Results for “Urban Air Mobility,” — Page 3

NASA NTRS2022

Conceptual Design of a Tiltduct Reference Vehicle for Urban Air Mobility

NASA is establishing a fleet of conceptual air vehicle designs to support research and development for Urban Air Mobility (UAM). This fleet of vehicles will enable examination of the sensitivity of UAM vehicle designs to technology assumptions, identify key research and development needs for UAM aircraft, and provide the UAM community with reference vehicles that are publicly available and based upon known assumptions. To date, five six-passenger UAM reference vehicles have been published: a single-main-rotor helicopter, a side-by-side helicopter, a quadrotor, a lift-plus-cruise, and a tiltwing. To increase the breadth of vehicle technologies encapsulated in the fleet of NASA UAM reference vehicles, this paper establishes a tiltduct vehicle as an addition to the fleet. The fleet will continue to evolve as future analyses and trade studies are performed. The tiltduct UAM reference vehicle has six tilting ducted proprotors. This paper describes the initial configuration downselection; discusses ducted proprotor design rules of thumb as they applied to the conceptual design of the reference vehicle; describes the vehicle sizing, trade studies, and tuning of models performed; and finally, compares the resulting tiltduct vehicle against the other six-passenger NASA UAM reference vehicles. The high-level analyses performed for this study did not indicate significant differences in performance between the tiltduct and tiltwing reference vehicles, and so vehicle performance alone may not be a key driver in the selection of a tiltduct vehicle over a tiltwing vehicle. However, if ducts are found to have significant acoustical benefits, then acoustical priorities may provide a compelling reason to incorporate ducted proprotors. One significant limitation of the design presented in this paper is that the ducted proprotor performance was tuned based upon performance characteristics observed during historical tests with disk loadings (defined as thrust divided by proprotor disk area) of 125-250 lb/ft$^2$. The tiltduct vehicle designed in this study has a disk loading of 30 lb/ft$^2$, to be more representative of UAM vehicles; further studies to understand performance of ducted proprotors at representative disk loadings are warranted.

Tiltduct↗

NASA NTRSDate not supplied

Immutable Secure Data Exchange and Storage for Urban Air Mobility Environments

The Urban Air Mobility (UAM) environment is derived from the Unmanned Traffic Management (UTM) concept of operations. Within the environment, UAM operators work independently to manage aerial vehicles in the urban environment. Providers of Services (PSU), UAM operators, and Supplemental Data Service Providers provide services to support flight operations within the UAM environment. The intent of this work is to leverage a permissioned blockchain approach, to, simulate secure data exchange and storage for UAM environments. Blockchain technologies can be used for identity management of vehicles, people, and systems.

Blockchain↗

NASA NTRSDate not supplied

NASA’s Secured Airspace for Urban Air Mobility (UAM)

The Urban Air Mobility (UAM) architecture is leveraged from the Unmanned Traffic Management (UTM) concept of operations. Within the UAM environment, UAM operators work collaboratively to manage aerial vehicles in the urban environment. Providers of Services for UAM (PSU), UAM operators, and Supplemental Data Service Providers (SDSP) provide services to support flight operations within that environment. As a recognized need, various views of UAM flight information are provided to the public and public safety entities. To accomplish this, among other goals, the Federal Aviation Administration (FAA) can coordinate flight information between the FAA controlled National Airspace System (NAS) and the UAM environments through the FAA-Industry Data Exchange Protocol (FIDXP). This concept of UAM proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical take-off and landing (VTOL) or short take-off and landing (STOL) aircraft to overcome increasing surface congestion. To garner the support of UAM and to realize its potential, an assurance of cybersecurity is critical for public acceptance. Understanding the various components communicating with one-another cybersecurity, like in other industries, has come to the forefront highlighting the need to protect these networks and systems from cyberattacks. With the planned growth and reach of UAM systems, it’s clear that the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. Consequently, as these threats evolve, the UAM cybersecurity capabilities must adapt to these changes as well. While learning is always the goal, the overall intent of this workshop is to make recommendations on the following: (1) how future UAM environments can be protected against cyber-attacks, and (2) what mechanisms should be put in place to detect attacks against UAM environments.

