speed (5 – 50 m/s) and purposeful obtrusion of wind flow into the inlet. The model wind tunnel inlet, contraction, and test section are geometrically identical to that of the full-scale wind tunnel and model testing provides aerodynamic performance characteristics under controlled test conditions allowing for insight into the full-scale test section flow quality. The test section turbulence levels are minimally affected by the onset direction of the ambient atmospheric wind, but are dramatically affected by the speed in the tunnel while operated in the presence of winds. Original design specifications were axial/vertical/lateral turbulence ≤ 0.5% at maximum test section speed, though early full scale tunnel testing determined that lateral turbulence would be ≤ 0.6%. For test section speeds ≥ 30 m/s the tunnel is within the design specification limits. Between 5 m/s and 30 m/s, the test section turbulence levels are dependent on the onset wind direction and test section speed where test section turbulence in the axial, vertical and lateral directions was seen to be between 0.5% and 1% and, at times, greater than 1%. Finally, testing was performed with blockage designs at the inlet to disrupt the wind flow quality entering the tunnel contraction zone in an attempt to create higher levels of turbulence for high turbulent test conditions simulating the earth’s boundary layer. The highest turbulence levels measured were 6% in the axial direction by use of large spires designed to obstruct ≈ 50% of the inlet area.

Inlet Performance↗

NASA NTRS2012

Heat Stress Equation Development and Usage for Dryden Flight Research Center (DFRC)

Heat Stress Indices are equations that integrate some or all variables (e.g. temperature, relative humidity, wind speed), directly or indirectly, to produce a number for thermal stress on humans for a particular environment. There are a large number of equations that have been developed which range from simple equations that may ignore basic factors (e.g. wind effects on thermal loading, fixed contribution from solar heating) to complex equations that attempt to incorporate all variables. Each equation is evaluated for a particular use, as well as considering the ease of use and reliability of the results. The meteorology group at the Dryden Flight Research Center has utilized and enhanced the American College of Sports Medicine equation to represent the specific environment of the Mojave Desert. The Dryden WBGT Heat Stress equation has been vetted and implemented as an automated notification to the entire facility for the safety of all personnel and visitors.

Houtas, Franzeska↗

DOE OSTI2024

Surface Meteorological System (MET) Instrument Handbook

The Surface Meteorological System (MET) consist mainly of conventional in situ sensors that obtain a defined “core” set of measurements. The core set of measurements is: Barometric Pressure (kPa), Temperature (°C), Relative Humidity (%), Arithmetic-Averaged Wind Speed (m/s), Vector-Averaged Wind Speed (m/s), and Vector-Averaged Wind Direction (deg). The sensors that collect the core variables are mounted at the standard heights defined for each variable: • Winds: 10 meters • Temperature and Relative Humidity: 2 meters • Barometric Pressure: 1 meter. Depending upon the geographical location, different models and types of sensors may be used to measure the core variables due to the conditions experienced at those locations. Most sites have additional sensors that measure other variables that are unique to that site or are well suited for the climate of the location but not at others.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Environmental Controls on Water Vapor Deuterium Excess in the Coastal Boundary Layer: An Information Theory Perspective

We use information theory to quantify the environmental controls on water vapor deuterium excess (D-excess) in coastal Southern California from June 2023 through February 2024. Using Shannon entropy, mutual information (MI), and joint mutual information, metrics that capture both linear and nonlinear relationships, we identify the most informative variables and variable combinations governing D-excess across contrasting marine and continental regimes. Relative humidity with respect to sea surface temperature (RHS) is consistently the strongest individual predictor, explaining up to 27% of D-excess variability during marine conditions but only 10% in continental air masses. The Relative humidity(RHS) + sea surface temperature (SST) combination demonstrates synergistic effects, where their joint influence (explaining up to 36% of D-excess variability) exceeds what either variable achieves individually, confirming their coupled influence on deuterium excess. Wind direction complements RHS most effectively during continental conditions. The best three-variable combination (RHS + SST + Planetary Boundary Layer height) explains 38% of D-excess variability in marine air, while no combination exceeds 20% explanatory power during continental periods. Information theory shows that heteroscedasticity in D-excess relationships indicates regime shifts in controlling processes and quantifies fundamental constraints on predictor variables: some environmental factors like surface pressure or water vapor flux contain insufficient information content to explain D-excess variability regardless of their physical relevance. These results highlight the different predictability limits between marine and continental regimes, challenging the adequacy of linear models and providing a rigorous framework for quantifying the information content of isotope-climate relationships with implications for both modern and paleoclimate applications.

information theory↗

NASA NTRS2016

New Approach to Characterize CO2 and CH4 Emissions over Sacramento, California Using an Airborne Aircraft Measurement

