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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Community Noise Impact of Urban Air Mobility Vehicle Operations

Advanced air mobility (AAM) missions, carried out by electrically driven air vehicles, are characterized by ranges of less than about 300-500 nm (about 500-900 km) and include both rural and urban operations. The missions may include public transportation, cargo delivery, air taxi, and emergency response. While the urban air mobility (UAM) subset of AAM is projected to have high economic benefit, it is also the most difficult to develop because it must overcome many barriers, including those associated with the airspace system, safety, and community noise. This presentation focuses on the utilization of UAM source noise data for assessment of community noise impact. Although a limited number of acoustic flight measurement campaigns have been made to characterize the source noise of prototype and preproduction UAM aircraft, prediction-based approaches are primarily considered herein. Following conceptual design, in which the vehicle is appropriately sized for its intended mission, a comprehensive analysis must be performed for a range of operating conditions spanning the flight envelope to determine the corresponding configurations of the vehicle, that is, the trimmed states. For each trimmed state, the noise produced by each source, for example, steady and unsteady rotor noise, may be computed and so-called source noise (hemi)spheres generated. These source data may subsequently be used in various community noise impact analyses. Several use cases are presented including those supporting noise certification and those for auralizations that may, in turn, be used as part of a perception-influenced design process. Land use planning tools for generating noise exposure maps, including those using simulation and integrated modeling approaches, are also presented. Finally, use cases supporting development of low noise flight operations, including an acoustic flight simulator and acoustically aware flight control, are considered.

aircraft community noise↗
NASA NTRS2023

The Viability of See-and-Avoid for Urban Air Mobility Operations

Urban Air Mobility (UAM) is an emerging aviation concept that could supplement today’s ground and air transportation systems. For UAM, it is generally assumed that the private sector will manage separation and not rely on the Federal Aviation Administration air traffic control system. To date, discussions of initial operations focus on using the visual abilities of the pilot to “see and avoid” (SAA) other aircraft. Decades of research on SAA has demonstrated that it is inadequate for reliable detection of aircraft that might pose a collision risk. The literature on multi-object tracking is also reviewed for findings on how well humans can visually track objects. The research shows that humans have limited resources for tracking and that this may be affected by object characteristics and cognitive skills. The conclusion is that SAA is a risky method for avoiding midair collisions. It is recommended that flight deck displays and automated collision avoidance systems be implemented for all UAM aircraft at the outset of their introduction.

urban air mobility↗
NASA NTRSDate not supplied

A Psychoacoustic Test on the Effect of Masking on Annoyance to Urban Air Mobility Vehicle Noise

Urban Air Mobility (UAM) vehicles have a large range of designs and configurations that lead to new noise characteristics and potentially different perceptual responses when compared to traditional aircraft. In addition, UAM vehicles are expected to operate around and within densely populated regions where the presence of ambient background noise is often present. Strategically, this can be leveraged to inform vehicle design and operations to partially or completely mask UAM noise, allowing for mitigation of negative responses and an increased number of allowed operations. A psychoacoustic test was conducted to investigate how masking effects can influence the annoyance response to a low frequency harmonic tone complex (80-320 Hz). To do this, five test subjects compared their annoyance response to the low frequency tonal noise with a higher frequency broadband noise (10dB down bandwidth between 300-2000 Hz), with and without a masking noise present. Detection thresholds were also measured for both sounds to help fit a model to the data. Although the effect of masking on annoyance is complex, results indicate that for some individuals, masking leads to a lower annoyance than the sound level alone would predict.

