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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Overview of an Exploratory, Real-Time, Multi-Pilot Simulation Study of Early eVTOL Operations at Non-Towered Vertiports

This paper provides a report out on an exploratory, multi-aircraft/multi-pilot, real-time simulation study conducted by NASA of early commercial powered-lift, Urban Air Mobility (UAM) operations at a non-towered vertiport. As used in this paper, vertiport refers to the primary ground and airspace elements facilitating the takeoff and landing of electric vertical takeoff and landing (eVTOL) aircraft with central emphasis on a vertipad, i.e. the physical touch-down and lift-off area and surrounding approach , departure, local pattern procedures. The study, known as the Piloted UML-2 ConOps Study (PUCS), had two high-level goals. The first goal was providing preliminary insights and observations relevant to the piloting and flight operations of early, commercial UAM operations aligned with the initial stage of the FAA’s Advanced Air Mobility (AAM) Implementation Plan and the second level NASA’s UAM Maturity Level (UML) scale. The second goal was evaluating a novel, medium-fidelity, extensible, many-pilot, real-time simulation capability known as the UAM Flyers developed by NASA. The Flyers are intended to allow rapid development, screening, evaluation, and demonstrations of potential Concepts of Operation (ConOps) for UAM flight operations and airspace management in a modular and low-cost, real-time, human-in-the-loop rapid simulation prototyping environment. For this study, ten Flyer cockpits were configured to evaluate flight operations through a non-towered vertiport with pilot interfaces and displays (external and in-cockpit) appropriate for operations under visual flight rules (VFR) and employing flight and communication procedures representative of current operations at non-towered airports. The presented results include an achieved operational tempo; durations of individual flight tasks for approaches and departures; off-nominal events and triggers; and pilot comments regarding potential procedural and technology improvements.

Urban Air Mobility↗
NASA NTRSDate not supplied

Ice Shape Analysis of an eVTOL Propeller in Forward Flight at the NASA Glenn Icing Research Tunnel

Advanced Air Mobility (AAM) introduces many novel electric vertical takeoff and landing (eVTOL) aircraft configurations for which the effect of icing is not well understood. While icing computational tools have often aided in the design and certification of conventional aircraft, experimental data is needed to support the development and validation of such tools for eVTOL applications. To investigate the icing phenomenon relevant to eVTOL aircraft, NASA Glenn Research Center developed a general-purpose propeller test stand for conducting fundamental icing research on electrically driven propellers in the Icing Research Tunnel (IRT). A 10-day test entry in the IRT was completed in March, 2023, with the goal of generating ice accretions on a non-proprietary propeller geometry under well-characterized conditions. Three carbon fiber propellers of diameters 0.610, 0.711, and 0.914 m (24, 28, and 36 in) were used during the test. Various parametric sweeps of cloud and operating conditions were performed to evaluate the sensitivity of the parameters on the resulting ice accretion characteristics such as ice thickness, mass, location (impingement limits), and type (glaze vs rime). Ice shapes were reviewed for their repeatability, correctness of trends, and sensitivity to parameter variations. The data from the test is being used to support the development of the ice accretion solver, GlennICE.

Icing↗
NASA NTRSDate not supplied

HIRF Tolerance and Avoidance for Advanced Air Mobility Vehicles

Advanced Air Mobility (AAM), including Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles may fly in similar airspace to Transport Category Rotorcraft, thereby requiring meeting the same stringent High-Intensity Radiated Fields (HIRF) certification requirements. In a previous effort, a proposed map-based approach protects a vehicle by keeping it away from high power sources at safe distances based on its tolerance level. By designing to a lower tolerance level, significant cost savings can be achieved at the cost of slightly more complex flight planning. However, too low a threshold can result in large avoidance areas, potentially reducing the vehicle operating space. This current effort suggests a minimum threshold for vehicles operating in an urban area. It is derived from analyzing regulatory transmitter data for New York City as a representative metropolitan. As a result, a vehicle can tolerate common lower-power transmitters by default and only needs to avoid far less common high-power sources. It is also found the existing HIRF requirements may be insufficient against many powerful transmitters such as weather radars and satellite uplink transmitters, and that the map-based approach can address this concern.

