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NASA NTRS2013

Diagnosing Aircraft Icing Potential from Satellite Cloud Retrievals

The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to the time and location of several recent aviation accidents and with icing PIREPS are also presented that reveal skill in identifying severe icing conditions. These results demonstrate the utility of satellite cloud retrievals for quantitatively diagnosing the potential for icing conditions on temporal and spatial scales that should be useful to the aviation community. Plans are being developed to deliver these new satellite products to the GOES-R Proving Ground in the near future so that they can be evaluated in operational applications.

Smith, William L., Jr.↗

NASA NTRS2018

Exploratory Analysis of the Airspace Throughput and Sensitivities of an Urban Air Mobility System

The use of small, vertical-takeoff and landing aircraft to provide efficient, high-speed, ondemand passenger transportation within a metropolitan area (e.g. intra-city transportation) is a topic of increasing interest and investment within the aerospace and transportation communities. Preliminary, mostly vehicle-level analysis suggests that passenger-carrying “Urban Air Mobility” has the potential to provide meaningful door-to-door trip time savings compared to identical trips taken solely by automobile, even for relatively short trips of a few tens of miles. Subsequent analysis has shown that if such trips can be conducted at costs competitive with ground transportation, the demand for such flight operations, not surprisingly, becomes unprecedented by historical airspace operations counts, raising fundamental questions regarding feasibility, practicality, capacity and basic system attributes such as separation criteria. In this paper, we conduct a preliminary assessment of vertipad requirements and en route separation minima relative to the feasibility of large-scale urban aviation operations. This analysis is acknowledged as being far from comprehensive and is intended to help define the initial boundaries of an airspace system compatible with enabling high-volume operations.

Goodrich, Kenneth H.↗

NASA NTRS2001

Operational Performance of Sensor Systems Used to Determine Atmospheric Boundary Layer Properties as Part of the NASA Aircraft Vortex Spacing System Project

There has been a renewed interest in the application of remote sensor technology to operational aviation and airport-related activities such as Aircraft Vortex Spacing System (AVOSS). Radio Acoustic Sounding Systems (RASS), Doppler-acoustic sodars, Ultrahigh Frequencies (UHF) profilers and lidars have many advantages in measuring wind and temperature profiles in the lower atmospheric boundary layer since they can operate more or less continuously and unattended; however, there are limitations in their operational use at airports. For example, profilers deteriorate (limited altitude coverage or missing) in moderate or greater rain and can be affected by airplane targets in their field of view. Sodars can handle precipitation better but are affected by the high noise environments of airports and strong winds. Morning temperature inversions typically limit performance of RASS, sodars and profilers. Fog affects sonic anemometers. Lidars can have difficulties in clouds, fog or heavy precipitation. Despite their limitations these sensors have proven useful to provide wind and temperature profiles for AVOSS. Capabilities and limitations of these and other sensors used in the AVOSS program are discussed, parameter settings for the sensor systems are documented, and recommendations are made for the most cost-effective group of sensors for the future. The potential use of specially tuned dynamic forecast models and measurements from landing and departing aircraft are addressed.

Zak, J. Allen↗

NASA NTRS2019

Ask-The-Expert: Minimizing Human Review for Big Data Analytics Through Active Learning

In this CIF project, we worked toward semi-automating knowledge discovery from anomaly detection algorithms through the use of active learning. Active learning is an area of research within machine learning that uses an "expert in the loop" to learn from large data sets that have very few annotations or labels available, and where providing such labels is expensive. In our case, the task can be defined as the identification of safety events from flight operational data. Since traditional anomaly detection algorithms cannot differentiate between operationally relevant and irrelevant statistical anomalies, Subject Matter Experts (SMEs) have a lengthy and expensive burden of investigating every example identified by the detection algorithm, classifying and labeling them as relevant or irrelevant. Active learningidentifies the unlabeled example for which a label would most improve the classifier, asks the domain expert for a label, and repeats this process until there are no more resources (time, budget) available for labeling or a minimum required performance is reached. A positive label indicates an operationally significant safety event whereas a negative label indicates otherwise. Based on these few labels we propose to build an active learning system that utilizes the SME's time in the most effective manner by iteratively asking for labels for as few informative instances as possible. Our work was proposed to be a stepping stone toward implementation and deployment of the system with user interface to be pursued by the Aviation Operations and Safety Program (AOSP) given its interest in safety monitoring and discovery of safety incidents.

aviation safety↗

NASA NTRSDate not supplied

Development of an Airspace Simulation and Modeling Tool for Enhanced Spectrum Management