Matthew Boucher↗
NASA NTRS2024

Presound: UAV Diagnostic System Enabled by Vibration-Based Machine Learning

A low-weight, inexpensive small unmanned aerial system (sUAS) that takes off, performs a mission, lands, and safely stows and recharges itself has myriad future applications ranging from agricultural imaging to last-mile package delivery. Likewise, Urban Air Mobility (UAM) systems will enable people to take air taxis from point to point in cities, rapidly moving commuters long distances without concern for road traffic and congestion. Fully electric aviation systems will be cleaner and quieter than ground transport. Cities could eliminate cars and buses, and convert roads to higher capacity bike and pedestrian throughways. Yet, for sUAS as well as UAM, system reliability and assurance is a limiting factor to deploying affordable autonomous flight systems. For this bright future of aviation to be realized, aircraft must be able to autonomously and accurately self-diagnose health issues both before takeoff and during flight. The GreenSight PreSound system is designed to identify defects on aircraft through intelligent analysis of vibration. It accomplishes this by measuring structural vibrations induced by the vehicle’s own propellers, and analyzing that data using a machine learning model that determines whether a defect is present. The PreSound system is designed to require no human oversight, and to operate across a wide array of vehicles through re-training of the model for each target aircraft. PreSound has been developed and seen limited early success using data collected from the GreenSight Dreamer sUAS, a 5lb quadrotor vehicle designed for aerial imaging applications. The final detection model, trained on data with props spinning at 50% throttle, achieves excellent performance with over 99% average accuracy in detecting blade damage using a single FFT vector input. It demonstrates the ability to generalize to new types of blade damage, correctly classifying a different type of blade damage with 98% accuracy. Full test pulses were classified with 100% accuracy, and in live testing, all sets of data during blade movement were classified accurately with over 95% confidence. When trained on in-flight data, the same model achieves an average accuracy of 85% in distinguishing between undamaged and blade-damaged states in flight. The authors believe that these accuracies show significant potential of this approach to expand unmanned flight safety, with significant potential benefits in accelerating Advanced Aerial Mobility (AAM) and UAM aviation applications.

UAS↗
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

m:N Operations High Complexity Simulation

The Human Autonomy Teaming Laboratory at NASA Ames Research Center (ARC) is planning to conduct an experiment investigating system-level effects operational vertiport disruptions on Urban Air Mobility (UAM) traffic in a simulated vertiport network in Denver, CO. The simulation will involve two parties, one at NASA ARC and another at NASA Langley Research Center (LaRC), each playing the role of a UAM Operator. This study, referred to as the "High Complexity Sim," features a 3-by-2-by-2 mixed subjects design. The variables to be manipulated are the scale of the disruption (Disruption, three levels: Small, Medium, and Large, affecting 1, 2, and 3+, vertiports, respectively), m:N ratio (Ratio, two levels: 2:6 and 2:12), and the assumption of UAM corridors (Corridors, two levels: With and Without). Local and system-wide capacity (i.e., throughput), efficiency (scale and number of flight delays, filed-vs-flown flight times), and human performance metrics (workload, situation awareness, heart rate/heart rate variability, eye gaze/fixation and saccades, stress) will be measured. This presentation details the experimental design and planned timeline for the study.

multi-vehicle↗
NASA NTRS2019

Concept of Operations for Urban Air Mobility Command and Control Communications

Urban Air Mobility (UAM) is a burgeoning flight services concept for passenger and cargo airborne applications operating within and around urban environments. Among the services envisioned, most attention is being directed at airborne personal transport to improve transit time and mitigate automobile congestion. In addition, delivery services for more efficient transport of goods and local area information gathering for timely media dissemination and emergency monitoring will also likely be early UAM system applications. Among the infrastructure components in need of development are communications systems that manage these air vehicles. Not only will there be a need to communicate with the pilots in command of the aircraft for traffic management, but the control of the aircraft and monitoring of the aircraft systems will also need to use these communications systems to ensure safe operations.

Urban Air Mobility (UAM)↗
NASA NTRSDate not supplied

ATM-X and Urban Air Mobility Overview

These slides are material for the Initial Urban Air Mobility (UAM) sub-project to provide an overview of Air Traffic Management eXploration (ATM-X) project and UAM to external collaborators.

Air Traffic Management –eXploration↗
NASA NTRSDate not supplied

Urban Air Mobility National Campaign Test Series

The Urban Air Mobility (UAM) National Campaign test series is designed to promote public confidence in UAM safety, facilitate community-wide learning while capturing the public’s imagination, and give prospective vehicle manufacturers and operators, and prospective airspace service providers, insights into the evolving regulatory and operational environment. The National Campaign is also intended to support requirements and system development for Urban Air Mobility through integrated demonstrations of candidate vehicles and airspace in operational scenarios critical to scalable commercialization. The NASA National Campaign series will facilitate bringing together vehicle and airspace service providers to demonstrate industry’s concept and technology maturity levels with respect to vehicle performance, safety assurance, and airspace interoperability solutions for civil use.

