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At least 73 records · Page 4

Vibro-Acoustic Response of Buildings Due to Sonic Boom Exposure: July 2007 Field Test

During the month of July 2007, a series of structural response measurements were made on a house on Edwards Air Force Base (EAFB) property that was exposed to sonic booms of various amplitudes. The purpose of this report is to document the measurements that were made, the structure on which they were made, the conditions under which they were made, the sensors and other hardware that were used, and the data that were collected. To that end, Chapter 2 documents the house, its location, the physical layout of the house, the surrounding area, and summarizes the transducers placed in and around the house. Chapter 3 details the sensors and other hardware that were placed in the house during the experiment. In addition, day-to-day variations of hardware configurations and transducer calibrations are documented in Chapter 3. Chapter 4 documents the boom generation process, flight conditions, and ambient weather conditions during the test days. Chapter 5 includes information about sub-experiments that were performed to characterize the vibro-acoustic response of the structure, the acoustic environment inside the house, and the acoustic environment outside the house. Chapter 6 documents the data format and presents examples of reduced data that were collected during the test days.

Klos, Jacob↗

Fire in the Arctic: Current Trends and Future Pathways

Wildland fires in the Arctic are expected to become more frequent and more severe. In recent years, extreme fire seasons have been documented across the Pan-Arctic and boreal in five of the last seven years – including large wildfires in Greenland in 2017 and 2019 over tundra and high carbon soil landscapes and an earlier start of extreme fire seasons in 2023. Future Arctic and boreal fire regimes will experience increased fire risk though the end of this century (McCarty et al., 2021, Senande-Rivera et al., 2022). The main factors affecting the severity and frequency of wildland fires are fuels (vegetated biomass and type of biomass) and fuel condition (dryness), fire weather conditions (relative humidity, drought, precipitation), and ignition (human-caused, lightning). Climate change directly influences all of these drivers, and indirectly also some human-caused ignitions.

Fire↗

A report on the upper-level wind conditions preceding and during the Shuttle Challenger (STS 51L) explosion

The prelaunch, launch, and postlaunch synoptic-scale weather conditions on January 28, 1986 are described. Particular consideration is given to upper-level jet streams, vertical wind shear, and the possible effect of shear-induced turbulence on Cape Canaveral at the time of the Shuttle launch. General data revealing the relations between wind shear and turbulence and jet streams are discussed. The NWS operational and surface radiosonde data, visible and IR GOES imagery, and total ozone data obtained from TOMS on Nimbus-7 are analyzed. Numerical simulations of the weather conditions were conducted. The simulations and observational data are compared, and the data reveal the juxtaposition of two distinct jet-stream systems (a polar front jet and a subtropical jet) over north-central Florida the morning of the launch. Recommendations for improving the observing system at Cape Canaveral are discussed.

Uccellini, Louis W.↗

Coherent Pulsed Lidar Sensing of Wake Vortex Position and Strength, Winds and Turbulence in the Terminal Area

NASA Langley Research Center (LaRC) has field tested a 2.0 gm, 100 Hertz, pulsed coherent lidar to detect and characterize wake vortices and to measure atmospheric winds and turbulence. The quantification of aircraft wake-vortex hazards is being addressed by the Wake Vortex Lidar (WVL) Project as part of Aircraft Vortex Spacing System (AVOSS), which is under the Reduced Spacing Operations Element of the Terminal Area Productivity (TAP) Program. These hazards currently set the minimum, fixed separation distance between two aircraft and affect the number of takeoff and landing operations on a single runway under Instrument Meteorological Conditions (IMC). The AVOSS concept seeks to safely reduce aircraft separation distances, when weather conditions permit, to increase the operational capacity of major airports. The current NASA wake-vortex research efforts focus on developing and validating wake vortex encounter models, wake decay and advection models, and wake sensing technologies. These technologies will be incorporated into an automated AVOSS that can properly select safe separation distances for different weather conditions, based on the aircraft pair and predicted/measured vortex behavior. The sensor subsystem efforts focus on developing and validating wake sensing technologies. The lidar system has been field-tested to provide real-time wake vortex trajectory and strength data to AVOSS for wake prediction verification. Wake vortices, atmospheric winds, and turbulence products have been generated from processing the lidar data collected during deployments to Norfolk (ORF), John F. Kennedy (JFK), and Dallas/Fort Worth (DFW) International Airports.

