Search NASA⌕ Search

SEARCH · Search NASA

Results for “aviation operations”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Sustainable Aviation Operations and the Role of Information Technology and Data Science: Background, Current Status and Future Directions

This paper reviews the achievements of the international community towards environmentally friendly aviation operations, also referred to as Sustainable Aviation Operations in the last 25 years and the aspirations and goals to limit the impact of aviation and climate in the future. The framework for achieving global progress is provided by the International Civil Aviation Organization. NASA and FAA supported research and development to advance ATM concepts, and implemented the technology, concepts, and procedures that were responsible for creating fuel efficient flights. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. Future developments in aviation operations require new concepts, procedure, modeling, and analysis techniques. There is an increasing interest in applying methods based on Machine Learning Techniques to problems in Air Traffic Management. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and the availability of a rich historical database provide opportunities to exploit the richness of data-driven methods. The promises and challenges in applying Machine Learning Techniques to Air Traffic Management are discussed in the paper along with the testing and trustworthiness required for adoption of the techniques in operations.

Sustainable Aviation, Data Science, Machine Learni↗
NASA NTRS2022

Sustainable Aviation Operations and the Role of Information Technology and Data Science: Background, Current Status and Future Directions

This paper reviews the achievements of the international community towards environmentally friendly aviation operations, also referred to as Sustainable Aviation Operations in the last 25 years and the aspirations and goals to limit the impact of aviation and climate in the future. The framework for achieving global progress is provided by the International Civil Aviation Organization. NASA and FAA supported research and development to advance ATM concepts, and implemented the technology, concepts, and procedures that were responsible for creating fuel efficient flights. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. Future developments in aviation operations require new concepts, procedure, modeling, and analysis techniques. There is an increasing interest in applying methods based on Machine Learning Techniques to problems in Air Traffic Management. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and the availability of a rich historical database provide opportunities to exploit the richness of data-driven methods. The promises and challenges in applying Machine Learning Techniques to Air Traffic Management are discussed in the paper along with the testing and trustworthiness required for adoption of the techniques in operations.

Sustainable Aviation, Data Science, Machine Learni↗
NASA NTRS2019

Application of Machine Learning Techniques to Aviation Operations: Promises and Challenges

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. This paper reviews the current-state-of-the art in applying MLT to aviation operations, its promises and challenges. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This paper compares the methodology used in and issues to be addressed in applying either model-driven or data-driven methods. Some aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for data-driven methods. The application of MLT to aviation operations falls into three categories: (a) based on the lack of a physics-based model, MLT is the favored approach, (b) marginal difference between regression methods using physics-based models and MLT and (c) better results using a blend of physics-based methods combined with MLT. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗
NASA NTRS2020

Observations on the Application of Machine Learning Techniques to Aviation Operations

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This talk describes issues to be addressed in applying either model-driven or data-driven methods. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The issues are illustrated by a detailed example and summary of current research in the area. The application of MLT to aviation operations falls into two categories: (a) based on the lack of a physics-based model, MLT is the favored approach and (b) marginal difference between regression methods using physics-based models and MLT. Further research is needed in the selection of MLT to critical aviation operations. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗
NASA NTRS2020

Application of Machine Learning Techniques to Aviation Operations: A Case Study

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This talk describes issues to be addressed in applying either model-driven or data-driven methods. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The issues are illustrated by a detailed example and summary of current research in the area. The application of MLT to aviation operations falls into two categories 58; (a) based on the lack of a physics-based model, MLT is the favored approach and (b) marginal difference between regression methods using physics-based models and MLT. Further research is needed in the selection of MLT to critical aviation operations. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗
NASA NTRS2020

Application of Machine Learning Techniques to Aviation Operations: NASA Case Studies

There is an increasing interest in applying methods based on Machine Learning Techniques(MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This talk describes issues to be addressed in applying either model-driven or data-driven methods. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The issues relating to data, feature selection and validation of the models are illustrated by examining case studies of the application of MLT to problems in air traffic management at NASA. Further research is needed in the application of MLT to critical aviation operations. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗
NASA NTRS2016

Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?

Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations.

