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At least 559 records · Page 31

A Research Platform for Urban Air Mobility (UAM) and UAS Traffic Management (UTM) Concepts and Application

The purpose of this paper is to describe a research platform for the Urban Air Mobility (UAM) concept. UAM was conceived to enable short-range, low-altitiude service to commuters in metropolitan areas. At the NASA Ames Airspace Operations Laboratory (AOL) user interfaces have been developed to support small UAS operations for the UAS Traffic Management (UTM) project. Due to operational similarities between UAM and UTM, the UTM architecture offers a convenient starting point for research and development of UAM operations. Herein, we begin with an overview of the primary need and expectations characterizing concepts for modern air transportation systems, followed by a brief description of the UTM and UAM concepts. We then describe the UTM architecture, as well as the AOL's research platform and capabilities. The potential applications for UAM research and development are then discussed, providing some direction for future research efforts.

UAM↗

Design of Low Inductance Busbar for 500 kVA Three-Level ANPC Converter

The adoption of SiC devices in high power applications enables higher switching speed, which requires lower circuit parasitic inductance to reduce the voltage overshoot. This paper presents the design of a busbar for a 500 kVA three-level active natural clamped converter. The layout of the busbar is discussed in detail based on the analysis of the multiple commutation loops, magnetic cancelling effect, and DC-link capacitor placement. The loop inductance of the designed busbar is verified with simulation, impedance measurements and converter experiment. The results can match with each other and the inductances of small and large loop are 6.5 nH and 17.5 nH respectively, which is significantly lower than the busbars of NPC type converters in other references.

SiC MOSFET↗

Exploring Network-Related Optimization Problems Using Quantum Heuristics

Network-related connectivity optimization problems are underlying a wide range of applications and are also of high computational complexity. We consider studying network optimization problems using two types of quantum heuristics.One is quantum annealing, and the other Quantum Alternating Operator Ansatz, an extension of the Quantum Approximate Optimization Algorithms for gate-model quantum computation, in which a cost-function based unitary and a non-commuting mixing unitary are applied alternately. We present problem mappings for problems of finding the spanning-tree or spanning-graph of a graph that optimizes certain costs, and a variant that further requires the spanning-tree be degree-bounded. With quantum annealing, all constraints are cast into penalty terms in the cost Hamiltonian, and the solution is encoded as the ground state of the Hamiltonian. We provide three mappings to the quadratic unconstrained binary optimization (QUBO) form, compare the resource requirements, and analyze the tradeoffs. For QAOA, we give special focus on the design of mixers based on the constraints presented in the problem, such that the system evolution remains in a subspace of the full Hilbert space where all constraints are satisfied. In the spanning-tree problem, one such hard constraint is that a mixer applied to a spanning-tree needs also be a spanning tree. This involves checking the connectivity of a subgraph, which is a global condition common for most network-related problems. We show how this feature can be efficiently represented in the mixer in a quantum coherent way, based on manipulation of a descendant-matrix and an adjacent matrix. We further develop a mixer for the spanning-graphs based on the spanning-tree mixer.

Wang, Zhihui↗

Commercialization and Human Settlement of the Moon and Cislunar Space Using ISRU, Fission Surface Power, and Advanced In-Space Propulsion Systems

Over 50 years have passed since themovie 2001: A Space Odyssey debuted in April 1968. In the film, Dr. Heywood Floyd flies to a large artificial gravity space station orbiting Earth aboard a commercial space plane. He then embarks on a commuter flight to the Moon arriving there 25 hours later. Today, on the 50th anniversary of the Apollo 11lunar landing, the images portrayed in 2001 remain well beyond our capabilities and 2100: A Space Odyssey seems a more appropriate title for Kubrick and Clarke's film. This paper looks at the key technologies, systems, and supporting infrastructure (in-situ resource utilization (ISRU), fission surface power (FSP), nuclear thermal propulsion (NTP), andorbiting propellant depots), that could be developed by NASA and the private sector over the next 30years allowing the operational capabilities presented in 2001 to be achieved, albeit on a more spartan scale.