Brockman, Philip↗

Surface Landing Site Weather Analysis for Constellation Program

Weather information is an important asset for NASA's Constellation Program in developing the next generation space transportation system to fly to the International Space Station, the Moon and, eventually, to Mars. Weather conditions can affect vehicle safety and performance during multiple mission phases ranging from pre-launch ground processing to landing and recovery operations, including all potential abort scenarios. Meteorological analysis is an important contributor, not only to the development and verification of system design requirements but also to mission planning and active ground operations. Of particular interest are the surface atmospheric conditions at both nominal and abort landing sites for the manned Orion capsule. Weather parameters such as wind, rain, and fog all play critical roles in the safe landing of the vehicle and subsequent crew and vehicle recovery. The Marshall Space Flight Center Natural Environments Branch has been tasked by the Constellation Program with defining the natural environments at potential landing zones. Climatological time series of operational surface weather observations are used to calculate probabilities of occurrence of various sets of hypothetical vehicle constraint thresholds, Data are available for numerous geographical locations such that statistical analysis can be performed for single sites as well as multiple-site network configurations. Results provide statistical descriptions of how often certain weather conditions are observed at the site(s) and the percentage that specified criteria thresholds are matched or exceeded. Outputs are tabulated by month and hour of day to show both seasonal and diurnal variation. This paper will describe the methodology used for data collection and quality control, detail the types of analyses performed, and provide a sample of the results that can be obtained,

Altino, Karen M.↗

Advanced Weather Hazard Perception Capabilities for Remotely Piloted Aircraft in Wildland Fire Operations

Weather, specifically winds, are the most variable and least predictable of the weather-related elements that affect wildfire behavior.1 This leads to aviation operations which must deal with increased risks due to dynamic weather factors. Remotely piloted aircraft provide the opportunity to remove human loss of life from these risk consequences and mitigate the overall risks for air operations for fire suppression and dropping of retardant. UAS also allows the opportunity to continue fire suppression with nighttime operations. However, with the use of new technologies in aviation operations comes additional risk factors and the need for remote sensing capabilities to identify and permit navigation around extreme weather conditions, with turbulence being the most unforeseeable. This paper presents advanced concepts for weather hazard perception capabilities for remote pilot operators to include data and display techniques intended for dynamic environments and low altitude operations. This work can support the potential of weather sensing capabilities to create hazard maps to track high-risk weather patterns in mountainous regions. Advanced sensing may provide opportunity to locate extreme turbulence hazards for uninhabited aerial systems (UAS) and decrease the likelihood of flying into unknown weather conditions to enable safe operations to assist in wildfire air support.

Tyler L Willhite↗

Extreme Space Weather Events and Charging Hazard Assessments in Lunar Environments

The sunlit lunar surface charges to positive potentials with mean values of a few tens of volts where photoelectron currents dominate the charging process. In contrast, surfaces in darkness may charge to negative potentials on the order of a few hundred volts when the charging process is dominated by hot electron populations in the absence of solar photons. Recently, observations of electron beams measured by instruments on spacecraft in low lunar orbit have been interpreted as evidence for extreme lunar surface potentials exceeding a few kilovolts suggesting that lunar orbital and surface plasma environments may contain charging risks similar to geostationary orbit during extreme space weather conditions. Space system design for successful operation in a wide range of lunar environments will therefore require evaluation of charging hazards during extreme space weather conditions. We present results from a study of space weather environments conducted to obtained credible extreme charging environments for use in charging hazard assessments for lunar missions including extreme conditions encountered when the Moon is in the solar wind, the magnetosheath, and the Earth's magnetotail.

Minow, Joseph I.↗

Aircraft and ground vehicle friction measurements obtained under winter runway conditions

Tests with specially instrumented NASA B-737 and B-727 aircraft together with several different ground friction measuring devices have been conducted for a variety of runway surface types and wetness conditions. This effort is part of the Joint FAA/NASA Aircraft/Ground Vehicle Runway Friction Program aimed at obtaining a better understanding of aircraft ground handling performance under adverse weather conditions, and defining relationships between aircraft and ground vehicle tire friction measurements. Aircraft braking performance on dry, wet, snow-, and ice-covered runway conditions is discussed together with ground vehicle friction data obtained under similar runway conditions. For the wet, compacted snow- and ice-covered runway conditions, the relationship between ground vehicles and aircraft friction data is identified. The influence of major test parameters on friction measurements such as speed, test tire characteristics, and surface contaminant-type are discussed. The test results indicate that use of properly maintained and calibrated ground vehicles for monitoring runway friction conditions should be encouraged particularly under adverse weather conditions.