UAM↗

NASA NTRSDate not supplied

A Data Analysis and Simulation Study of Urban Air Mobility

For the Urban Air Mobility (UAM) industry, NASA has defined a series of UAM Maturity Levels (UML) corresponding to increasingly more complex and operationally dense UAM operations. In support of the gradual progression towards higher UML levels, NASA is currently conducting a set of UAM air traffic simulations—collectively referred to as X4. This paper describes a set of system effectiveness measures, and their associated metrics, for data analysis of X4 simulations. The descriptions, rationales, and calculation procedures for two metrics to be used in data analysis of simulation results, the number of predicted demand-capacity imbalances and the pre-departure delays, are described. Results from data analysis of one set of simulation runs are presented to demonstrate how these metrics support the assessment of performance of the system architecture for X4 simulations and the verification of experiment requirements.

Urban Air Mobility↗

NASA NTRS2021

Advanced Air Mobility(AAM) Ecosystems Working Group Briefing Urban Air Mobility Noise Working Group (UNWG) Subgroup 2: Ground & Flight Testing

Overview of Urban Air Mobility Noise Working Group (UNWG) activities of Subgroup 2, responsible for developing Urban Air Mobility (UAM) vehicle ground and flight testing recommendations for those tasked with evaluating the acoustic characteristics of UAM vehicles under development. This topic is being briefed to an audience at the Advanced Air Mobility (AAM) Ecosystems Working Group Meeting (AEWG).

acoustics↗

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 NTRS2018

Urban Air Mobility Airspace Integration Concepts and Considerations

Urban Air Mobility (UAM) - defined as safe and efficient air traffic operations in a metropolitan area for manned aircraft and unmanned aircraft systems - is being researched and developed by industry, academia, and government. Significant resources have been invested toward cultivating an ecosystem for Urban Air Mobility that includes manufacturers of electric vertical takeoff and landing aircraft, builders of takeoff and landing areas, and researchers of the airspace integration concepts, technologies, and procedures needed to conduct Urban Air Mobility operations safely and efficiently alongside other airspace users. This paper provides high-level descriptions of both emergent and early expanded operational concepts for Urban Air Mobility that NASA is developing. The scope of this work is defined in terms of missions, aircraft, airspace, and hazards. Past and current Urban Air Mobility operations are also reviewed, and the considerations for the data exchange architecture and communication, navigation, and surveillance requirements are also discussed. This paper will serve as a starting point to develop a framework for NASA's Urban Air Mobility airspace integration research and development efforts with partners and stakeholders that could include fast-time simulations, human-in-the-loop (HITL) simulations, and flight demonstrations.

airspace integration↗

NASA NTRS2021

Parametric Study of State-of-Charge for an Electric Aircraft in Urban Air Mobility

The envisioned concept of urban air mobility is anticipated to support passenger transportation, cargo delivery, and emergency services in major metropolitan areas with increasing autonomy levels in the future. Distributed electric propulsion powered electric vertical takeoff and landing aircraft are expected to enable urban air mobility. However, the low specific energy of onboard lithium-ion polymer batteries and wind conditions impose constraints on flight endurance. Therefore, to enable autonomous urban air mobility operations using electric aircraft, one of the critical steps from a safety and efficiency perspective is to understand how various operational and environmental conditions impact the state-of-charge of the onboard lithium-ion polymer batteries. This research performs a parametric study of the state-of-charge for a NASA-proposed conceptual multirotor aircraft flight in the urban environment. The parameters considered for the parametric analysis are cruise airspeed, cruise altitude, climb and descent profiles, wind conditions (wind magnitude, wind direction relative to the route, and wind magnitude uncertainty), and required time of arrival.