Borowski, Stan↗

Simulating Fleet Noise for Notional UAM Vehicles and Operations in New York

This paper presents the results of systems-level simulations using Metrosim that were conducted for notional Urban Air Mobility (UAM)-style vehicles analyzed for two different scenarios for New York (NY). UAM is an aviation industry term for passenger or cargo-carrying air transportation services, which are often automated, operating in an urban/city environment. UAM-style vehicles are expected to use vertical takeoff and landing with fixed wing cruise flight. Metrosim is a metroplex-wide route and airport planning tool that can also be used in standalone mode as a simulation tool. The scenarios described and reported in this paper were used to evaluate a fleet noise prediction capability for this tool. The work was a collaborative effort between the National Aeronautics and Space Administration (NASA), Intelligent Automation, Inc (IAI), and the Port Authority of New York and New Jersey (PANYNJ). One scenario was designed to represent an expanded air-taxi operation from existing helipads around Manhattan to the major New York airports. The other case represented a farther term vision case with commuters using personal air vehicles to hub locations just outside New York, with an air-taxi service running frequent connector trips to a few key locations inside Manhattan. For both scenarios, the trajectories created for the entire fleet were passed to the Aircraft Environmental Design Tool (AEDT) to generate Day-Night Level (DNL) noise contours for inspection. Without data for actual UAM vehicles available, surrogate AEDT empirical Noise-Power-Distance (NPD) tables used a similar sized current day helicopter as the Baseline, and a version of that same data linearly scaled as a first guess at possible UAM noise data. Details are provided for each of the two scenario configurations, and the output noise contours are presented for the Baseline and reduced noise DNL cases.

Glaab, Patricia↗

Study network-related optimization problems using quantum alternating optimization ansatz

Network-related connectivity optimization problems are underlying a wide range of applications and are also of high computational complexity. We consider studying network optimization problems using two types of quantum heuristics. One is quantum annealing, and the other Quantum Alternating Operator Ansatz, an extension of the Quantum Approximate Optimization Algorithms for gate-model quantum computation, in which a cost-function based unitary and a non-commuting mixing unitary are applied alternately. We present problem mappings for problems of finding the spanning-tree or spanning-graph of a graph that optimizes certain costs, and a variant that further requires the spanning-tree be degree-bounded. With quantum annealing, all constraints are cast into penalty terms in the cost Hamiltonian, and the solution is encoded as the ground state of the Hamiltonian. We provide three mappings to the quadratic unconstrained binary optimization (QUBO) form, compare the resource requirements, and analyze the tradeoffs. For QAOA, we give special focus on the design of mixers based on the constraints presented in the problem, such that the system evolution remains in a subspace of the full Hilbert space where all constraints are satisfied. In the spanning-tree problem, one such hard constraint is that a mixer applied to a spanning-tree needs also be a spanning tree. This involves checking the connectivity of a subgraph, which is a global condition common for most network-related problems. We show how this feature can be efficiently represented in the mixer in a quantum coherent way, based on manipulation of a descendant-matrix and an adjacent matrix. We further develop a mixer for the spanning-graphs based on the spanning-tree mixer.

Zhihui Wang↗

Distributed Pressure Sensing for Enabling Self-Aware Autonomous Aerial Vehicles

Autonomous aerial transportation will be a fixture of future robotic societies, simultaneously requiring more stringent safety requirements and fewer resources for characterization than current commercial air transportation. More robust, adaptable, self-state estimation will be necessary to create such autonomous systems. We present a modular, scalable, distributed pressure sensing skin for aerodynamic state estimation of a large, flexible aerostructure. This skin used a network of 22 nodes that performed in-situ computation and communication of data collected from 74 pressure sensors, which were embedded into the skin panels of an ultra-lightweight 14-foot wingspan made from commutable, lattice-based subcomponents, and tested at NASA Langley Research Center's 14X22 wind tunnel. The density of the pressure sensors allowed for the use of a novel distributed algorithm to generate estimates of the wing lift contribution that were more accurate than the direct integration of the pressure distribution over the wing surface.

Daniel Cellucci↗

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↗

Prospective Futures of Distance Education

Society is in the midst of IT, Bio, Nano, Quantum and Energetics Technology Revolutions, which have changed and are changing econometrics, national security, health, transportation, shopping, travel, cost of living, socialization, commerce, employment, and education. We are now beyond the Industrial Age, are in the IT Age and heading rapidly into the Virtual Age.In that process we are changing from physical activities to virtual activities, developing and embracing tele-everything including tele-commuting, tele-work, tele-travel, tele-education, tele-shopping, tele-medicine, tele-commerce, tele-socialization, tele-politics and with on-site printing manufacture, tele-manufacturing. The gig economy, largely on the web and operated virtually, is a large and increasing portion of the national economy. Tele-everything took a great leap forward during the COVID pandemic response