HIRF↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗
NASA NTRSDate not supplied

Urban Air Mobility Traffic Analysis Tool for Airspace Involving Vertiport Hub Operations to Examine Simulated Conflicts

Presented herein are details of the development of an Urban Air Mobility Traffic Analysis Tool (UAM TAT), designed to analyze the traffic of Vertical Take-off and Landing (VTOL) air-craft in urban agglomerations to enable the Urban Air Mobility(UAM) operations. The tool aims to address challenges of UAM operations in a simulated airspace by testing different scenarios and methods for air traffic management. It emphasizes the need for effective risk management practices and methodologies to ensure the safety of operations, given the increasing use of highly automated aircraft (i.e., Advanced Air Mobility (AAM))in urban environments. The tool is modular and allows for the simulation of various families of VTOLs and different air traffic rules, making it suitable for defining and estimating airspace and vertiports capacity, determining VTOL requirements, and testing and comparing air traffic management methods. The results of five different simulations are presented that show the capabilities and functionalities of the tool. The simulations present the impact of vertiport hub operations and various ATM approach on the VTOLs’ conflicts.

Urban Air Mobility↗
NASA NTRSDate not supplied

Wake Disturbance-Based Separation Evaluation for Urban Air Mobility Aircraft

This paper builds upon previous research to evaluate Urban Air Mobility (UAM) flight dynamics in the presence of wake disturbances. A model for fixed-wing-generated wake effects is applied to a Revolutionary Vertical Lift Technology (RVLT) Lift+Cruise UAM trail aircraft operating in the fixed-wing Cruise configuration. The wake effects are evaluated at various longitudinal and latitudinal separation configurations to determine the most hazardous wake encounter situation. Trim calculations and closed-loop simulations show a trailing aircraft flying directly into a wake vortex as the most hazardous scenario. Furthermore, trailing behind a larger aircraft at similar speeds greatly increases the safe separation distance. These considerations indicate a need for dynamic pairwise separation criteria to enable dense Advanced Air Mobility (AAM) operations while maintaining safety.

Urban Air Mobility↗
NASA NTRSDate not supplied

Identifying Human Factors Research for Unmanned Aircraft Systems and Advanced Air Mobility

This paper identifies some of the key human factors (HF) challenges when integrating Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) into the civil airspace. Unique HF considerations—those which are derived from the key differentiating aspects of UAS/AAM compared to conventional aviation—are the primary basis for identifying HF research opportunities. By identifying what makes UAS and AAM fundamentally different from conventional aviation, from a human integration perspective, HF research can be targeted to effectively inform best practices, standards, policy, guidance, and regulations associated with aircraft and air traffic systems and operations. HF research areas are discussed within the following topic areas: Sustained low-altitude operations; loss of natural sensing; novel aircraft; novel operations; link management and lost link; link performance; distributed pilot teams; and increased automation. The identified research descriptions are intended to serve as illustrative examples of what research is fundamental, and why. They are not intended to prescribe, prioritize or exclude research.

AAM↗
NASA NTRSDate not supplied

Overview of an Exploratory, Multi-Pilot Simulation Study of Early eVTOL Operations at Non-Towered Vertiports

This paper provides a report out on an exploratory, multi-aircraft/multi-pilot, real-time simulation study conducted by NASA of early commercial powered-lift, Urban Air Mobility (UAM) operations at a non-towered vertiport. As used in this paper, vertiport refers to the primary ground and airspace elements facilitating the takeoff and landing of electric vertical takeoff and landing (eVTOL) aircraft with central emphasis on a vertipad, i.e. the physical touch-down and lift-off area and surrounding approach , departure, local pattern procedures. The study, known as the Piloted UML-2 ConOps Study (PUCS), had two high-level goals. The first goal was providing preliminary insights and observations relevant to the piloting and flight operations of early, commercial UAM operations aligned with the initial stage of the FAA’s Advanced Air Mobility (AAM) Implementation Plan and the second level NASA’s UAM Maturity Level (UML) scale. The second goal was evaluating a novel, medium-fidelity, extensible, many-pilot, real-time simulation capability known as the UAM Flyers developed by NASA. The Flyers are intended to allow rapid development, screening, evaluation, and demonstrations of potential Concepts of Operation (ConOps) for UAM flight operations and airspace management in a modular and low-cost, real-time, human-in-the-loop rapid simulation prototyping environment. For this study, ten Flyer cockpits were configured to evaluate flight operations through a non-towered vertiport with pilot interfaces and displays (external and in-cockpit) appropriate for operations under visual flight rules (VFR) and employing flight and communication procedures representative of current operations at non-towered airports. The presented results include an achieved operational tempo; durations of individual flight tasks for approaches and departures; off-nominal events and triggers; and pilot comments regarding potential procedural and technology improvements.

