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At least 307 records · Page 17

Data Science and Urban Air Mobility: Challenges and Opportunities

Aviation is broadly a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.

Urban Air Mobility↗

Wake Vortex Interaction of Urban Air Mobility Aircraft

This paper presents a study of wake vortex interaction modeling for urban air mobility. Wake vortex modeling approaches for fixed-wing aircraft and rotorcraft are investigated. A wake age model is developed that accounts for the temporal and spatial dissipation of the wake-induced downwash. A wake vortex model is developed for rotorcraft that accounts for blade flapping motion and cyclic pitch control to reduce the lift asymmetry. This in turn results in an equal lift circulation strength on the advancing side and retreating side of the rotor. Two wake vortex interaction simulations are performed to illustrate the modeling approaches.

Wake Vortex↗

Regional Air Mobility Market Demand Study

Research objective to identify and measure potential demand for regional air mobility (RAM), in addition to providing emission profiles of competing transportation modes.

Jacob Wishart↗

Demand Forecast Model Development and Scenarios Generation For Urban Air Mobility Concepts

The purpose of this project is to estimate the demand for various Urban Air Mobility Concepts (UAM) of Operations and to generate scenarios for use in analysis and simulations. The demand forecast model, previously developed under NASA/NIA Contract No: NNL13AA08B; Task Order No: NNL16AA36T, for an urban on-demand air-taxi commuter concept is the basis for this work.

M. Rimjha↗

Functional Hazard Assessment for the eVTOL Aircraft Supporting Urban Air Mobility (UAM) Applications: Exploratory Demonstrations

The active development community surrounding electric vertical takeoff and landing (eVTOL) aircraft has demonstrated potential to bring new technological capabilities to market, encouraging visions of widespread and diverse Urban Air Mobility (UAM) applications. New capabilities always come with safety considerations, some familiar and others less so. OEMs who intend to obtain FAA type certification for their eVTOL designs must plan for and execute sufficient safety engineering processes to demonstrate that credible hazards associated with these eVTOL designs are adequately mitigated. This work provides an orientation for eVTOL stakeholders, especially new entrants and those in hybrid roles, to the safety and regulatory context for assuring eVTOL aircraft for UAM applications. We further present selections of functional hazard assessment (FHA) performed on a reference eVTOL concept, with process and decision narration. The exercise allows exploration of several safety considerations specific to eVTOL systems and demonstrates the FHA process together with negotiation of some of its options and variations.

Hazard Analysis↗

Description of the NASA Urban Air Mobility Maturity Levels (UML)

As part of its assessment of the nascent passenger-carrying urban air mobility (UAM)ecosystem, NASA’s UAM Coordination and Assessment Team developed a framework known as the UAM Maturity Level (UML) scale. This framework is intended to have multiple applications including: 1) insight into the likely operational capabilities as a UAM air transportation system develops over time; 2) analysis of technology and regulatory requirements associated with the UAM maturation process; 3) assessment of the current maturity of various segments of the UAM ecosystem; 4) coordination of UAM ecosystem priorities and areas of emphasis; and 5) increasing community and public awareness of UAM and how it may affect mobility in the future. This paper describes the structure of the UML scale and its levels. The paper also describes candidate strategies for advancing between levels, along with associated regulatory gaps and considerations.

Kenneth H Goodrich↗

Comparison Study of Machine Learning Techniques to Predict Flight Energy Consumption for Advanced Air Mobility

This paper addresses the need to predict the flight energy consumption of aerial vehicles in the presence of wind using machine learning techniques. The presented work is critical to achieving sustainable and efficient operations for Advanced Air Mobility (AAM) and to evaluating the readiness of the ground-supporting energy infrastructure, e.g., electric grid and AAM portals. The flight energy consumption is described using the "energy per meter" (EPM) metric. We present a comparison study of influential machine learning techniques in predicting EPM using real-world flight test data. We presented new results of using the Decision Tree, Random Forest, and linear regression techniques, along with our previous results using the Recurrent Neural Network and Feed Forward Neural Network techniques. The comparison results show that the Linear Regression method outperforms other methods on the basis of the Mean Squared Error and error variance.

Machine Learning↗

Air Mobility Data & Reasoning Fabric

Throughout the world, especially in dense urban environments, the quality of life is being negatively impacted by ever growing commute time. Travel, beyond commuting, is increasingly driven by door-to-door challenges ? not just gate-to-gate considerations. Air Mobility may be an approach to address these challenges, as it can effectively convert our 2D mobility system to a 3D mobility system, vastly increasing mobility options.

Air mobility↗

Urban Air Mobility Regional Readiness

What is needed, on a regional level, to prepare for future urban air mobility operations in terms of airspace management, infrastructure, community, and aircraft.