Dennis M. Bushnell↗

Correlated Electromagnetic Levitation Actuator: A Reaction Sphere Based Attitude Control System

To address problems experienced by current reaction wheels and control moment gyroscopebased attitude control systems (ACS), researchers at NASA’s Marshall Space Flight Center have begun developing a reaction sphere actuator based on correlated electromagnetic levitation that will be immune to destructive bearing friction, momentum saturation, and gimbal lock. The Correlated Electromagnetic Levitation Actuator (CELA) advances the state of the art of reaction sphere ACSs by employing the concept of correlated magnetics. It is a frictionless, direct-drive reaction sphere that harnesses a unique technology with an array of applications across multiple disciplines. Correlated electromagnets function in a manner that is analogous to a matched filter; the convolution of two signals is peaked at the index representing the greatest match. For CELA, the signals are the patterns of magnetic flux density as a function of position. The magnitude of the convolution equates to an attractive or repulsive force, and these forces can be azimuthal or radial. The development of CELA is based in four distinct disciplines: Advanced Manufacturing, Prototype Development, Electromagnetic Modeling, and Controls. We are developing novel manufacturing techniques required to build arrays of permanent and electromagnet dipoles on curved surfaces. To print the permanent magnetic array, we have developed a probe with pyramidal magnets that will reside on a robotic arm to induce localized magnetic fields on a surface. The probe also includes the ability to erase dipole patterns from a permanent magnet by heating the surface to its Curie temperature. A number of test articles and prototypes have been developed using additive manufacturing methods. These prototypes have included hemispherical motors to test the drive algorithm, and a levitation test bed that demonstrates a magnetic bearing method based on attractive magnetic forces and ratiometric Hall effect sensors. We developed an array of electromagnetic dipoles on a printed circuit board (PCB) with individual H-bridges controlling each coil. This device created various flux density patterns and we measured their magnetic fields using a custom Hall effect 3-D probe and a LabVIEW virtual instrument. These data will serve as a benchmark for characterizing the accuracy of future models. Current work is focused on modeling the magnetic fields of our prototype arrays using COMSOL Finite Element Analysis and verifying the model against our test data. Accurate modeling will allow us to quickly test new patterns of electromagnets and their macro behavior. Eventually, the magnetic field models will be implemented in our controls simulations to facilitate precise control of the reaction sphere. Initial model results agree with field measurements to within 1 G (5% of measured flux density). Currently, we are testing different material properties of the electromagnets and their magnetic fields and thermal effects. These results will be used to refine the design of the electromagnetic dipoles. Our control efforts have centered on developing commutation, levitation, and field pattern shaping hardware in the form of breadboards and PCBs with software running on a local microcontroller. In addition, our partners developed MATLAB Simulink models to demonstrate a PID controller thatmitigates disturbance forces resulting from the interaction of drive and levitation magnetics. Finally, we have designed a three-axis test stand that will be used in future work to demonstrate CELA’s orientation control capability.

controls↗

Correlated Electromagnetic Levitation Actuator: A Reaction Sphere-Based Attitude Control System