Urban Air Mobility↗

NASA NTRS2021

Parametric Study of State of Charge for an Electric Aircraft in Urban Air Mobility

The envisioned concept of urban air mobility is anticipated to support passenger transportation, cargo delivery, and emergency services in major metropolitan areas with increasing autonomy levels in the future. Distributed electric propulsion powered electric vertical takeoff and landing aircraft are expected to enable urban air mobility. However, the low specific energy of onboard lithium-ion polymer batteries and wind conditions impose constraints on flight endurance. Therefore, to enable autonomous urban air mobility operations using electric aircraft, one of the critical steps from a safety and efficiency perspective is to understand how various operational and environmental conditions impact the state-of-charge of the onboard lithium-ion polymer batteries. This research performs a parametric study of the state-of-charge for a NASA-proposed conceptual multirotor aircraft flight in the urban environment. The parameters considered for the parametric analysis are cruise airspeed, cruise altitude, climb and descent profiles, wind conditions (wind magnitude, wind direction relative to the route, and wind magnitude uncertainty), and required time of arrival.

Urban Air Mobility↗

NASA NTRSDate not supplied

A Data Analysis Approach for Simulations of Urban Air Mobility Operations

For the Urban Air Mobility (UAM) industry, NASA has defined a series of UAM Maturity Levels (UML) corresponding to increasingly more complex and operationally dense UAM operations. In support of the gradual progression towards higher UML levels, NASA is currently conducting a set of UAM air traffic simulations—collectively referred to as X4. This paper describes a set of system effectiveness measures, and their associated metrics, for data analysis of X4 simulations. The descriptions, rationales, and calculation procedures for two metrics to be used in data analysis of simulation results, the number of predicted demand-capacity imbalances and the pre-departure delays, are described. Results from data analysis of one set of simulation runs are presented to demonstrate how these metrics support the assessment of performance of the system architecture for X4 simulations and the verification of experiment requirements.

Urban Air Mobility↗

NASA NTRSDate not supplied

Annoyance Model Assessments of Urban Air Mobility Vehicle Operations

As urban air mobility (UAM) vehicles begin to enter service, consideration must be given to vertiport siting and flight routing to help reduce community noise impact and promote adoption by the community. Notwithstanding environmental justice concerns, a possible early strategy is to operate out of existing heliports and fly along established helicopter routes, many of which follow uninhabited waterways and/or roadways (with the thought for the latter that an already noisy ambient environment will mask the sound of the aircraft). However, no prior annoyance model has been fielded that both takes audibility into account and that may be applied to such a real-world strategy. This paper reviews a recently developed annoyance model that includes audibility as a factor and applies it to two flight operations. A simple overflight case is first undertaken to demonstrate the approach. A point-to-point operation in the New York City area is then considered to demonstrate how annoyance varies across an urban soundscape. The cases considered use modeled UAM vehicle noise propagated to a set of ground observers as the signals and either recorded or modeled ambient acoustic data as the maskers.

aircraft community noise↗

NASA NTRSDate not supplied

Annoyance Model Assessments of Urban Air Mobility Vehicle Operations

As urban air mobility (UAM) vehicles begin to enter service, consideration must be given to vertiport siting and flight routing to help reduce community noise impact and promote adoption by the community. Notwithstanding environmental justice concerns, a possible early strategy is to operate out of existing heliports and fly along established helicopter routes, many of which follow uninhabited waterways and/or roadways (with the thought for the latter that an already noisy ambient environment will mask the sound of the aircraft). However, no prior annoyance model has been fielded that both takes audibility into account and that may be applied to such a real-world strategy. This paper reviews a recently developed annoyance model that includes audibility as a factor and applies it to two flight operations. A simple overflight case is first undertaken to demonstrate the approach. A point-to-point operation in the New York City area is then considered to demonstrate how annoyance varies across an urban soundscape. The cases considered use modeled UAM vehicle noise propagated to a set of ground observers as the signals and either recorded or modeled ambient acoustic data as the maskers.

aircraft community noise↗

NASA NTRS2019

Supply Chain Ecosystem for Urban Air Mobility

An update on urban air mobility in context of supply management and where research indicates trends and needs.