Yager, Thomas J.↗

Current status of Joint FAA/NASA Runway Friction Program

Tests with specially instrumented NASA B-737 and FAA B-727 aircraft together with several different ground friction measuring devices have been conducted for a variety of runway surface types and wetness conditions. This effort is part of the Joint FAA/NASA Aircraft Ground Vehicle Runway Friction Program aimed at obaining a better understanding of aircraft ground handling performance under adverse weather conditions and defining relationships between aircraft and ground vehicle tire friction measurements. Aircraft braking performance on dry, wet, snow-, and ice-covered runway conditions is discussed together with ground vehicle friction data obtained under similar runway conditions. For the wet, compacted snow- and ice-covered runway conditions, the relationship between ground vehicles and aircraft friction data is identified. The influence of major test parameters on friction measurements such as speed, test tire characteristics, and surface contaminant type are discussed. The test results indicate that use of properly maintained and calibrated ground vehicles for monitoring runway friction conditions should be encouraged particularly under adverse weather conditions. The current status of the runway friction program is summarized and future test plans are identified.

Yager, Thomas J.↗

Evaluation of Candidate Millimeter Wave Sensors for Synthetic Vision

The goal of the Synthetic Vision Technology Demonstration Program was to demonstrate and document the capabilities of current technologies to achieve safe aircraft landing, take off, and ground operation in very low visibility conditions. Two of the major thrusts of the program were (1) sensor evaluation in measured weather conditions on a tower overlooking an unused airfield and (2) flight testing of sensor and pilot performance via a prototype system. The presentation first briefly addresses the overall technology thrusts and goals of the program and provides a summary of MMW sensor tower-test and flight-test data collection efforts. Data analysis and calibration procedures for both the tower tests and flight tests are presented. The remainder of the presentation addresses the MMW sensor flight-test evaluation results, including the processing approach for determination of various performance metrics (e.g., contrast, sharpness, and variability). The variation of the very important contrast metric in adverse weather conditions is described. Design trade-off considerations for Synthetic Vision MMW sensors are presented.

Alexander, Neal T.↗

Determination of the Limiting Magnitude

The limiting magnitude of an optical camera system is an important property to understand since it is used to find the completeness limit of observations. Limiting magnitude depends on the hardware and software of the system, current weather conditions, and the angular speed of the objects observed. If an object exhibits a substantial angular rate during the exposure, its light spreads out over more pixels than the stationary stars. This spreading causes the limiting magnitude to be brighter when compared to the stellar limiting magnitude. The effect, which begins to become important when the object moves a full width at half max during a single exposure or video frame. For targets with high angular speeds or camera systems with narrow field of view or long exposures, this correction can be significant, up to several magnitudes. The stars in an image are often used to measure the limiting magnitude since they are stationary, have known brightness, and are present in large numbers, making the determination of the limiting magnitude fairly simple. In order to transform stellar limiting magnitude to object limiting magnitude, a correction must be applied accounting for the angular velocity. This technique is adopted in meteor and other fast-moving object observations, as the lack of a statistically significant sample of targets makes it virtually impossible to determine the limiting magnitude before the weather conditions change. While the weather is the dominant factor in observing satellites, the limiting magnitude for meteors also changes throughout the night due to the motion of a meteor shower or sporadic source radiant across the sky. This paper presents methods for determining the limiting stellar magnitude and the conversion to the target limiting magnitude.