Urban Air Mobility↗
NASA NTRS2024

Ice Shape Analysis of an eVTOL Propeller in Forward Flight at the NASA Glenn Icing Research Tunnel

Advanced Air Mobility (AAM) introduces many novel electric vertical takeoff and landing (eVTOL) aircraft configurations for which the effect of icing is not well understood. While icing computational tools have often aided in the design and certification of conventional aircraft, experimental data is needed to support the development and validation of such tools for eVTOL applications. To investigate the icing phenomenon relevant to eVTOL aircraft, NASA Glenn Research Center developed a general-purpose propeller test stand for conducting fundamental icing research on electrically driven propellers in the Icing Research Tunnel (IRT). A 10-day test entry in the IRT was completed in March, 2023, with the goal of generating ice accretions on a non-proprietary propeller geometry under well-characterized conditions. Three carbon fiber propellers of diameters 0.610, 0.711, and 0.914 m (24, 28, and 36 in) were used during the test. Various parametric sweeps of cloud and operating conditions were performed to evaluate the sensitivity of the parameters on the resulting ice accretion characteristics such as ice thickness, mass, location (impingement limits), and type (glaze vs rime). Ice shapes were reviewed for their repeatability, correctness of trends, and sensitivity to parameter variations. The data from the test is being used to support the development of the ice accretion solver, GlennICE.

Icing↗
NASA NTRSDate not supplied

HIRF Avoidance Approach for Advanced Air Mobility Vehicles

Advanced Air Mobility (AAM), including Urban Air Mobility (UAM), vehicles may be required to meet stringent High-Intensity Radiated Fields (HIRF) certification requirements. HIRF can cause interference and even damage to vehicle systems. A recently proposed map-based HIRF avoidance approach can help reduce HIRF protection costs compared to the standard approach. However, it necessitates knowing the locations, frequencies, and transmit powers of high-power antennas within the operating area. This study aims to provide the necessary transmitter data by utilizing regulatory license databases. Using New York City as a representative urban area, fixed transmitter data are presented for AM, FM, TV, satellite uplink, land-mobile radio, microwave link, weather radars, and others. The maximum antenna effective isotropic radiated powers are reported. The associated electric field envelopes at 100 feet (30.48 m) distance are compared against the current rotorcraft HIRF standard. The results show the current standards are far adequate in protecting the vehicles. Maps of regions with high HIRF are illustrated. Data for several other cities are also being considered.

HIRF↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learning↗
NASA NTRSDate not supplied

HIRF Tolerance and Avoidance for Advanced Air Mobility Vehicles

Advanced Air Mobility (AAM), including Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles may fly in similar airspace to Transport Category Rotorcraft, thereby requiring meeting the same stringent High-Intensity Radiated Fields (HIRF) certification requirements. In a previous effort, a proposed map-based approach protects a vehicle by keeping it away from high power sources at safe distances based on its tolerance level. By designing to a lower tolerance level, significant cost savings can be achieved at the cost of slightly more complex flight planning. However, too low a threshold can result in large avoidance areas, potentially reducing the vehicle operating space. This current effort suggests a minimum threshold for vehicles operating in an urban area. It is derived from analyzing regulatory transmitter data for New York City as a representative metropolitan area. As a result, a vehicle can tolerate common lower-power transmitters by default and only needs to avoid far less common high-power sources. It is also found the existing HIRF requirements may be insufficient against many powerful transmitters such as weather radars and satellite uplink transmitters, and that the map-based approach can address this concern.