The emergence of new aerial vehicles into the National Airspace System creates an increased demand for aeronautical communications to support aviation operations. However, the issue of spectrum scarcity remains an ever-present concern, and the growing demand cannot be supported using existing spectrum allocation strategies. As a result, a new spectrum management approach is required, and the National Aeronautics and Space Administration (NASA) is investigating advanced concepts to modernize the management and use of aviation spectrum by leveraging the latest advancements in wireless communications, big data and machine learning. This research proposes an autonomous spectrum allocation concept, which allocates communications resources, such as spectrum and power, based on the predicted communications and air traffic demands throughout the airspace, as opposed to the use of fixed allocations as is done today. This approach will result in improved spectrum utilization efficiency and enhanced airspace capacity. The autonomous spectrum allocation concept decomposes into three research areas: demand prediction, resource allocation, and use case evaluation. As part of the use case evaluation effort, a modeling and simulation capability is currently under development. This simulation capability includes the implementation of various features, including visualization of both live or virtually-generated airspace traffic, simulation scenario development, simulation management with data collection, and flight plan creation with corresponding trajectory generation. This modeling and simulation capability will continue to evolve as new and advanced airspace applications are introduced into existing and emerging operational environments.

Eric J. Knoblock↗

NASA NTRS2012

Technologies Render Views of Earth for Virtual Navigation

On a December night in 1995, 159 passengers and crewmembers died when American Airlines Flight 965 flew into the side of a mountain while in route to Cali, Colombia. A key factor in the tragedy: The pilots had lost situational awareness in the dark, unfamiliar terrain. They had no idea the plane was approaching a mountain until the ground proximity warning system sounded an alarm only seconds before impact. The accident was of the kind most common at the time CFIT, or controlled flight into terrain says Trey Arthur, research aerospace engineer in the Crew Systems and Aviation Operations Branch at NASA s Langley Research Center. In situations such as bad weather, fog, or nighttime flights, pilots would rely on airspeed, altitude, and other readings to get an accurate sense of location. Miscalculations and rapidly changing conditions could contribute to a fully functioning, in-control airplane flying into the ground. To improve aviation safety by enhancing pilots situational awareness even in poor visibility, NASA began exploring the possibilities of synthetic vision creating a graphical display of the outside terrain on a screen inside the cockpit. How do you display a mountain in the cockpit? You have to have a graphics-powered computer, a terrain database you can render, and an accurate navigation solution, says Arthur. In the mid-1990s, developing GPS technology offered a means for determining an aircraft s position in space with high accuracy, Arthur explains. As the necessary technologies to enable synthetic vision emerged, NASA turned to an industry partner to develop the terrain graphical engine and database for creating the virtual rendering of the outside environment.

Source record↗

NASA NTRS1997

A Practical Guide to Interpretation of Large Collections of Incident Narratives Using the QUORUM Method

Analysis of incident reports plays an important role in aviation safety. Typically, a narrative description, written by a participant, is a central part of an incident report. Because there are so many reports, and the narratives contain so much detail, it can be difficult to efficiently and effectively recognize patterns among them. Recognizing and addressing recurring problems, however, is vital to continuing safety in commercial aviation operations. A practical way to interpret large collections of incident narratives is to apply the QUORUM method of text analysis, modeling, and relevance ranking. In this paper, QUORUM text analysis and modeling are surveyed, and QUORUM relevance ranking is described in detail with many examples. The examples are based on several large collections of reports from the Aviation Safety Reporting System (ASRS) database, and a collection of news stories describing the disaster of TWA Flight 800, the Boeing 747 which exploded in mid- air and crashed near Long Island, New York, on July 17, 1996. Reader familiarity with this disaster should make the relevance-ranking examples more understandable. The ASRS examples illustrate the practical application of QUORUM relevance ranking.