Sridhar, Banavar↗
NASA NTRS2006

Runway Incursion Prevention for General Aviation Operations

A Runway Incursion Prevention System (RIPS) and additional incursion detection algorithm were adapted for general aviation operations and evaluated in a simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) in the fall of 2005. RIPS has been designed to enhance surface situation awareness and provide cockpit alerts of potential runway conflicts in order to prevent runway incidents while also improving operational capability. The purpose of the study was to evaluate the airborne incursion detection algorithms and associated alerting and airport surface display concepts for general aviation operations. This paper gives an overview of the system, simulation study, and test results.

Jones, Denise R.↗
NASA NTRS2006

Runway Incursion Prevention System for General Aviation Operations

A Runway Incursion Prevention System (RIPS) and additional incursion detection algorithm were adapted for general aviation operations and evaluated in a simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) in the fall of 2005. RIPS has been designed to enhance surface situation awareness and provide cockpit alerts of potential runway conflicts in order to prevent runway incidents while also improving operational capability. The purpose of the study was to evaluate the airborne incursion detection algorithms and associated alerting and airport surface display concepts for general aviation operations. This paper gives an overview of the system, simulation study, and test results.

Jones, Denise R.↗
NASA NTRS2011

Simulator Evaluation of Runway Incursion Prevention Technology for General Aviation Operations

A Runway Incursion Prevention System (RIPS) has been designed under previous research to enhance airport surface operations situation awareness and provide cockpit alerts of potential runway conflict, during transport aircraft category operations, in order to prevent runway incidents while also improving operations capability. This study investigated an adaptation of RIPS for low-end general aviation operations using a fixed-based simulator at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC). The purpose of the study was to evaluate modified RIPS aircraft-based incursion detection algorithms and associated alerting and airport surface display concepts for low-end general aviation operations. This paper gives an overview of the system, simulation study, and test results.

Jones, Denise R.↗
NASA NTRS2012

The National Aviation Operational Monitoring Service (NAOMS): A Documentation of the Development of a Survey Methodology

The National Aviation Operational Monitoring Service (NAOMS) was a research project under NASA s Aviation Safety Program during the years from 2000 to 2005. The purpose of this project was to develop a methodology for gaining reliable information on changes over time in the rates-of-occurrence of safety-related events as a means of assessing the safety of the national airspace. The approach was a scientifically designed survey of the operators of the aviation system concerning their safety-related experiences. This report presents the results of the methodology developed and a demonstration of the NAOMS concept through a survey of nearly 20,000 randomly selected air-carrier pilots. Results give evidence that the NAOMS methodology can provide a statistically sound basis for evaluating trends of incidents that could compromise safety. The approach and results are summarized in the report and supporting documentation and complete analyses of results are presented in 14 appendices.

Connors, Mary M.↗
NASA NTRS2016

Global Simulation of Aviation Operations

The simulation and analysis of global air traffic is limited due to a lack of simulation tools and the difficulty in accessing data sources. This paper provides a global simulation of aviation operations combining flight plans and real air traffic data with historical commercial city-pair aircraft type and schedule data and global atmospheric data. The resulting capability extends the simulation and optimization functions of NASA's Future Air Traffic Management Concept Evaluation Tool (FACET) to global scale. This new capability is used to present results on the evolution of global air traffic patterns from a concentration of traffic inside US, Europe and across the Atlantic Ocean to a more diverse traffic pattern across the globe with accelerated growth in Asia, Australia, Africa and South America. The simulation analyzes seasonal variation in the long-haul wind-optimal traffic patterns in six major regions of the world and provides potential time-savings of wind-optimal routes compared with either great circle routes or current flight-plans if available.

simulation↗
NASA NTRS2012

Psychophysiological Assessment of Fatigue in Commercial Aviation Operations

The overall goal of this study is to improve our understanding of crew work hours, workload, sleep, fatigue, and performance, and the relationships between these variables on actual flight deck performance. Specifically, this study will provide objective measures of physiology and performance, which may benefit investigators in identifying fatigue levels of operators in commercial aviation and provide a way to better design strategies to limit crew fatigue. This research was supported by an agreement between NASA Ames Research Center and easyJet Airline Company, Ltd., Luton, UK. Twenty commercial pilots volunteered to participant in the study that included 15 flight duty days. Participants wore a Zephyr Bioharness ambulatory physiological monitor each flight day, which measured their heart rate, respiration rate, skin temperature, activity and posture. In addition, pilots completed sleep log diaries, self-report scales of mood, sleepiness and workload, and a Performance Vigilance Task (PVT). All data were sent to NASA researchers for processing and analyses. Heart rate variability data of several subjects were subjected to a spectral analysis to examine power in specific frequency bands. Increased power in low frequency band was associated with reports of higher subjective sleepinesss in some subjects. Analyses of other participants data are currently underway.