To address problems experienced by current reaction wheels and control moment gyroscopebased attitude control systems (ACS), researchers at National Aeronautics and Space Administration’s (NASA’s) Marshall Space Flight Center (MSFC) have begun developing a reaction sphere actuator based on correlated electromagnetic levitation that will be immune to destructive bearing friction, momentum saturation, and gimbal lock. The Correlated Electromagnetic Levitation Actuator (CELA) advances the state of the art of reaction sphere ACSs by employing the concept of correlated magnetics. It is a frictionless, direct-drive reaction sphere that harnesses a unique technology with an array of applications across multiple disciplines. Correlated electromagnets function in a manner that is analogous to a matched filter; the convolution of two signals is peaked at the index representing the greatest match. For CELA, the signals are the patterns of magnetic flux density as a function of position. The magnitude of the convolution equates to an attractive or repulsive force, and these forces can be azimuthal or radial. The development of CELA is based in four distinct disciplines: Advanced Manufacturing, Prototype Development, Electromagnetic Modeling, and Controls. We are developing novel manufacturing techniques required to build arrays of permanent and electromagnet dipoles on curved surfaces. To print the permanent magnetic array, we have developed a probe with pyramidal magnets that will reside on a robotic arm to induce localized magnetic fields on a surface. We have also used high temperature ovens to erase dipole patterns from a permanent magnet by heating the surface to its Curie temperature. A number of test articles and prototypes have been developed using additive manufacturing methods. These prototypes have included hemispherical motors to test the drive algorithm, and a levitation test bed that demonstrates a magnetic bearing method based on attractive magnetic forces and ratiometric Hall effect sensors. We developed an array of electromagnetic dipoles on a printed circuit board (PCB) with individual H-bridges controlling each coil. This device created various flux density patterns and we measured their magnetic fields using a custom Hall effect 3-D probe and a LabVIEW virtual instrument. These data will serve as a benchmark for characterizing the accuracy of future models. Current work is focused on modeling the magnetic fields of our prototype arrays using COMSOL finite element analysis (FEA) and verifying the model against our test data. Accurate modeling will allow us to quickly test new patterns of electromagnets and their macro behavior. Eventually, the magnetic field models will be implemented in our controls simulations to facilitate precise control of the reaction sphere. Initial model results agree with field measurements to within 1 G (5% of measured flux density). Currently, we are testing different material properties of the electromagnets and their magnetic fields and thermal effects. These results will be used to refine the design of the electromagnetic dipoles. Our control efforts have centered on developing commutation, levitation, and field pattern shaping hardware in the form of breadboards and PCBs with software running on a local microcontroller. In addition, our partners developed MATLAB Simulink models to demonstrate a PID controller that mitigates disturbance forces resulting from the interaction of drive and levitation magnetics. Finally, we have designed a three-axis test stand that will be used in future work to demonstrate CELA’s orientation control capability.

reaction sphere↗

Implementation of Field-Oriented Control in Joint Actuator Electronics for Satellite-Servicing Robotics

NASA’s OSAM-1 (On-orbit Servicing, Assembly, and Manufacturing 1) is a robotic spacecraft designed to extend the life of a satellite. Launching in 2026, the OSAM-1 servicer will use a robotic arm to grasp, refuel, and relocate Landsat 7. In order to accomplish the various servicing operations, including the critical auto-grapple capturing operation, the robot arm uses active compliance and visual servo control loops. These sophisticated control algorithms are enabled by the high performance Joint Control Boards (JCBs). At the core of the robot arm control architecture, the JCBs employ field-oriented control (FOC) to accurately commutate and efficiently control joint actuator torque. FOC offers numerous benefits over other current control methods, allowing the JCBs to achieve the high bandwidth and performance required by the outer control loops. As an added benefit, a torque feed-forward term allows the FOC loop to simulate microgravity actuator performance during ground testing. In this paper, a FOC implementation for space robotics applications and an end-to-end actuator calibration process are discussed.

Sam Zhao↗

Electrical Ground Support Equipment for the Sampling Caching System of the Mars 2020 Rover

In this work we describe in detail the architecture, design, testing and operation of the Electrical Ground Support Equipment (EGSE) “Blue Box” used to test and validate the Sampling Caching System (SCS) of the Mars 2020 Perseverance rover. The Blue Box architecture is centered around COTS motor controllers and COTS input-output modules communicating over an EtherCAT bus. A custom, low-level safety subsystem ensures no harm can be done to the flight articles. The modular architecture of the EGSE reduces cost and complexity while expediting assembly time. The Blue Box drives the 19 actuators of the SCS which span the main robotic arm, the corer system, the internal sample handling arm, the sample tube sealing system and the gas dust removal tool; mimicking the Rover Motor Control Assembly (RMCA). Due to the limited availability of RMCA’s, the EGSE enabled and performed the bulk of testing activities for SCS. The majority of the SCS actuators are composed of a 3-phase DC brushless motors, hall sensors for commutation, dual resolvers for output angular measurement, brakes, heaters and platinum thermistors. Additionally, the EGSE read 12 strain gauges forming part of a force torque sensor, and switches used for external positioning references. Over the 3-year span of the V&V campaign for the SCS, over 32 EGSE systems were built, tested and deployed to test venues at JPL and externally. The EGSE tested several families of the SCS subsystem, ranging from engineering units, life test units and two flight units. Test venues that this EGSE supported included lab benches, ultra-clean cleanrooms, ATLO facilities, and thermal vacuum chambers. Together with the test software systems, SSDEV and SSDEV-ECAT, the Blue Box EGSE enabled the team to efficiently test flight hardware and flight software together. We go over the safety features and fault management techniques employed to protect flight hardware. The effects of the long, 50-feet, EGSE harnesses on motor performance, EMI, electrical noise, and motor control performance are explained. Mitigations to these unwanted effects, including shielding strategy and inductance compensation, are summarized. We go over an excerpt of notable anomalies that this EGSE suffered through its operation, along with investigations and resolutions. Lessons learned, areas of improvement as part of future work, and recommendations for future implementations for similar EGSE’s, are shared.