Urban Air Mobility↗
NASA NTRSDate not supplied

A Survey of Cyber Threat

Multiple companies are competing to develop human-crewed and unmanned aerial vehicles to provide flight in urban environments. With the growth of aerial systems and future airborne vehicle networks and the need to enable secure data exchange and service interactions within Urban Air Mobility (UAM) environments, cybersecurity has come to the forefront as a topic, highlighting the need to protect these networks from cyber-attacks. This paper will identify potential threats, vulnerabilities, and weaknesses of UAM environments, that could lead to system compromises and disruptions.

Cyber Security↗
NASA NTRSDate not supplied

A Survey of Cyber Threats and Security Controls Analysis for Urban Air Mobility Environments

Since the cyber threat landscape changes daily, cybersecurity needs to be an ongoing activity for every organization within the UAM environments. This paper will provide information on identified cyber threats and controls associated with an instance of the Urban Air Mobility (UAM) environment. The MITRE ATT&CK model and framework and the selection of cyber threats and the National Institute of Standards and Technology publications for security control identification and cybersecurity risk identification will be leveraged for analysis.

Cyber Threats↗
NASA NTRSDate not supplied

Cyber Threats and Security Controls Analysis for Urban Air Mobility Environments

Since the cyber threat landscape changes daily, cybersecurity needs to be an ongoing activity for every organization within the UAM environments. This paper will provide information on identified cyber threats and controls associated with an instance of the Urban Air Mobility (UAM) environment. The MITRE ATT&CK model and framework and the selection of cyber threats and the National Institute of Standards and Technology publications for security control identification and cybersecurity risk identification will be leveraged for analysis.

Urban Air Mobility↗
NASA NTRSDate not supplied

Cyber Threats & Security Controls Analysis for Urban Air Mobility Environments

Since the cyber threat landscape changes daily, cybersecurity needs to be an ongoing activity for every organization within the UAM environments. This paper will provide information on identified cyber threats and controls associated with an instance of the Urban Air Mobility (UAM) environment. The MITRE ATT&CK model and framework and the selection of cyber threats and the National Institute of Standards and Technology publications for security control identification and cybersecurity risk identification will be leveraged for analysis.

Cyber Threats↗
NASA NTRSDate not supplied

Systems Health Monitoring: Integrating FMEA into Bayesian Networks

The foreseeable high traffic density suggests that a large number of electric propulsion systems will enter the airspace, and that they will also operate at high frequency, e.g., large number of take offs and landings per unit time. The reliability of such critical systems is therefore key to ensure high safety standards in the low-altitude airspace. Diagnostic systems, which aim at identifying incipient faults, can mitigate unexpected failures or lower-than-expected reliability by performing early fault detection by monitoring the systems. A key element of fault diagnosis is fault detection and isolation (FDI), which complexity increases with the complexity of the system itself, namely the number of subsystems and components, interactions among sub-systems, and the number of sensors available. The proposed approach leverages combination of failure mode and effect analysis (FMEA) integrated with Bayesian networks, thus introducing dependability structures into a diagnostic framework to aid FDI. Faults and failure events from the FMEA are mapped within a Bayesian network, where network edges replicate the links embedded within FMEAs. The integrated framework enables the fault isolation process by identifying the probability of occurrence of specific faults or root causes given evidence observed through sensor signals. In this work, sub systems of Urban Air Mobility (UAM) type vehicle like avionics, structures, power-train etc. are taken into account to show the approach at the system level. This work integrates early design phase in the development of UAM type vehicles with diagnostic tools, which are often developed later in the product life-cycle, or retrofitted at a later time on systems. Failure mode and effect analysis (FMEA) derived for the system in the design phase is embedded within a Bayesian network (BN).