HIRF↗
NASA NTRSDate not supplied

Assessing High-Intensity Radiated Fields (HIRF) from High-Power Antennas for Air Vehicle Safety

Advanced Air Mobility (AAM), including Urban Air Mobility (UAM), vehicles may be required to meet stringent High-Intensity Radiated Fields (HIRF) certification requirements. HIRF can cause interference and even damage to vehicle systems. A recently proposed map-based avoidance approach can help reduce HIRF protection costs compared to the standard approach. However, it necessitates knowing the locations, frequencies, and transmit powers of high-power antennas within the operating area. This study aims to provide the necessary transmitter data by utilizing regulatory license databases. Using New York City as a representative urban area, fixed transmitter data are presented for AM, FM, TV, satellite uplink, land-mobile radio, microwave link, weather radars, and others. The maximum effective isotropic radiated powers of the antenna are reported. The associated electric field envelopes at 100 feet (30.48 m) distance are compared against the current rotorcraft HIRF standard. The results show that the current standards for protecting vehicles are inadequate. Maps of regions with high HIRF are illustrated. Data for several other cities are also being considered.

HIRF↗
NASA NTRS2024

Federal USS Synthesis Effort: 2023 Flight Test Report. A NASA and Department of Defense Joint Evaluation of Multi-Domain Airspace Integration

In recent years, advancements in technology have greatly improved the utility and applicability of Uncrewed Aircraft Systems (UAS) and have highlighted the need for and importance of UAS Traffic Management (UTM). Onboard sense and avoid systems, ground-based sensors, and long- range command and control (C2) systems have significantly expanded the possibilities for UAS beyond visual line of sight (BVLOS) operations. Initially, research on UTM flights focused on their interactions with other UTM operations, but that has since been expanded to include interactions with the flight profiles of Advanced Air Mobility (AAM) and upper Class E Traffic Management (ETM) operations. Recognizing the potential of these systems and the increase in UAS autonomy, the Department of Defense (DoD) is working towards integrating these missions and systems into a unified DoD Federal ecosystem. The Federal USS Synthesis Effort (FUSE) aims to develop a live system that can efficiently combine this wide range of UTM, AAM, and ETM systems, thus enabling expanded operations within a single common operating environment. The goal of the Federal USS Synthesis Effort (FUSE) is for NASA and the DoD to develop a live system that can efficiently combine UTM, AAM, and ETM systems. The most recent endeavor in this effort was a live flight test conducted near Grand Forks Air Force Base in June, 2023, where the FUSE ecosystem successfully demonstrated integrating UTM, AAM, and ETM operations while providing a single, shared COP to users. Additional investigations were made during the test, including assessing the usefulness of the system and its capability to support UAS weighing over 55 lbs.; testing user messaging capabilities and a DoD adaptation of a Federal USS; and assessing user workload, automated vs manual control, and the usability of NASA’s XTMClient.

Federal USS↗
NASA NTRS2024

Assessing High-Intensity Radiated Fields (HIRF) from High-Power Antennas for Air Vehicle Safety

Advanced Air Mobility (AAM), including Urban Air Mobility (UAM), vehicles may be required to meet stringent High-Intensity Radiated Fields (HIRF) certification requirements. HIRF can cause interference and even damage to vehicle systems. A recently proposed map-based avoidance approach can help reduce HIRF protection costs compared to the standard approach. However, it necessitates knowing the locations, frequencies, and transmit powers of high-power antennas within the operating area. This study aims to provide the necessary transmitter data by utilizing regulatory license databases. Using New York City as a representative urban area, fixed transmitter data are presented for AM, FM, TV, satellite uplink, land-mobile radio, microwave link, weather radars, and others. The maximum effective isotropic radiated powers of the antenna are reported. The associated electric field envelopes at 100 feet (30.48 m) distance are compared against the current rotorcraft HIRF standard. The results show that the current standards for protecting vehicles are inadequate. Maps of regions with high HIRF are illustrated. Data for several other cities are also being considered.