Levine, Dan↗

Human Factors Research Considerations for Terminal Area Urban Air Mobility Operations

In this presentation, we discuss the human factors research challenges from introducing greater levels of automation in a future air transportation concept called Urban Air Mobility (UAM). UAM is an air transportation concept that aims to provide air transportation services to the daily commuter, as well as emergency response and package delivery. The principal innovation over current day large air transport system is the greater distribution of important safety functions to automated and human agents; these functions include air traffic management, traditionally an air traffic controller responsibility. A central aspect of UAM is the development of an automated air traffic manager, whose primary responsibility is to approve airspace access for vehicle operators. Vehicle operator roles may include onboard and remote pilots, as well as a human manager who will supervise an entire fleet. Alternatively, both fleet manager and vehicle operators can be merged into a single role – a feasible option if UAM aircraft are autonomous. In lieu of tower controllers, vertiport managers, with the assistance of automation, will manage arrival and departure schedules between vertiports, as well as supervise surface operations. Our approach here will be to introduce use cases currently being developed by NASA, and then provide preliminary definitions for each of the roles introduced above and how coordination between them can be configured to support the operations within the use cases described. Subsequently, we review the tools and interfaces being developed to support the various roles. To conclude, we present current human factors work related to defining the roles above and suggest future work to advance the UAM concept.

trial planning↗

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↗

Exploring Ridesharing in Passenger Urban Air Mobility: A Comparative Analysis

There is growing interest in urban air mobility (UAM) as an alternative for passenger and cargo transport around metropolitan areas in a multimodal transportation system that leverages small, electric aircraft. Ridesharing has been proposed as a means of making UAM passenger trips more affordable and environmentally friendly. We present a UAM ridesharing model integrated into an existing computational framework for analyzing daily work commute trips within a metropolitan area. We leverage this model to estimate the potential demand for ridesharing-enabled UAM trips within six metropolitan areas across the United States: Chicago, IL; Cleveland, OH; Dallas, TX; Denver, CO; New York City, NY; and Orlando, FL. We compare results for each metropolitan area with and without ridesharing. Results indicate that ridesharing enables at least an order of magnitude more UAM-preferring passengers than without ridesharing, though specifics vary across metropolitan areas and network sizes. Enabling ridesharing in UAM also considerably lowers the mean and mode value of time for passengers that select the UAM mode, indicating that ridesharing can help make UAM more economically accessible to a larger set of the population. An important caveat is that the UAM ridesharing model does not account for operational constraints, such as aerodrome capacity and aircraft availability, and relies on a perfect knowledge of passenger movements and mode preferences. This leads to high UAM ridesharing volumes that are unlikely to reflect real-world UAM operations and thus serves as an upper bound estimate.

advanced air mobility↗

Exploring Ridesharing in Passenger Urban Air Mobility: A Comparative Analysis

There is growing interest in urban air mobility (UAM) as an alternative for passenger and cargo transport around metropolitan areas in a multimodal transportation system that leverages small, electric aircraft. Ridesharing has been proposed as a means of making UAM passenger trips more affordable and environmentally friendly. We present a UAM ridesharing model integrated into an existing computational framework for analyzing daily work commute trips within a metropolitan area. We leverage this model to estimate the potential demand for ridesharing-enabled UAM trips within six metropolitan areas across the United States: Chicago, IL; Cleveland, OH; Dallas, TX; Denver, CO; New York City, NY; and Orlando, FL. We compare results for each metropolitan area with and without ridesharing. Results indicate that ridesharing enables at least an order of magnitude more UAM-preferring passengers than without ridesharing, though specifics vary across metropolitan areas and network sizes. Enabling ridesharing in UAM also considerably lowers the mean and mode value of time for passengers that select the UAM mode, indicating that ridesharing can help make UAM more economically accessible to a larger set of the population. An important caveat is that the UAM ridesharing model does not account for operational constraints, such as aerodrome capacity and aircraft availability, and relies on a perfect knowledge of passenger movements and mode preferences. This leads to high UAM ridesharing volumes that are unlikely to reflect real-world UAM operations and thus serves as an upper bound estimate.

advanced air mobility↗