UAM↗
NASA NTRS2021

High-Density Automated Vertiport Concept of Operations

The National Aeronautics and Space Administration (NASA) vision for Advanced Air Mobility (AAM) includes Urban Air Mobility (UAM) – a concept involving vertical takeoff and landing (VTOL) aircraft, decentralized (or federated) traffic management, and new infrastructure to support urban, suburban, and rural flight operations. High-density performance-based routes or corridors enable prompt transportation of people and goods from node to node, where each node represents a vertiport, defined as an identifiable ground or elevated area used for the takeoff and landing of VTOL aircraft. In the presence of uncertainty surrounding aircraft turnaround time on the ground, vertiports are the critical end points in scheduling, sequencing, and spacing (SSS) of aircraft in dense metropolitan environments. This Concept of Operations (ConOps) includes vertiports of varying sizes, configurations, service offerings, and locations. UAM air vehicles include conventional rotorcraft, unmanned VTOL aircraft, and novel piloted VTOL aircraft. This ConOps focuses on operations at a high-density vertiport, supported by a Vertiport Automation System (VAS) with high-throughput operation capabilities under conditions defined as NASA’s Urban Air Mobility Maturity Level Four (UML-4).

UAM↗
NASA NTRS2021

High-Density Automated Vertiport Concept of Operations

The National Aeronautics and Space Administration (NASA) vision for Advanced Air Mobility (AAM) includes Urban Air Mobility (UAM) – a concept involving vertical takeoff and landing (VTOL) aircraft, decentralized (or federated) traffic management, and new infrastructure to support urban, suburban, and rural flight operations. High-density performance-based routes or corridors enable prompt transportation of people and goods from node to node, where each node represents a vertiport, defined as an identifiable ground or elevated area used for the takeoff and landing of VTOL aircraft. In the presence of uncertainty surrounding aircraft turnaround time on the ground, vertiports are the critical end points in scheduling, sequencing, and spacing (SSS) of aircraft in dense metropolitan environments. This Concept of Operations (ConOps) includes vertiports of varying sizes, configurations, service offerings, and locations. UAM air vehicles include conventional rotorcraft, unmanned VTOL aircraft, and novel piloted VTOL aircraft. This ConOps focuses on operations at a high-density vertiport, supported by a Vertiport Automation System (VAS) with high-throughput operation capabilities under conditions defined as NASA’s Urban Air Mobility Maturity Level Four (UML-4).

Urban Air Mobility↗
NASA NTRSDate not supplied

Zero Trust and Identity Access Management in Support of Service-Based Urban Air Mobility Applications

Urban Air Mobility environments will contain of a collection of service-based services, which will be typically hosted within cloud infrastructures. The underlying data for these UAM services will need to be secured. One approach to securing these UAM services would be to leverage the Zero Trust framework, that focuses on securing services and associated data, instead of securing the network. An early step in moving towards a Zero Trust framework is to standardize identity access manage support for an ever-widening set of services, where users must explicitly be granted access to each service.

UAM↗
NASA NTRSDate not supplied

Operational Analysis to Evaluate Practical Potential of Vertical Vertiplex for Urban Air Mobility

Urban Air Mobility (UAM) is intended to serve as an alternative mode of transportation to relieve congestions in and out of urban areas. Therefore, a high density vertiplex (HDV) with multiple touchdowns and liftoff (TLOF) zone is necessary to alleviate the demands. To increase the operational efficiency of the vertiplex, EVTOL aircraft are distributed to parking spaces to utilize the TLOF zone for another approach and departure procedure. The surface footprint of the infrastructure increases drastically due to the horizontal arrangement of taxiways and parking spaces. Because high-demand locations will likely be in an urban environment with space constraints, consideration to decrease the surface footprint of the infrastructure without jeopardizing the operational efficiency is necessary for the realization of UAM. The first part of this paper proposes an innovative approach to vertically orient taxiways and parking spaces by utilizing a vertical lift to transport EVTOL aircraft within the vertiplex while meeting the safety-critical requirements outlined in Heliport Design Advisory Circular: AC 150/5390-2c. The second part of the paper evaluates the practical potential of the proposed vertical vertiplex by analyzing relative surface area utilization and operational capacity.

Smart Air Mobility↗