McGreevy, Michael W.↗

NASA NTRS2017

Considerations for an Integrated UAS CNS Architecture

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating revolutionary and advanced universal, reliable, always available, cyber secure and affordable Communication, Navigation, Surveillance (CNS) options for all altitudes of UAS operations. In Spring 2015, NASA issued a Call for Proposals under NASA Research Announcements (NRA) NNH15ZEA001N, Amendment 7 Subtopic 2.4. Boeing was selected to conduct a study with the objective to determine the most promising candidate technologies for Unmanned Air Systems (UAS) air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. The overall objectives are to develop UAS CNS requirements and then develop architectures that satisfy the requirements for UAS in both controlled and uncontrolled air space. This contract is funded under NASAs Aeronautics Research Mission Directorates (ARMD) Aviation Operations and Safety Program (AOSP) Safe Autonomous Systems Operations (SASO) project and proposes technologies for the Unmanned Air Systems Traffic Management (UTM) service.There is a need for accommodating large-scale populations of Unmanned Air Systems (UAS) in the national air space. Scale obviously impacts capacity planning for Communication, Navitation, and Surveillance (CNS) technologies. For example, can wireless communications data links provide the necessary capacity for accommodating millions of small UASs (sUAS) nationwide? Does the communications network provide sufficient Internet Protocol (IP) address space to allow air traffic control to securely address both UAS teams as a whole as well as individual UAS within each team? Can navigation and surveillance approaches assure safe route planning and safe separation of vehicles even in crowded skies?Our objective is to identify revolutionary and advanced CNS alternatives supporting UASs operating at all altitudes and in all airspace while accurately navigating in the absence of navigational aids. These CNS alternatives must be reliable, redundant, always available, cyber-secure, and affordable for all types of vehicles including small UAS to large transport category aircraft. The approach will identify CNS technology candidates that can meet the needs of the range of UAS missions to specific air traffic management applications where they will be most beneficial and cost effective.

Templin, Fred L.↗

NASA NTRS2017

Considerations for an Integrated UAS CNS Architecture

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating revolutionary and advanced universal, reliable, always available, cyber secure and affordable Communication, Navigation, Surveillance (CNS) options for all altitudes of UAS operations. In Spring 2015, NASA issued a Call for Proposals under NASA Research Announcements (NRA) NNH15ZEA001N, Amendment 7 Subtopic 2.4. Boeing was selected to conduct a study with the objective to determine the most promising candidate technologies for Unmanned Air Systems (UAS) air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. The overall objectives are to develop UAS CNS requirements and then develop architectures that satisfy the requirements for UAS in both controlled and uncontrolled air space. This contract is funded under NASAs Aeronautics Research Mission Directorates (ARMD) Aviation Operations and Safety Program (AOSP) Safe Autonomous Systems Operations (SASO) project and proposes technologies for the Unmanned Air Systems Traffic Management (UTM) service.There is a need for accommodating large-scale populations of Unmanned Air Systems (UAS) in the national air space. Scale obviously impacts capacity planning for Communication, Navigation, and Surveillance (CNS) technologies. For example, can wireless communications data links provide the necessary capacity for accommodating millions of small UASs (sUAS) nationwide? Does the communications network provide sufficient Internet Protocol (IP) address space to allow air traffic control to securely address both UAS teams as a whole as well as individual UAS within each team? Can navigation and surveillance approaches assure safe route planning and safe separation of vehicles even in crowded skies?Our objective is to identify revolutionary and advanced CNS alternatives supporting UASs operating at all altitudes and in all airspace while accurately navigating in the absence of navigational aids. These CNS alternatives must be reliable, redundant, always available, cyber-secure, and affordable for all types of vehicles including small UAS to large transport category aircraft. The approach will identify CNS technology candidates that can meet the needs of the range of UAS missions to specific air traffic management applications where they will be most beneficial and cost effective.

Templin, Fred L.↗

NASA NTRS2017

Requirements for an Integrated UAS CNS Architecture

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating revolutionary and advanced universal, reliable, always available, cyber secure and affordable Communication, Navigation, Surveillance (CNS) options for all altitudes of UAS operations. In Spring 2015, NASA issued a Call for Proposals under NASA Research Announcements (NRA) NNH15ZEA001N, Amendment 7 Subtopic 2.4. Boeing was selected to conduct a study with the objective to determine the most promising candidate technologies for Unmanned Air Systems (UAS) air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. The overall objectives are to develop UAS CNS requirements and then develop architectures that satisfy the requirements for UAS in both controlled and uncontrolled air space. This contract is funded under NASAs Aeronautics Research Mission Directorates (ARMD) Aviation Operations and Safety Program (AOSP) Safe Autonomous Systems Operations (SASO) project and proposes technologies for the Unmanned Air Systems Traffic Management (UTM) service. Communications, Navigation and Surveillance (CNS) requirements must be developed in order to establish a CNS architecture supporting Unmanned Air Systems integration in the National Air Space (UAS in the NAS). These requirements must address cybersecurity, future communications, satellite-based navigation APNT, and scalable surveillance and situational awareness. CNS integration, consolidation and miniaturization requirements are also important to support the explosive growth in small UAS deployment. Air Traffic Management (ATM) must also be accommodated to support critical Command and Control (C2) for Air Traffic Controllers (ATC). This document therefore presents UAS CNS requirements that will guide the architecture.

