Status of UAM Proprotor Design Validation Campaign: Available Data and Computational Tools
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Optimization↗
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Rapid Aero Modeling of a Lift+Cruise UAM Configuration for Stability and Control Using Overset Grid CFD
This talk will address some aspects of an effort to develop both static and dynamic stability and control derivatives of a generic Lift+Cruise Urban Air Mobility vehicle. In particular, the use of NASA overset grid CFD packages OVERFLOW and Chimera Grid Tools allowed for rapid grid and solution generation while varying many database factors. Approach details include coarse gridding and control effectors, rotor disk modeling, convergence evaluation, and parallel execution on a midrange compute resource. A brief *description of the Rapid Aero Modeling (RAM) approach, including design of experiments and response surface modeling, will be given, and recent simulations of powered and unpowered dynamic multisine maneuvers will be presented.
Overset Grid CFD↗
Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles
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Optimal Reciprocal Collision Avoidance↗
Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles
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Optimal Reciprocal Collision Avoidance↗
Influence of the Perception Constraint, Observer Position, and Broadband Self-Noise on Low-Fidelity UAM Vehicle Perception-Influenced-Design (PID) Optimization
This paper will present an approach in design optimization of a proprotor in a forward flight condition with several acoustic objective functions that simulate community response. An adjoint-capable blade element momentum theory (BEMT), implemented in CCBlade.jl, will be used to compute the blade forces and inflow properties required to compute tonal and broadband noise using the second-generation Aircraft NOise Prediction Program (ANOPP2). The influence of broadband noise, observer location, and choice of perception constraint on optimized values of rotation rate, chord distribution, and twist angle will be shown. It is determined that broadband self-noise is an influential source noise mechanism in the design optimization when frequency weighting is used to predict the noise at an out-of-plane observer position.
acoustics↗
TFWAS Interdisciplinary Paper Session: Ultrasonic Additive Manufacturing (UAM) of Liquid Cold Plate Heat Exchangers for NASA Thermal Management Applications
No abstract provided
Mastropietro, A. J. J↗
Design Studies on Mechanically Geared, Magnetically Geared, and Direct Drive Drivetrains for UAM Applications
Urban air mobility vehicles require high reliability and high performance electric motor drive trains. In this paper, a design optimization study is carried out to compare mechanically geared, magnetically geared, and direct drive motor drivetrain topology achievable performance in a 100 kW hover power quad rotor propulsor application. Design studies are carried out accounting for a nominal mission profile. Studies are carried out assuming constant propulsor rotor RPMs of 400, 1000, 2000, and 3000 RPM. Results show that mechanically geared drives are the lightest at all RPMs but their weight benefit over direct drive and magnetically geared decays with increased rotor RPM. Direct drive is shown to always achieve the highest efficiency due to its lower motor speed resulting in low electrical frequencies. Magnetically geared drivetrains are shown to need some requirement refinement or technology improvement to provide significant benefit over direct drive drivetrains.
Thomas Tallerico↗
Design Studies on Mechanically Geared, Magnetically Geared, and Direct Drive Drivetrains for UAM Applications
Urban air mobility vehicles require high reliability and high performance electric motor drive trains. In this paper, a design optimization study is carried out to compare mechanically geared, magnetically geared, and direct drive motor drivetrain topology achievable performance in a 100 kW hover power quad rotor propulsor application. Design studies are carried out accounting for a nominal mission profile. Studies are carried out assuming constant propulsor rotor RPMs of 400, 1000, 2000, and 3000 RPM. Results show that mechanically geared drives are the lightest at all RPMs but their weight benefit over direct drive and magnetically geared decays with increased rotor RPM. Direct drive is shown to always achieve the highest efficiency due to its lower motor speed resulting in low electrical frequencies. Magnetically geared drivetrains are shown to need some requirement refinement or technology improvement to provide significant benefit over direct drive drivetrains.