HIRF↗
NASA NTRSDate not supplied

An in-Time Aviation Safety Management System Concept of Operations and Modernization of the National Airspace System

The National Airspace System (NAS) is growing in complexity of aircraft, missions, and operations. In response, many organizations have published papers and concepts of operations (ConOps) for new and enhanced safety systems. The National Academies’ vision for an In-time Aviation Safety Management System (IASMS) is integral to Federal Aviation Administration (FAA) modernization efforts. The National Aeronautics and Space Administration (NASA) System-Wide Safety (SWS) project is conducting safety research, exploring solutions, and defining the safety needs of future missions, such as Advanced Air Mobility (AAM) and autonomous aircraft operating in a more connected, flexible, and dynamic airspace. IASMS enables and provides a path for bringing FAA’s operational vision to fruition through increasingly automated safety systems that integrate services, functions, and capabilities (SFCs). These SFCs provide the necessary responsiveness to monitor, assess, and mitigate known hazards and emergent risks. This paper describes how safety in today’s air transportation system will need to evolve, identifies key points regarding in-time safety, and explores the criticality of IASMS in the future NAS.

IASMS↗
NASA NTRSDate not supplied

Vision-Based Distributed Sensing at Vertiports for Advanced Air Mobility and Urban Air Mobility Approach and Landing

Advanced Air Mobility (AAM) encompasses a broad vision for air transportation, including Urban Air Mobility (UAM) as a subset. AAM aims to create a more connected and efficient transportation network across various geographical settings. However, navigating AAM aircraft in GPS-denied or degraded environments during approach and landing is challenging. Traditional vision aids like glideslopes and localizers are limited in vertiport environments due to narrow beam constraints and reduced landing angle options. This paper addresses the need for accurate navigation solutions at vertiports by proposing a vision-based distributed sensing (VIDIS) system utilizing cameras with bundle adjustment to assist incoming AAM aircraft during approach and landing while monitoring surface movements to enhance safety and efficiency. Key focus areas for current and future vertiport developers include identifying suitable sensor types and infrastructure standards to support AAM operations and including vertiport markings as vision-based navigation aids. The proposed system offers a novel approach to overcoming navigation challenges in AAM operations, particularly in urban settings where traditional aids may be insufficient. Preliminary simulation results with distributed cameras demonstrate promising outcomes for implementing bundle adjustment techniques to enhance vision-based navigation solutions at vertiports. Generating waypoint-based trajectories via waypoint integration using explicit guidance synthesis (WINGS) creates smooth AAM trajectories for landing at vertiports by using the current waypoint's terminal conditions as the initial conditions for the next waypoint. Combining bundle adjustment's ground-based solution of vertiport features with WINGS, Coplanar Pose from Orthography and Scaling with Iterations (COPOSIT), and an extended Kalman filter (EKF) estimates the state of an incoming aircraft during approach and landing at vertiports. Future work includes testing VIDIS in a high-fidelity simulation and with real-world data.

Distributed sensing↗
NASA NTRSDate not supplied

Vision-Based Distributed Sensing at Vertiports for Advanced Air Mobility and Urban Air Mobility Approach and Landing

Advanced Air Mobility (AAM) encompasses a broad vision for air transportation, including Urban Air Mobility (UAM) as a subset. AAM aims to create a more connected and efficient transportation network across various geographical settings. However, navigating AAM aircraft in GPS-denied or degraded environments during approach and landing is challenging. Traditional vision aids like glideslopes and localizers are limited in vertiport environments due to narrow beam constraints and reduced landing angle options. This paper addresses the need for accurate navigation solutions at vertiports by proposing a vision-based distributed sensing (VIDIS) system utilizing cameras with bundle adjustment to assist incoming AAM aircraft during approach and landing while monitoring surface movements to enhance safety and efficiency. Key focus areas for current and future vertiport developers include identifying suitable sensor types and infrastructure standards to support AAM operations and including vertiport markings as vision-based navigation aids. The proposed system offers a novel approach to overcoming navigation challenges in AAM operations, particularly in urban settings where traditional aids may be insufficient. Preliminary simulation results with distributed cameras demonstrate promising outcomes for implementing bundle adjustment techniques to enhance vision-based navigation solutions at vertiports. Generating waypoint-based trajectories via waypoint integration using explicit guidance synthesis (WINGS) creates smooth AAM trajectories for landing at vertiports by using the current waypoint's terminal conditions as the initial conditions for the next waypoint. Combining bundle adjustment's ground-based solution of vertiport features with WINGS, Coplanar Pose from Orthography and Scaling with Iterations (COPOSIT), and an extended Kalman filter (EKF) estimates the state of an incoming aircraft during approach and landing at vertiports. Future work includes testing VIDIS in a high-fidelity simulation and with real-world data.

Distributed sensing↗