Kingery, Aaron↗

Contrasting Trends in Colorado Fire Weather Index from Reanalysis and Observations

Recent wildfires in Colorado raise the question of whether rising global temperatures have increased fire weather occurrences in Colorado. The U.S. National Weather Service defines fire weather as when “forecast weather conditions will result in a significant threat for the ignition and/or spread of wildfires.” We use two datasets to address the question: “How has the occurrence of fire weather changed in Colorado?” Using 22 years of observed weather conditions from a meteorological tower at the National Renewable Energy Laboratory and 67 years of ERA5 reanalysis data, we assess changing trends in Colorado fire weather as defined by hot, dry, and windy conditions. Additionally, we explore if the difference in recorded wind speeds between observational data and reanalysis data can be explained by differences in spatial and temporal resolution and what are the implications in the context of quantifying fire weather occurrences. The observational data are limited in temporal extent and spatial representativeness, but they capture exact real-world conditions at a location in complex terrain. The reanalysis data are available for an extended period of time and for the entire state, but the data are of relatively coarse spatial and temporal resolution and may fail to capture extremes. To quantify fire risk, we calculate the hot–dry–windy index (HDWI), which relies on wind speed and vapor pressure deficit. No statistically significant trend in the HDWI appears in the observational dataset. However, according to the reanalysis data, strong increasing trends in HDWI values emerge across all of Colorado. This apparent conflict between observational and reanalysis data suggests that reanalysis data may not be representative. Further, more long-term observational datasets are required to assess fire risk.

17 WIND ENERGY↗

Optimizing Air Traffic - Integrating Artificial Intelligence and Machine Learning in Flight Path Planning and 3D Airspace Visualization for Air Traffic Control

Air Traffic Control (ATC) systems are vital components of the National Airspace System (NAS). ATC, Airport Traffic Control Towers (ATCT), and Terminal Radar Approach Control (TRACON) are responsible for directing all flights departing from and arriving at airports, managing our nation’s airspace, preventing potential accidents, and ensuring that every flight is accounted for. However, these systems often face challenges in effectively monitoring the skies. Issues such as poor communication between operators, difficulty in performing operations, and the constant need for vigilance frequently burden ATC operators. Additionally, the projected increase in air traffic in the coming years will only exacerbate the stress associated with this role. To address these issues, we propose a system that assists ATC operators in situations such as handovers, emergencies, and routing aircraft to avoid weather hazards. Our solution includes an Artificial Intelligence (AI) and Machine Learning (ML)-based Flight Pathways Planning System (FPPS) designed to find the fastest and most optimal routes for aircraft, taking into account weather conditions, restricted terrain, and Extended-Range Twin-Engine Operational Performance Standards (ETOPS) ratings. The proposed Predictive Weather Planning Model, included in FPPS, adjusts routes based on real-time and forecasted weather conditions. Additionally, our NVIDIA Omniverse 3D Visualization System offers a highly interactive environment for better visualization and a clear view of the airspace. By incorporating these systems, the roles of ATC, ATCT, and TRACON operators will become more manageable and less stressful, equipping them to efficiently handle the growing density of airspace.

Regina Ayoubi↗

A Markov Decision Process Framework for Optimal Airport Reconfiguration

The airport runway configuration is defined as a combination set of runways for arrivals and departures used at a point during operation of the airport. An optimal configuration of these runways depends on a number of factors, including traffic demand, wind magnitude and direction, other adverse weather conditions, and noise restrictions, among others. Based on the current state of these factors and predictions of traffic demand and weather conditions, runway configuration changes are made and coordinated between tower controller, other air traffic control facilities, pilots, and ground personnel. Reconfigurations can be quite disruptive to airport operations; minimizing their frequency and scheduling them well in advance is essential for mitigating some of the added workload for controllers and pilots. Unfortunately, deciding on an appropriate time to change is challenging for human decision makers. Not only do multiple factors need to be evaluated, but the uncertainty in their forecasts must also be considered. Previous optimization methods, such as mixed linear integer programming, have been proposed. Although these methods can reason over a large set of variables, they do not systematically handle the uncertainty associated with weather movement, traffic demands, and other variables. In this work, we introduce a Markov Decision Process (MDP)-based decision making framework which can reason effectively over the inherent uncertainties and make optimal decisions on if/when to change the airport configuration. In a prototype implementation, we present a single runway with three aircraft and utilize knowledge of the forecasted wind speed and direction to determine whether to keep or change the current runway configuration. Our aim through this work is to present a framework for airport reconfiguration which can be scalable to additional aircraft, multiple runways, and various input parameters. This technique will optimize the airport reconfiguration procedure by providing a proactive approach, optimizing not just at the next optimal opportunity for a reconfiguration based on varying atmospheric and traffic conditions in the terminal airspace, but also anticipating future necessary reconfigurations. This will eliminate the inefficiencies of frequent changes currently associated with runway reconfiguration procedures.