Kopardekar, Parimal↗

Initial Development and Integration of a Vertiport Automation System for Advanced Air Mobility Operations

The High Density Vertiplex Sub-Project, as part of NASA’s Advanced Air Mobility (AAM) Project, has been developing a reference Vertiport Automation System (VAS) to support the management of arrival and departure operations in the terminal area of a vertiport or network of inter-connected vertiports known as a vertiplex. The VAS is potentially a key element of an integrated AAM architecture that will enable greater levels of coordination and predictability for vertiport users through its integration and sharing of information, and greater control of vertiport resources for managing operators. This paper provides an overview of the VAS and a description of an initial implementation that has been integrated into a broader reference architecture as part of ongoing research. Examples from recent simulations are presented with an outline for next steps and considerations.

vertiport↗

A Psychoacoustic Test for Urban Air Mobility Vehicle Sound Quality

This paper describes a psychoacoustic test in the Exterior Effects Room (EER) at the NASA Langley Research Center. The test investigated the degree to which sound quality metrics (sharpness, tonality, etc.) are predictive of annoyance to notional sounds of Urban Air Mobility (UAM) vehicles (i.e., air taxis). A suite of 136 unique (4.6 second duration) UAM rotor noise stimuli was generated. These stimuli were based on aeroacoustic predictions of a NASA reference UAM quadrotor aircraft under two flight conditions. The synthesizer changed rotor noise parameters such as the blade passage frequency, the relative level of broadband self-noise, and the relative level of tonal motor noise. With loudness constant, the synthesis parameters impacted sound quality in a way that created a spread of predictors both in synthesizer parameters and in sound quality metrics. Forty subjects listened to the suite of UAM noise stimuli in the EER and judged each sound individually on a standard scale of annoyance. Additionally, a subset of the UAM noise stimuli were compared to a reference sound that varied in loudness. From these responses, the relative effect of changes in loudness or changes in other sound quality metrics on annoyance was evaluated. This paper covers background and motivation for the test, details of how the sound stimuli were generated, and details of the test design and execution. Test results investigate how sound quality may affect perceived annoyance to UAM vehicle noise, indicating the importance of sharpness, tonality, impulsiveness, and roughness on annoyance to UAM noise.

UAM↗

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↗

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↗

TCAS Alerts from Simulated Urban Air Mobility Flights Along FAA Helicopter Routes in Dallas-Fort Worth

This is a presentation of the current state of a TCAS study being conducted by the ATM-X project. This study examines the rate at which an urban air mobility vehicle flying along existing helicopter routes near DFW will trigger alerts on the TCAS II systems equipped on commercial airliners flying in the D10 TRACON of DFW airspace. The presentation will cover initial results, as well as next steps on the path towards producing a full paper. These initial results show that some aircraft could fly along published helicopter routes, while obeying published restrictions, and fly into and out of DFW airport without triggering any TCAS RAs, so long as the airport is operating in South Flow and the UAM vehicles approach and depart; the airport in the same direction as commercial traffic. Attempting to take off opposite the direction of commercial traffic produces a large number of TCAS RAs. Future work will examine North Flow, check sensitivity to aircraft performance, and examine alternative routes.

helicopter routes↗

Collaborative Weather Research and Development for Urban Air Mobility

NASA recently collaborated with National Center for Atmospheric Research (NCAR) and AvMet Application Inc. to identify the weather information, existing aviation weather products, and the novel approaches that are required to model and mitigate various impacts of uncertain atmospheric conditions to support safe and efficient Urban Air Mobility (UAM) operations. This presentation will provide updates on the collaborative efforts of weather impacts modelling and analysis for future evaluation of UAM concepts of operations in the presence of weather.

Urban Air Mobility↗

High-Fidelity Simulations of a Quadrotor Vehicle for Urban Air Mobility

High-fidelity computational fluid dynamics simulations have been carried out to analyze NASA’s quadrotor air taxi concept for urban air mobility. High-order accurate schemes, dual-time stepping, and the delayed detached-eddy simulation model have been employed. The flow solver has been loosely coupled with the rotorcraft comprehensive analysis code. The vehicle simulated is a six-passenger quadrotor for air taxi operations. The quadrotor has been simulated in hover and cruise, with flight conditions representative of an air taxi mission. Initially, the quadcopter vehicle is analyzed using low-fidelity tools. Then, a complete analysis using high-fidelity simulations of the quadcopter is performed in conjunction with collective pitch control. Airloads, wake geometry, and performance are studied and compared. A comparison between isolated rotors and complete vehicle simulations is presented. NASA’s quadrotor is one of NASA’s concept vehicles designed in support of aircraft development for vertical take-off and landing air taxi operations.

ARMD↗

Guidance for Designing Safety into Urban Air Mobility: Hazard Analysis Techniques

The national airspace system is exceptionally safe, specifically in terms of commercial air traffic operations. The introduction of innovative aircraft (such as electric vertical takeoff and landing vehicles) undergoing novel operations (such as for an urban air passenger carrying mission) is a potential disruptor to the current means of regulating and ensuring the safety of air travel. The aviation industry and associated regulatory bodies are adapting their approaches to assuring system safety to enable these new paradigms. However, any system safety analysis requires that a hazard assessment be performed. In this work, we consider the Functional Hazard Assessment (FHA) and Systems Theoretic Process Analysis (STPA) techniques for hazard assessment and evaluate whether they can be used in a complementary fashion for regulatory approval purposes. We perform an FHA and an STPA on an electric vertical takeoff and landing (eVTOL) vehicle undergoing an urban air mobility (UAM) passenger carrying reference scenario and present excerpts of this analysis. We then draw parallels between the techniques and highlight elements where they naturally reinforce to each other’s results, specifically in the consideration of hazard severity with respect to flight phases, the design of hazard mitigations, and the applicability of the results to all types of regulatory approvals (e.g., type certification, operational approval, and crew training).

Mallory S Graydon↗