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At least 37 records · Page 2

Airport Runway Configuration Management with Offline Model-free Reinforcement Learning

Runway configuration management (RCM) deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction and other environmental variables. RCM is one of the most challenging tasks in air traffic management, as it relies on operational and environmental variables (e.g., weather forecast) that are highly uncertain and complex to model. In this paper, an innovative and automated approach is deployed using offline model-free reinforcement learning to provide decision-support for RCM. The proposed technology processes historical data about variables of interest, decisions made regarding RCM, and their subsequent outcome, to identify a policy that would encourage good decisions and avoid the poor ones. The policy search is guided by an appropriately chosen weighted utility function (e.g., based on minimizing delays and go-arounds). Finally, the performance of the proposed tool is validated using Charlotte Douglas International Airport as the case study, which shows that the proposed method is superior to other conventional rule-based approaches.

Milad Memarzadeh↗

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.↗

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↗

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.↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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.↗

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.↗

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↗

TRMM Observations of Convective Regimes in the Amazon

This study utilizes TRMM satellite precipitation radar, lightning imaging sensor, and passive microwave imager data together with ground-based lightning data to investigate the vertical structure, lightning, and rainfall characteristics of Amazonian and central South American convection for three separate wet-seasons. These characteristics are partitioned as a function of 850 mb zonal wind direction, motivated by observations collected during the six-week TRMM-LBA field campaign. The TRMM-LBA field campaign observations suggest that systematic variations in Amazonian convective vertical structure, lightning, and rainfall are all linked to bimodal variations in the low-level zonal wind (e.g., easterly and westerly regimes). The more spatially and temporally comprehensive TRMM dataset used in this study extends the TRMM-LBA observations by examining regime variability in Amazonian and South American convective structure over a continental scale domain. On a continental-scale, patterns of east and west regime 850 mb winds combined with LIS lightning flash densities suggest the presence of synoptic-scale controls (e.g., intrusion of extratropical frontal systems and interaction with the SACZ) on regional-scale variability in convective vertical structure. TRMM PR, TMI and ground-based lightning data suggest that regional variability in wet-season convective structure is most evident over the southern Amazon, Mato Grosso, Altiplano, southern Brazil, and eastern coastal regions of central and southern South America. Convective vertical structure, rain fall rates, and lightning activity are all more pronounced during easterly (westerly) regimes over the southern Amazon and Mato Grosso (Altiplano, and southern Brazil). Importantly, when considered with case-study results from TRMM-LBA, the systematic differences in convective structure that occur as a function of regime suggest that associated regime-differences may exist in the vertical distribution of diabatic heating. Hence the discrimination of convective vertical structure "regimes" over parts of the Amazon and vicinity based on a resolved variable such as the 850 mb zonal wind direction, while far from being perfect, may have important applications to the problems of cumulus parameterization, rainfall estimation and retrievals of latent heating over the Amazon.

Petersen, W. A.↗

Lidar Wind Profiler Comparison to Weather Balloon for Support of Orion Crew Exploration Vehicle Landings

A comparison study by the National Aeronautics and Space Administration Dryden Flight Research Center, Edwards, CA and the Naval Post Graduate School Center for Interdisciplinary Remotely-Piloted Aircraft Studies, Marina, CA was conducted to show the advantages of an airborne wind profiling lidar system in reducing drift uncertainty along a reentry vehicle descent trajectory. This effort was in support of the once planned Orion Crew Exploration Vehicle ground landing. A Twin Otter Doppler Wind Lidar was flown on multiple flights along the approximate ground track of an ascending weather balloons launched from the Marina Municipal Airport. The airborne lidar used was a 5-milli-Joules, 2-micron infrared laser with a 10-centimeter telescope and a two-axis scanner. Each lidar wind profile contains data for an altitude range between the surface and flight altitude of 2,700 meters, processed on board every 20 seconds. In comparison, a typical weather balloon would traverse that same altitude range with a similar data set available in approximately 15-20 minutes. These tests were conducted on November 15 & 16, 2007. Results comparing the balloon and a 10 minute multiple lidar profile averages show a best case absolute difference of 0.18 m/s (0.35 knots) in speed and 1 degree in direction during light and variable (less than 5 knots, without constant direction) wind conditions. These limited test results indicated a standard deviation wind velocity and direction differences of 0.71 m/s (1.3 knots) and 7.17 degrees for 1800Z, and 0.70 m/s (1.3 knots) and 6.79 degrees, outside of cloud layer.

Houtas, Franzeska↗

Evaluation of surface energy and radiation balance systems for FIFE

The energy balance and radiation balance components were determined at six sites during the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) conducted south of Manhattan, Kansas during the summer of 1987. The objectives were: to determine the effect of slope and aspect, throughout a growing season, on the magnitude of the surface energy balance fluxes as determined by the Energy Balance Method (EBM); to investigate the calculation of the soil heat flux density at the surface as calculated from the heat capacity and the thermal conductivity equations; and to evaluate the performance of the Surface Energy and Radiation Balance System (SERBS). A total of 17 variables were monitored at each site. They included net, solar (up and down), total hemispherical (up and down), and diffuse radiation, soil temperature and heat flux density, air and wet bulb temperature gradients, wind speed and direction, and precipitation. A preliminary analysis of the data, for the season, indicate that variables including net radiation, air temperature, vapor pressure, and wind speed were quite similar at the sites even though the sites were as much as 16 km apart and represented four cardinal slopes and the top of a ridge.

Fritschen, Leo J.↗

Neptune’s Dynamic Atmosphere from Kepler K2 Observations: Implications for Brown Dwarf Light Curve Analyses

Observations of Neptune with the Kepler Space Telescope yield a 49-day light curve with 98% coverage at a 1-minute cadence. A significant signature in the light curve comes from discrete cloud features. We compare results extracted from the light curve data with contemporaneous disk-resolved imaging of Neptune from the Keck 10-meter and Hubble Space Telescope. The direct comparison validates the zonal wind profile and cloud feature variability information extracted from the light curve. Neptune’s clouds vary in location and intensity on short and long time scales, with large discrete storms dominating the light curves; smaller or fainter clouds contribute to its variability. This has implications for the interpretation of information extracted from light curves of directly imaged exoplanets and cloudy brown dwarfs.

Simon, Amy A.↗