Emission fluxes of carbon dioxide (CO2) and methane (CH4) over Sacramento, California, USA, are estimated using an aircraft equipped with a cavity ring-down greenhouse gas sensor through the Alpha Jet Atmospheric eXperiment (AJAX). To better quantify the emission fluxes over the entire city and two small point sources within the area, we designed flights in a cylindrical pattern and computed the emission fluxes from 9 flights over all seasons using the Kriging method based on Gausss divergence theorem. The concentrations at the downwind side of Sacramento show somewhat persistent patterns among the 9 flights, but the magnitudes and locations of the fluxes vary depending on the individual weather conditions and seasonality on a given flight day. The net emission fluxes tend to be smaller in summer (July) than winter (November). Both trace gas mixing ratios as well as the wind speed and direction show high spatial variability both horizontally and vertically. The local maximum emission fluxes over a landfill and a rice field measured on July 29, 2015, were 2-3 times lower than the maximum measured over the entire city. These low emission fluxes suggest that not only the local source but also the transport of greenhouse gases due to diurnal and seasonal variation in winds have a strong effect on the CO2 and CH4 flux estimation of the both local emissions and city-size emissions. Our results highlight that the aircraft-based approach is effective and useful for capturing city-size emission fluxes and estimating the greenhouse gas emissions and its sources.

airborne↗

NASA NTRS2012

Detection of Bi-Directionality in Strain-Gage Balance Calibration Data

An indicator variable was developed for both visualization and detection of bi-directionality in wind tunnel strain-gage balance calibration data. First, the calculation of the indicator variable is explained in detail. Then, a criterion is discussed that may be used to decide which gage outputs of a balance have bi- directional behavior. The result of this analysis could be used, for example, to justify the selection of certain absolute value or other even function terms in the regression model of gage outputs whenever the Iterative Method is chosen for the balance calibration data analysis. Calibration data of NASA s MK40 Task balance is analyzed to illustrate both the calculation of the indicator variable and the application of the proposed criterion. Finally, bi directionality characteristics of typical multi piece, hybrid, single piece, and semispan balances are determined and discussed.

Ulbrich, Norbert↗

DOE OSTI2025

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗

NASA NTRS2021

Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar

Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.

Eunsang Cho↗

NASA NTRS1976

Water resources planning for rivers draining into Mobile Bay

The application of remote sensing, automatic data processing, modeling and other aerospace related technologies to hydrological engineering and water resource management are discussed for the entire river drainage system which feeds the Mobile Bay estuary. The adaptation and implementation of existing mathematical modeling methods are investigated for the purpose of describing the behavior of Mobile Bay. Of particular importance are the interactions that system variables such as river flow rate, wind direction and speed, and tidal state have on the water movement and quality within the bay system.

April, G. C.↗

NASA NTRS1994

Irregular, long-period boundary oscillations beyond approximately 100 R(sub e): GEOTAIL plasma observations

Near the tail boundary beyond about 100 Re, GEOTAIL often measures irregular, long-period oscillations in plasma velocity and density. Flow speed and density oscillate between magnetosheath values and values an order of magnitude less. The oscillations can persist for days. A typical oscillation lasts 100 minutes, but the range is large. The oscillations are highly asymmetric in that the increasing phase of the oscillation is an order of magnitude faster than the decreasing phase. This asymmetry shows that they are a distinct class of oscillations, not previously explicitly reported, and that they are not mere consequences of tail flapping in a variable solar wind. The changes in flow direction through an oscillation imply that the oscillation results from a motion of the boundary toward and away from the spacecraft with an amplitude between 5 and 10 R(sub e). A consideration of options suggests that the most plausible cause of these oscillations is the 'breathing' of the magnetotail that attends the substorm cycle.

Siscoe, G. L.↗

NASA NTRS2016

Evaluation of Different MODIS AOD Retrieval Algorithms for PM (sub 2.5) Estimation in the Western, Midwestern and Southeastern United States with Implications for Public Health

This study was part of the research activities of the Center for Applied Atmospheric Research and Education (CAARE) funded by the NASA MUREP (Minority University Research and Education Project) Institutional Research Opportunity (MIRO) Program. Satellite measurements of Aerosol Optical Depth (AOD) have been shown to be correlated with ground measurements of fine particulate matter less than 2.5 microns PM (sub 2.5), which in turn has been linked to respiratory and heart diseases. The strength of the correlation between AOD and PM (sub 2.5) varies for different AOD retrieval algorithms and geographic regions. We evaluated several Moderate Resolution Imaging Spectrometer (MODIS) AOD products from different satellites (Aqua vs. Terra), retrieval algorithms (Dark Target versus Deep Blue), Collections (5.1 versus 6) and spatial resolutions (10-kilometers versus 3-kilometers) for cities in the Western, Midwestern and Southeastern U.S. We developed and validated PM (sub 2.5) prediction models using remotely-sensed AOD data, which were improved by incorporating meteorological variables (temperature, relative humidity, precipitation, wind speed, and wind direction) from the North American Land Data Assimilation System Phase 2 (NLDAS-2). Adding these meteorological data significantly improved the predictive power of all the PM (sub 2.5) models, especially in the Western U.S. Temperature, relative humidity and wind speed were the most significant meteorological variables throughout the year in the Western U.S. Wind speed was the most significant meteorological variable for the cold season while temperature was the most significant variable for the warm season in the Midwestern and Southeastern U.S. Our study re-establishes the connection between PM (sub 2.5) and public health concerns including respiratory and cardiovascular diseases (asthma, high blood pressure, coronary heart disease, heart attack, and stroke). Using PM (sub 2.5) data and health data from the Centers for Disease Control and Prevention (CDC)'s Behavioral Risk Factor Surveillance System (BRFSS), our statistical analysis showed that heart attack and stroke occurrences had the strongest correlations with PM (sub 2.5).

Environmental Public Health↗