runway reconfiguration↗

NASA Aircraft Vortex Spacing System Development Status

The National Aeronautics and Space Administration (NASA) is addressing airport capacity enhancements during instrument meteorological conditions through the Terminal Area Productivity (TAP) program. Within TAP, the Reduced Spacing Operations (RSO) subelement at the NASA Langley Research Center is developing an Aircraft VOrtex Spacing System (AVOSS). AVOSS will integrate the output of several systems to produce weather dependent, dynamic wake vortex spacing criteria. These systems provide current and predicted weather conditions, models of wake vortex transport and decay in these weather conditions, and real-time feedback of wake vortex behavior from sensors. The goal of the NASA program is to provide the research and development to demonstrate an engineering model AVOSS in real-time operation at a major airport. The demonstration is only of concept feasibility, and additional effort is required to deploy an operational system for actual aircraft spacing reduction. This paper describes the AVOSS system architecture, a wake vortex facility established at the Dallas-Fort Worth International Airport (DFW), initial operational experience with the AVOSS system, and emerging considerations for subsystem requirements. Results of the initial system operation suggest a significant potential for reduced spacing.

Hinton, David A.↗

NASA Wake Vortex Research for Aircraft Spacing

The National Aeronautics and Space Administration (NASA) is addressing airport capacity enhancements during instrument meteorological conditions through the Terminal Area Productivity (TAP) program. Within TAP, the Reduced Spacing Operations (RSO) subelement at the NASA Langley Research Center is developing an Aircraft Vortex Spacing System (AVOSS). AVOSS will integrate the output of several inter-related areas to produce weather dependent, dynamic wake vortex spacing criteria. These areas include current and predicted weather conditions, models of wake vortex transport and decay in these weather conditions, real-time feedback of wake vortex behavior from sensors, and operationally acceptable aircraft/wake interaction criteria. In today's ATC system, the AVOSS could inform ATC controllers when a fixed reduced separation becomes safe to apply to large and heavy aircraft categories. With appropriate integration into the Center/TRACON Automation System (CTAS), AVOSS dynamic spacing could be tailored to actual generator/follower aircraft pairs rather than a few broad aircraft categories.

Perry, R. Brad↗

Modeling of Multiscale Solar Dynamics for Understanding Drivers of Space Weather

Understanding the solar dynamics is critical for improving our capabilities to forecast the evolution of space weather conditions. We take advantage of currently available computational capabilities to model solar dynamics from the deep interior to the corona and investigate mechanisms that may drive space weather conditions. The simulations are performed using the 3D radiative MHD code StellarBox. Comparison of synthetic spectroscopic observables obtained from numerical simulations and actual observations allows us to uncover physical processes associated with observed phenomena. To facilitate a transition from modeling short-term physical phenomena to developing a reliable forecast-oriented model, we suggest using the data assimilation approach. It allows us to cross-analyze dynamo model solutions and observations and to consider possible uncertainties and errors. In this presentation, we briefly summarize current multi-scale modeling capabilities and results and discuss ongoing developments to build a reliable physics-based forecast-oriented model of solar activity.

Irina N Kitiashvili↗

Modeling of Multiscale Solar Dynamics for Understanding Drivers of Space Weather

Understanding the solar dynamics is critical for improving our capabilities to forecast the evolution of space weather conditions. We take advantage of currently available computational capabilities to model solar dynamics from the deep interior to the corona and investigate mechanisms that may drive space weather conditions. The simulations are performed using the 3D radiative MHD code StellarBox. Comparison of synthetic spectroscopic observables obtained from numerical simulations and actual observations allows us to uncover physical processes associated with observed phenomena. To facilitate a transition from modeling short-term physical phenomena to developing a reliable forecast-oriented model, we suggest using the data assimilation approach. It allows us to cross-analyze dynamo model solutions and observations and to consider possible uncertainties and errors. In this presentation, we briefly summarize current multi-scale modeling capabilities and results and discuss ongoing developments to build a reliable physics-based forecast-oriented model of solar activity

Irina N Kitiashvili↗