UAM↗

NASA NTRS2020

Urban Air Mobility (UAM)

ARMD's urban air mobility strategy, including key activities of UMLs, Grand Challenge series, UAM ecosystem working groups, supply chain management, and modeling simulation tools.

Kopardekar, Parimal H.↗

NASA NTRS2019

Supply Chain Ecosystem for Urban Air Mobility

Future urban mobility promises to deliver transformative impact across the value chain. Consequently, suppliers will face disruption in the form of new technologies, stakeholders and market dynamics. How can supply networks be optimized to meet capabilities that are yet unknown? This session will explore what business models and supply chain strategies can best deliver value for urban air transport and will address how to scale these networks at the pace of this rapidly evolving ecosystem.

Urban Air Mobility↗

NASA NTRSDate not supplied

Eye Glance Behaviors of Ground Control Station Operators in a Simulated Urban Air Mobility Environment

Research into concepts such as advanced air mobility (AAM) and urban air mobility (UAM) offers an opportunity for successfully and safely adding new classes of vehicles into the National Airspace System. However, a need exists for research into the human factors associated with these concepts. In this paper, we evaluate the gaze behaviors of three remote ground control station operators (GCSOs) conducting simulated UAM operations. The participants monitored and controlled an unmanned aircraft system (UAS) from pre-flight to landing using ground control station (GCS) software across nine scenarios within a remote UAS operations center at NASA Langley Research Center (LaRC). As this work was exploratory, descriptive statistics were calculated to provide some initial insight into GCSO gaze patterns associated with the GCS display. Scenarios that required the operator to directly interact with an airspace scheduling system off-screen resulted in fewer on-screen glances than scenarios that did not include direct interactions with the off-screen system. After investigating several areas of interest (AOIs) within the GCS display, participants primarily viewed three AOIs: the map, vehicle status, and operations checklist. The results yielded several GCS design and operational improvement recommendations to include: (a) adding altitude information to the vehicle icon, (b) adding additional traffic information, and (c) including additional GCS training, to reduce the need to scan an operations checklist, which would allow allocation of visual attention towards other AOIs.

Urban Air Mobility↗

NASA NTRSDate not supplied

Theoretical and Simulated Capacity of Urban Air Mobility Airspace Characteristics

As interest in urban air mobility grows, as are the optimistic predictions for potentially hundreds of simultaneous operations within a given metropolitan airspace. This high density of traffic poses a challenge for safe, efficient, and timely operations, particularly when realistic airspace restrictions, fleet sizes, and fluctuating demand are considered. Routes for urban air mobility aircraft, similar to automotive roadways more than other types of airways, are one proposed solution for traffic management. This paper identifies several potential components of urban air mobility routes and compares their numerically predicted maximum capacity with what is achieved in a realistic simulation that includes airspace restrictions, parking limitations, fleet sizes, and uneven demand.

Urban Air Mobility↗

NASA NTRSDate not supplied

Theoretical and Simulated Capacity of Urban Air Mobility Airspace Characteristics

As interest in urban air mobility grows, as are the optimistic predictions for potentially hundreds of simultaneous operations within a given metropolitan airspace. This high density of traffic poses a challenge for safe, efficient, and timely operations, particularly when realistic airspace restrictions, fleet sizes, and fluctuating demand are considered. Routes for urban air mobility aircraft, similar to automotive roadways more than other types of airways, are one proposed solution for traffic management. This paper identifies several potential components of urban air mobility routes and compares their numerically predicted maximum capacity with what is achieved in a realistic simulation that includes airspace restrictions, parking limitations, fleet sizes, and uneven demand.

Urban Air Mobility↗