Templin, Fred↗

NASA NTRS2002

General Aviation Pilots' Perceived Usage and Valuation of Aviation Weather Information Sources

Aviation suffers many accidents due to the lack of good weather information in flight. Existing aviation weather information is difficult to obtain when it is most needed and is not well formatted for in-flight use. Because it is generally presented aurally, aviation weather information is difficult to integrate with spatial flight information and retain for reference. Efforts, by NASA's Aviation Weather Information (AWIN) team and others, to improve weather information accessibility, usability and decision aiding will enhance General Aviation (GA) pilots' weather situation awareness and decision-making and therefore should improve the safety of GA flight. Consideration of pilots' economic concerns will ensure that in-flight weather information systems are financially accessible to GA pilots as well. The purpose of this survey was to describe how aviation operator communities gather and use weather information as well as how weather related decisions are made between flight crews and supporting personnel. Pilots of small GA aircraft experience the most weather-related accidents as well as the most fatal weather related accident. For this reason, the survey design and advertisement focused on encouraging participation from GA pilots. Perhaps as a result of this emphasis, most responses, 97 responses or 85% of the entire response set, were from GA pilots, This paper presents only analysis of these GA pilots' responses. The insights provided by this survey regarding GA pilots' perceived value and usage of current aviation weather information. services, and products provide a basis for technological approaches to improve GA safety. Results of this survey are discussed in the context of survey limitations and prior work, and serve as the foundation for a model of weather information value, guidance for the design of in-flight weather information systems, and definition of further research toward their development.

Latorella, Kara↗

NASA NTRS2017

The Impacts of Rising Temperatures on Aircraft Takeoff Performance

Steadily rising mean and extreme temperatures as a result of climate change will likely impact the air transportation system over the coming decades. As air temperatures rise at constant pressure, air density declines, resulting in less lift generation by an aircraft wing at a given airspeed and potentially imposing a weight restriction on departing aircraft. This study presents a general model to project future weight restrictions across a fleet of aircraft with different takeoff weights operating at a variety of airports. We construct performance models for five common commercial aircraft and 19 major airports around the world and use projections of daily temperatures from the CMIP5 model suite under the RCP 4.5 and RCP 8.5 emissions scenarios to calculate required hourly weight restriction. We find that on average, 10 - 30% of annual flights departing at the time of daily maximum temperature may require some weight restriction below their maximum takeoff weights, with mean restrictions ranging from 0.5 to 4% of total aircraft payload and fuel capacity by mid- to late century. Both mid-sized and large aircraft are affected, and airports with short runways and high temperatures, or those at high elevations, will see the largest impacts. Our results suggest that weight restriction may impose a non-trivial cost on airlines and impact aviation operations around the world and that adaptation may be required in aircraft design, airline schedules, and/or runway lengths.

air transportation system↗

NASA NTRSDate not supplied

End-User Assessment of the NASA SPoRT Lightning AI Product

The NASA Short-term Prediction Research and Transition (SPoRT) Center has begun to develop products to address operational challenges and enhance safety during the lifecycle of lightning activity, and conduct evaluations in concentrated R2O/O2R efforts. The product evaluated for this study is Lightning Artificial Intelligence (A.I.), which predicts the probability of lightning out to 15 minutes in advance and spatially maps it using filled color contours. Lightning A.I. uses reflectivity, differential reflectivity, and correlation coefficient data from a subset of radars within the NEXRAD network to generate lightning probabilities at approximately 2 km resolution. The domains, spanning 145 x 145 km are centered over NASA-affiliated centers across the CONUS and use radar data which are closest in proximity. Lightning A.I. was developed with intended use by emergency managers at NASA centers. However, National Weather Service (NWS) offices are also often tasked with monitoring and forecasting the threat for lightning within their County Warning Areas for various impact-based decision support services. These forecasts are typically provided for aviation operations and large-scale, outdoor events, which may have varying safety requirements for decision-making based on lightning proximity and recency. The NASA SPoRT center conducted an assessment of the operational uses of Lightning A.I by various collaborative NWS Offices from late July into early September. This assessment included feedback from participants on both the product itself as well as its accessibility within the new, interactive NASA SPoRT Lightning Viewer. This presentation will include background information about Lightning A.I. and highlight results from this assessment. The feedback from the assessment will be used to inform research on any necessary modifications to this and future lightning products to assist end users.