Thomas Tallerico↗
Influence of the Perception Constraint, Observer Position, and Broadband Self-Noise on Low-Fidelity UAM Vehicle Perception-Influenced-Design (PID) Optimization
This paper will present an approach in design optimization of a proprotor in a forward flight condition with several acoustic objective functions that simulate community response. An adjoint-capable blade element momentum theory (BEMT), implemented in CCBlade.jl, will be used to compute the blade forces and inflow properties required to compute tonal and broadband noise using the second-generation Aircraft NOise Prediction Program (ANOPP2). The influence of broadband noise, observer location, and choice of perception constraint on optimized values of rotation rate, chord distribution, and twist angle will be shown. It is determined that broadband self-noise is an influential source noise mechanism in the design optimization when frequency weighting is used to predict the noise at an out-of-plane observer position.
acoustics↗
Urban Air Mobility (UAM) Procedure Design and Flight Test Evaluation Methodology
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David Zahn↗
Operational Integration Assessment (OIA) of Midterm UAM Operations in the NAS
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Jason Prince↗
Analysis of Helicopter and UAM Laboratory Comparison (HULC) Psychoacoustic Test
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HULC↗
Conceptualizing UAM: Technologies and Methods for Safe and Efficient Urban Air Transportation
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Lidia Zewde↗
National Campaign (NC)-1 Strategic Conflict Management Simulation (X4) Final Report
Urban Air Mobility (UAM) enables highly automated, cooperative, passenger or cargo-carrying air transportation services in and around urban areas. UAM is a subset of the Advanced Air Mobility (AAM) concept under development by the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), and industry. The Strategic Conflict Management (SCM) Simulation, dubbed “X4”, was conducted between July 2021 and June 2022 by NASA with the FAA and industry to evolve the Provider of Services for UAM (PSU) that will be needed to ensure initial UAM operations can scale in the National Airspace System (NAS). The FAA UAM Concept of Operations (ConOps) v1 [1] served as an initial guiding document for the X4 airspace management system design to ensure the architecture supports testing of services provided by third-party service providers. To that end, the X4 architecture leveraged concepts and technologies developed for Unmanned Aircraft System (UAS) Traffic Management (UTM) while also developing and testing new capabilities and services needed for UAM. The architecture included an initial prototype of the FAA-Industry Exchange Protocol (FIDXP), third-party services such as the PSUs, and Discovery and Synchronization Service (DSS), and other new services such as Demand-Capacity Balancing (DCB) to facilitate UAM strategic conflict management. During X4, NASA led discussions and collaborated with seven industry airspace partners to develop initial airspace management concepts for UAM that drove what would be tested and evaluated during the simulations. The initial capabilities defined for PSU leveraged UTM UAS Service Supplier (USS) as a starting point and evolved to meet UAM requirements. These discussions were also an opportunity for NASA to collaborate with industry to develop a set of initial Community-Based Rules (CBRs). These CBRs enabled how UAM traffic would be cooperatively managed among UAM operators. The collaborative, iterative process of developing CBRs with industry during X4 provided insight into the challenges involved and identified the need for a suitable and effective forum for future CBR development. In parallel with these discussions, NASA conducted a series of seven software sprints and two collaborative simulations with the airspace partners that built up in complexity. Over the course of the year, all seven partners successfully completed all the sprints by demonstrating the required capabilities. They also participated in the two collaborative simulations to demonstrate how multiple PSUs could work together in a collaborative, more complex environment with higher traffic density. The X4 simulation accomplished NASA's objectives and helped advance the development of the seven participating PSUs. The lessons learned provided insight into key elements of the UAM Notional Architecture from the FAA ConOps v1 [1] and UTM technologies when applied to UAM: - Having a Concept of Use (ConUse) defined prior to the activity would accelerate the time and effort from concept development to testing. - While the UAM Notional Architecture provided a starting point for a federated architecture that support services provided by third-party providers, the USS and PSU differed in their capability definitions for operational intent submission and sharing, conformance monitoring, airspace authorization, strategic conflict management, airspace constraints and dynamic replanning. - While existing DSS developed for UTM provided a way for PSU and other UAM services (such as DCB) to discover relevant operations from each other, additional complexity and challenges were found during X4 testing and illuminated the need for a more suitable solution for UAM. Industry can leverage the results of this demonstration to accelerate UAM requirements, CBRs, and standards development. The FAA and other government municipalities and agencies will be able to leverage results to inform future policies and identify additional gaps that require further analysis, moving toward operationalization of UAM.