Hernandez, Norma↗
NASA NTRS2016

Strategic Design of Long-Haul and Oceanic Aircraft Trajectories in Aviation Operations

Long-Haul Aircraft consume most of their fuel during the cruise phase of flight. The inefficiency in cruise flights compared to efficient routes varies is around 3 to 4. The efficiency of oceanic flights is low due to limited navigational and communication equipment, congestion and airspace restrictions. The availability of Automated Dependent Surveillance-Broadcast (ADS-B) and other improvements provides opportunity for better strategic planning of trajectories. Transatlantic flights between US and Europe constitute one of the busiest oceanic airspace regions in the world. This talk examines the benefits of a wind-optimal trajectory concept with a strategic de-confliction component compared to the current flight planning using the North Atlantic Tracks. The analysis is based on air traffic between US and Europe during July 2012. The potential fuel savings are in the range of (420-970) kg per flight for a Boeing 767-300, the most widely used aircraft between the city-pairs in this study. The talk also describes a global simulation of aviation operations combining flight plans and real air traffic data with historical commercial city-pair aircraft type and schedule data and global atmospheric data. The resulting capability extends the simulation and optimization functions of NASAs Future Air Traffic Management Concept Evaluation Tool (FACET) to global scale. This new capability is used to characterize the evolution of global air traffic, analyze fuel savings and seasonal variations in the long-haul wind-optimal traffic patterns in six major regions of the world.

strategic trajectory design↗
NASA NTRS1988

Human error in aviation operations

The role of human error in commercial and general aviation accidents and the techniques used to evaluate it are reviewed from a human-factors perspective. Topics addressed include the general decline in accidents per million departures since the 1960s, the increase in the proportion of accidents due to human error, methods for studying error, theoretical error models, and the design of error-resistant systems. Consideration is given to information acquisition and processing errors, visually guided flight, disorientation, instrument-assisted guidance, communication errors, decision errors, debiasing, and action errors.

Nagel, David C.↗
NASA NTRS2017

Hyper-Spectral Communications, Networking and ATM as Foundation for Safe and Efficient Future Flight: Transcending Aviation Operational Limitations with Diverse and Secure Multi-Band, Multi-Mode, and mmWave Wireless Links: Project Overview, Aviation Communications and New Signaling

NASA's Aeronautics Research Mission Directorate (ARMD) has recently solicited proposals and awarded funds for research and development to achieve and exceed the goals envisioned in the ARMD Strategic Implementation Plan (SIP). The Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is the only University Leadership Initiative (ULI) program to address communications and networking (and to a degree, navigation and surveillance). This paper will provide an overview of the HSCNA project, and specifically describe two of the project's technical challenges: comprehensive aviation communications and networking assessment, and proposed multi-band and multimode communications and networking. The primary goals will be described, as will be research and development aimed to achieve and exceed these goals. Some example initial results are also provided.

aeronautics↗
NASA NTRSDate not supplied

Impact of General Aviation Operations on Airport Performance Through Fast-Time Simulations at Charlotte Douglas International Airport

NASA, in partnership with the Federal Aviation Administration and commercial airlines, deployed the Integrated Arrival, Departure, and Surface (IADS) traffic management system at Charlotte Douglas International Airport (CLT) in 2017 for field evaluation. The system features new capabilities of data exchange and integration, collaborative surface metering and scheduling, which has demonstrated operational benefits of reducing delay time and fuel consumption. General Aviation flights, however, are not currently included in the surface metering programs because of their different operational procedures and lack of reliable predictability in departure time. Thus, their impact on the system performance is not well understood. This paper presents a study of the impact of General Aviation traffic at CLT using fast-time simulations.

General Aviation↗