Kelley Murphy↗

NASA NTRSDate not supplied

Investigating the Causes and Consequences of Controlled Rest on the Flight Deck

INTRODUCTION: Long and irregular working hours can lead to fatigue in aviation operations. In some regions, a short nap taken on the flight deck (known as controlled rest) can be used as a countermeasure to unexpected in-flight sleepiness. We aimed to investigate the impact of taking controlled rest on self-reported sleepiness at top-of-descent. METHODS: Data from 120 long-haul (> 6 h flight duration), unaugmented flights were analyzed (n = 31 pilots). Pilots wore actigraphs and completed sleep logs before and during trips. At pre-flight and top-of-descent, pilots completed a Karolinska Sleepiness Scale (KSS). A mixed-effects model was used to assess the impact of controlled rest on KSS at top-of-descent. Sleep duration in the 48 hours prior to departure, timing of the flight (day vs. night), and pre-flight KSS scores were included as covariates. RESULTS: Due to missing data, complete data from 83 flights (n = 29 participants) were available in the analyses of the KSS. There were no differences by controlled rest status for KSS scores at top-of-descent (estimated marginal means ± SEM with controlled rest: 5.10 ± 0.22, without controlled rest: 5.37 ± 0.29; p = .45, η2p = 0.01). DISCUSSION: Our results suggest that there is no difference in self-reported sleepiness at top-of-descent on flights in which controlled rest was taken compared to flights without controlled rest. Further research is necessary to determine the impact of controlled rest on objective measures of performance at top-of-descent.

aviation↗

NASA NTRSDate not supplied

The Impact of Controlled Rest on Self-Reported Sleepiness at Top-of-Descent

aviation↗

NASA NTRSDate not supplied

The Impact of Controlled Rest on Neurobehavioral Outcomes at Top-of-Descent

INTRODUCTION: Long and irregular working hours can lead to fatigue in aviation operations. In some regions, a short nap taken on the flight deck (known as controlled rest) can be used as a countermeasure to unexpected in-flight sleepiness. We aimed to investigate the impact of taking controlled rest on neurobehavioral measures at top-of-descent. METHODS: Data from 120 long-haul (> 6 h flight duration), unaugmented flights were analyzed (n = 31 pilots). Pilots wore actigraphs and completed sleep logs before and during trips. At pre-flight and top-of-descent, pilots completed a 5-minute psychomotor vigilance task (PVT) and Karolinska Sleepiness Scale (KSS). A series of mixed-effects models were conducted to assess the impact of controlled rest on outcome measures at top-of-descent. Sleep duration in the prior 48 hours, timing of the flight, and pre-flight scores for each measure were included as covariates. RESULTS: Due to missing data, complete data from 76 flights (n = 28 participants) were available in the models examining the PVT metrics, and data from 83 flights (n = 29 participants) were available in the analyses of the KSS. Pilots who took controlled rest had faster response speeds at top-of-descent (p = .03, η2p = 0.07; estimated marginal mean [EMM] = 4.19, standard error [SE] = 0.07, 95% CI [4.08, 4.29]) than those who did not take controlled rest (EMM = 4.00, SE = 0.05, 95% CI [3.86, 4.14]). There were no differences by controlled rest status for KSS scores and PVT lapses (p values > .05, η2p values ≤ 0.01). DISCUSSION: Our results suggest that taking controlled rest may improve vigilant attention at critical phases of flight and, thus, may be a useful fatigue management tool during unaugmented flights. Further research is necessary to determine the impact of factors on the decision to take controlled rest (e.g., airline culture, personal preference) and how the controlled rest policy is applied in practice.

aviation↗

NASA NTRS1973

A comparative analysis of area navigation systems in general aviation

Radio navigation systems which offer the capabilities of area navigation to general aviation operators are discussed. The systems considered are: (1) the VORTAC system, (2) the Loran-C system, and (3) the Differential Omega system. The inital analyses are directed toward a comparison of the systems with respect to their compliance to specified performance parameters and to the cost effectiveness of each system in relation to those specifications. Further analyses lead to the development of system cost sensitivity charts, and the employment of these charts allows conclusions to be drawn relative to the cost-effectiveness of the candidate navigation system.

Dodge, S. M.↗

NASA NTRS1976

Wind shear and turbulence around airports

A two part study was conducted to determine the feasibility of predicting the conditions under which wind/turbulence environments hazardous to aviation operations exist. The computer model used to solve the velocity temperature, and turbulence distributions in the atmospheric boundary layer is described, and the results of a parameteric analysis to determine the expected range of wind shear and turbulence to be encountered in the vicinity of airports are given. The second part describes the delineation of an ensemble of aircraft accidents in which low level wind shear and/or turbulence appeared to be causative factors. This set of accidents, encompassing a wide range of meteorological conditions, should prove useful in developing techniques for reconstructing hazardous wind environments for aircraft safety investigation purposes.

Lewellen, W. S.↗