Urban Air Mobility↗
National Campaign (NC)-1 Strategic Conflict Management Simulation (X4) Community Based Rules
Projected demand for transportation services in the urban environment has led to the development of several Concepts of Operation for Urban Air Mobility, or UAM. UAM is a concept for the transportation of people and goods in the metropolitan environment using small, efficient aircraft over short distances as part of an expanding multimodal transportation network. UAM will leverage emerging technologies including electric Vertical Takeoff and Landing (eVTOL) aircraft, increasing levels of automation and a new operational paradigm in dense airspace where a set of agreed-upon rules govern the procedures and interactions defining a cooperative environment in which operators are entrusted with a range of functions typically conducted by Air Traffic Control (ATC). These rules, proposed in the FAA NextGen Office’s UAM Concept of Operations [1], were originally termed Community Based Rules or Community Business Rules (CBRs), and will in the future termed Cooperative Operating Practices (COPs); this document uses the original term, CBR. CBRs are a set of rules, developed by the UAM community and (where necessary) approved by the FAA that govern the interactions between UAM entities and limit the need for ATC services including, but not limited to, separation control by ATC, addressing a fundamental challenge to scaling UAM operations. UAM community development of CBRs is anticipated to accelerate the adoption of new practices while retaining the regulatory authority of the FAA within required domains (e.g., NAS safety, security and equal access). However, there currently exists no agreed industry forum or defined procedures for CBR development. Investigation of best practices for the development of UAM CBRs was identified by NASA and the FAA NextGen Office as a research need. In collaboration with seven industry partners, NASA participated in a series of simulations that investigated elements of the envisioned UAM operations, with a primary focus on Strategic Conflict Management (SCM). The development and conduct of cooperative UAM simulations with seven industry partners provided a unique opportunity to investigate CBR development practices. Development of CBRs for the UAM SCM simulations was conducted in parallel with simulation capability development and was closely related to requirements definition for the simulations. As such, the CBR development effort presented herein had two objectives: explore CBR development practices in collaboration with the industry partners and develop an initial set of UAM CBRs to support simulation requirements definition and development. Consensus was achieved among NASA and the industry partners on 24 CBRs that were developed to support the cooperative simulation operations across five topic areas: General (related to test requirements), Operational Intent, Conformance Monitoring, Demand Capacity Balancing, and Airspace Constraint Management. Additional topic areas and CBRs were discussed but were deemed outside the scope of the simulation; these are included in the appendices. A collaborative, iterative process was employed for developing the CBRs engaging both NASA and Industry; because CBR development is envisioned to be community-driven, opportunities were sought that provided industry partners leadership roles in developing CBRs. The following key observations and recommendations may aid the UAM industry in future CBR development efforts: - The lack of a defined process proved challenging initially. Stakeholder engagement in the early stages of CBR development was intermittent and may have been due to the lack of a clear definition of roles and responsibilities of those involved in the effort. - Industry leadership of CBR topic areas proved successful. Discussions in these topic areas were engaging, with alternate viewpoints freely discussed and detailed CBRs resulting. This points to the importance of identifying the best-suited leadership in technical areas for CBR development. - Discussions within a CBR topic area were typically dominated by only a few participants. Whereas all industry partners contributed to CBR development, within each topic area, technical leadership was evident even when not formally established. This observation may indicate that smaller, focused groups may be more effective in initial CBR development than an open forum or large standards development effort (although both maybe required prior to FAA review and approval for some CBRs). - Identifying suitable forums for initial UAM CBR development and identifying the most effective industry participants and leadership will be crucial for successful CBR development. Although the operational need for UAM CBRs may not be immediate, establishing the forums and leadership to define the processes for CBR development is a prudent early step to UAM realization.
Community Based Rules↗
Provider of Services for Urban Air Mobility (PSU) Prototype Simulation (X5) Final Report
Urban Air Mobility (UAM) is a new air transportation service concept to carry passengers or cargo in metropolitan areas, leveraged by innovative aircraft and air traffic automation technologies. NASA has conducted a series of simulations, called the X-series simulation, to evaluate the UAM concept of operations and support the development of airspace procedures and services for UAM operations. The simulation called “X5” was conducted in 2023 to test a Provider of Services for UAM (PSU) prototype developed by NASA for UAM flight planning, strategic conflict management support, and data exchange between UAM operators. In this simulation, two strategic conflict management capabilities, Demand-Capacity Balancing and Sequencing and Scheduling, were further investigated. This document describes the UAM system architecture modeled, the X5 simulation environment to be executed (e.g., traffic scenario and UAM airspace construct), and the strategic conflict management processes developed and evaluated in this study. Then, the simulation results are provided using several system performance metrics, such as the number of operations planned and activated, demand-capacity imbalances detected and resolved, and pre-departure delays. Based on these metrics, the test findings and lessons learned from this simulation are discussed. NASA developed a PSU prototype as part of a reference implementation of UAM system architecture and evolved strategic conflict management capabilities for UAM operations from the previous collaborative simulations with industry partners. Below is the summary of the achievements: - Aligned NASA’s UAM reference architecture with the FAA’s UAM ConOps notional architecture - Extended UAM airspace management capabilities to include 1) Demand-Capacity Balancing (DCB) to ensure operators coordinate planned usage of shared vertiports, and 2) Sequencing and Scheduling (S&S) at UAM corridor entry and exit points to help facilitate an orderly flow of traffic - Defined the PSU information exchange APIs and requirements towards informing industry standards - Developed and tested a NASA PSU prototype as reference implementation to validate the requirements and APIs - Developed a prototype service connecting NASA’s PSU and the FAA system for testing future PSU-ATM interface requirements - Tested NASA-developed assumptions for UAM operations such as airspace design, procedures, vehicle performance, and strategic conflict management methods to inform future Cooperative Operating Practices (COPs) development with industry - Evaluated system performance metrics such as number of simultaneous operations and ground delays that can help define system-level requirements. The simulation results showed that the UAM traffic demand could be managed to minimize the needs of tactical separation provision with ground delays assigned by DCB and S&S. These accomplishments and the lessons learned from the PSU Prototype X5 simulation activities will be valuable inputs for the Air Mobility Pathfinders (AMP) project, which is NASA’s new project to create and evaluate a reference architecture for safe, secure, and scalable UAM operations.
Simulation↗
Demand Capacity Balancing at Vertiports for Initial Strategic Conflict Management of Urban Air Mobility Operations
Urban Air Mobility (UAM) is a new transportation concept that enables highly automated, cooperative, passenger or cargo-carrying air transportation services in and around urban areas. To achieve the high level of operational density and complexity desired by the UAM community, an airspace system that allows UAM operators to readily access and operate safely and efficiently in the airspace is needed. This airspace system will require air traffic management designed to reduce the risk of conflicts and loss of separation between UAM flights. In general, strategic conflict management is considered as the first layer of conflict management for safe flight operations to condition the traffic to reduce the need for airborne separation provision, the second layer of conflict management. Demand Capacity Balancing (DCB) is one of the concept components to achieve strategic conflict management. DCB strategically evaluates traffic demand and resource capacities to allow UAM operators to determine when, where and how they operate, while mitigating conflicting needs for airspace and vertiport capacity. DCB can be applied whenever UAM demand exceeds the capacity in airspace or at vertiports. As the UAM ecosystem evolves with advanced technologies and matured operational procedures, more complicated conflict management will likely be needed. In the current UAM ‘Concept of Operation (ConOps) 1.0’ operational stage defined by FAA, however, it will be meaningful to explore the demand capacity balancing at vertiports only, as an initial strategic conflict management approach for UAM operations because vertiport capacity seems to be a bottleneck of UAM traffic. For this research, we developed a demand-capacity imbalance detection and resolution service for UAM. This DCB service identifies the demand from operators and compares the demand to a given capacity at the shared resources (i.e., vertiports) over the upcoming time horizon which is divided into time bins having a constant interval. When a new flight plan is submitted, the algorithm embedded in the DCB service checks the available time bins based on the desired departure time and estimated arrival time at origin and destination vertiports, respectively. If the time bins for the originally desired times are already occupied by other flights (i.e., demand is at or above capacity), the algorithm finds the next available time bins for takeoff and landing and shifts the conflicting departure time to the earliest time that satisfies the capacity constraints at both origin and destination vertiports. The details of the algorithm will be described in the final manuscript. Figure 1 shows that the proposed DCB algorithm works well for a sample traffic scenario. In this example, a total of 144 flights, split between two operators, are planned over 2 hours, traveling 10 routes between five vertiports. In the heatmaps, the horizontal axis shows 12 time bins where each bin represents a 12-minute interval, and the vertical axis shows five vertiports. The number in each cell shows the number of operations, counting both departures and arrivals, at a specific vertiport in each time bin. For the given capacity of 2 operations/vertiport/bin, Figure 1 shows that the original demand sometimes exceeds the capacity, but the modified demand is reduced to the given capacity after resolving demand-capacity imbalances. When UAM flights are operated, it is expected that many practical issues would arise in the federated system architecture with multiple operators. UAM operators may experience a time synchronization issue due to communication delay between operator and vehicle. UAM vehicles would fly at different flight speeds, depending on vehicle models. Actual departure and arrival times can have large variations, compared to the schedule. The lead time from flight plan submission to desired departure time can vary by service type (e.g., regular shuttle service vs. on-demand service). Using the proposed DCB algorithm, we also investigated how the actual flight schedule and DCB performance are affected by these uncertainties such as unsynchronized times between operators, flight speed differences, lead time differences, and departure time errors. The final manuscript will include the background of this research work, the description of the DCB algorithm and its use cases with traffic scenarios. It will also provide the analytical results about the impact of various uncertainties that can occur in actual UAM operations on the DCB at vertiports, in terms of demand distribution changes, number of simultaneous operations, and delay propagation.
Urban Air Mobility↗
A Blockchain Case Study for Urban Air Mobility Operational Intent
The next generation of aerial passenger and cargo transportation may leverage the concept of Urban Air Mobility (UAM). UAM is a concept that proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical takeoff and landing (VTOL) or short takeoff and landing (STOL) aircraft to overcome increasing surface congestion [1]. The UAM concept leverages a decentralized service-based architecture for airspace solutions. Within the 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 the UAM environment. Also, various views of UAM flight information are provided to the public and public safety entities [2]. 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). To realize the potential of UAM, an assurance of cybersecurity is critical for public acceptance. Cybersecurity has come to the forefront highlighting the need to protect these networks and systems from cyberattacks. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. As these threats evolve, the UAM cybersecurity capabilities must adapt to these changes as well [3]. This research focuses on the secure data exchange and storage of this decentralized UAM environment to address these challenges. This research intends to leverage a permissioned blockchain approach to address cybersecurity threats that may impact a UAM environment. Blockchain technologies can be used for tracking transactions and verifying negotiated agreements between stakeholders in the NAS environment. For example, the record of the submitted flight plan and the approved flight plan could be verified using the Blockchain-based immutable ledger.
UAM↗