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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Wind Tunnel Testing Techniques for a Tandem Tilt-Wing, Distributed Electric Propulsion VTOL Aircraft

Urban Air Mobility (UAM) vertical takeoff and landing (VTOL) aircraftdesigns frequently include multiple distributed propulsors, complex wing-propulsor aerodynamics, significant airframe configuration changes during normal flight operations, and no historical database regarding the best ways to transition between vertical and horizontal flight. This paper describes the methodology used for wind tunnel testing of the Langley Aerodrome No. 8 (LA-8) in the NASA Langley 12-Foot Low-SpeedTunnel during multiple test entries in 2019 and2020. The LA-8 is a tandem tilt-wing aircraft with 4 motor-propellerunits and 4 control surfaces distributed across each wing, plus an inverted V-tail with 2 ruddervators on the fuselage. An initial tunnel entryused one-factor-at-a-time (OFAT) testing to (1) define candidate trimmed transition corridors between vertical and horizontal flight, (2) assess whether there was adequate control authority, and (3) define appropriatetest factor ranges for subsequent design of experiment (DOE) wind tunnel testing. The total number of independent variables for these wind tunnel tests (23) made DOE testing an efficient option for assessing the large number of potential interactions associated with the LA-8. The general advantages and disadvantages of OFAT and DOE wind tunnel testing techniques are also discussed –along with the benefits of a combined approach

wind tunnel research techniques↗
NASA NTRSDate not supplied

Dynamic Vehicle Assessment for Intelligent Contingency Management for Urban Air Mobility Vehicles

New algorithms will be required to ensure passenger and bystander safety during the expected era of autonomous urban air mobility (UAM) aircraft. This paper examines an approach for assessing the vehicle capability to fly itself and to complete a mission safely. The concepts combine elements of system identification, adaptive control, flight dynamics, envelope predictions, and handling qualities, as well as human pilot intuition. The approach is applied to a simulation of a generic distributed electric propulsion urban air mobility-type aircraft, which was developed under the NASA Transformational Tools and Technologies (TTT) project, Autonomous Systems / Intelligent Contingency Management subproject.

flight envelope prediction↗
NASA NTRS2021

Thermal Management System Design for Electrified Aircraft Propulsion Concepts

This paper describes the development of thermal management systems (TMS) for three electrified aircraft propulsion (EAP) vehicle concepts released by NASA that span the UAM, regional, and single-aisle markets. For each EAP concept, a conventional TMS is designed for two electric component technology levels: state of the art and advanced. The goals for the paper are to compare the TMS designs for the above EAP concepts, to study how changes in requirements affect the TMS subcomponents, and to develop generalized TMS sizing relations. Each conventional TMS concept utilizes a liquid-based cooling methodology and is designed to cool the EAP electrical components only. The design parameters considered in this study include TMS architecture variation due to differing vehicle cooling requirements, electrical component efficiencies, vehicle total fuel burn or energy consumption, and electrical component operating temperatures. Results show that cooling components with low temperature limits increases TMS weight and demonstrate that efficiency gains of the specific technologies can net a lower weight TMS system despite more stringent temperature limits.

Thermal management system↗
NASA NTRS2021

ATTRACTOR: Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability

Autonomous systems (AS) are crucial to realizing the vision of new, complex transportation modes, such as advanced air mobility (AAM) and urban air mobility (UAM). A chief barrier to induction of AS into aviation is insufficient understanding of AS reliability in time-critical and safety-critical environments—an obstacle to certification. ATTRACTOR is aimed at building a basis for certification of classes of autonomous cyber-physical-human systems (CPHS) via establishing metrics and models of trustworthiness and trust in multi-agent team interactions, analyzable trajectories, explainability of computational algorithms (explainable artificial intelligence, or XAI), and persistent modeling and simulation, in the context of missions planning and operation. By “building a basis for certification,” we mean acquiring an understanding of when a system is trustworthy and developing computable means to estimate trustworthiness and trust in order to eventually inform functional requirements that contribute to certification. The outcomes are applicable not just to aviation but to all domains that rely on autonomous systems.

Autonomy↗
NASA NTRSDate not supplied

Webinar on Urban Air Mobility Vision: Sky For All

The webinar will highlight the role UAM can play in future mobility improvements to enhance lives of people living in urban environments. In addition, challenges of integrating these vehicles into the current airspace will be discussed. NASA will present how these questions are being addressed from a US perspective.

Urban Air Mobility↗
NASA NTRS2021

Revolutionary Vertical Lift Technology (RVLT) Side-By-Side Hybrid Concept Vehicle Powertrain Dynamic Model

The Side-by-Side (SBS) Hybrid is one of several Revolutionary Vertical Lift Technology (RVLT) concept aircraft identified by NASA to investigate Urban Air Mobility (UAM) requirements. This paper presents a dynamic model of the SBS Hybrid powertrain built using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) and the Electrical Modeling and Thermal Analysis Toolbox (EMTAT). The model consists of the rotors, electrical power system, and turboshaft engines connected through freewheeling clutches, gearboxes, and multiple shafts. This research effort models the complex behavior of the powertrain, including the operation of the freewheeling clutches and electrical power system at the simulation time scale of the shaft dynamics. Several simulations highlight the key features present in the model and demonstrate its operation.

Powertrain↗
NASA NTRSDate not supplied

Impact of Handling Qualities on Motor Sizing for Multirotor Aircraft with Urban Air Mobility Missions

Control models of three NASA Urban Air Mobility (UAM) reference vehicles (the quadrotor, octocopter, and Lift+Cruise (LPC)) were created and compared to determine the effect of rotor number and disk loading on control margin and design. The heave and yaw axes demand more actuator usage than the roll and pitch axes. Between heave and yaw, heave was the more demanding of the two because of the dependence of heave on the engine speed controller (ESC). When the feedback gains for all three vehicles were optimized to Level 1 handling qualities (HQs) specifications using CONDUIT, the ESC for the octocopter was the most stable and had the highest rise time (time for the rotor to respond to an input), while the LPC ESC was the least stable and had the smallest rise time. Rise time corresponds to the time required for rotor response. When actuator usage was translated to current margin, torque margin, and power margin, heave was the most demanding axis, followed by yaw, roll, and then pitch for all three vehicles. The results emphasize the importance of an accurate motor model within the control system architecture.

Impact↗
NASA NTRS2021

Noise Measurements from Ground Tests of the Moog SureFly Vehicle

Noise measurements from a ground test of a small vertical lift research vehicle are presented. The proof-of-concept all-electric vehicle called “SureFly” was developed by Moog, Inc. A cooperative effort between NASA and Moog, Inc. has led to one of the first acoustic test datasets from an Urban Air Mobility (UAM) vehicle being developed for passenger and cargo. Results show propeller and possibly motor tones are important for the overall noise levels. The vehicle has four support arms each with a pair of contra-rotating propellers. Noise measurements show higher noise levels from the lower propellers, likely due to inflow distortion from the arms and top propellers. Possible motor noise was identified by calculating harmonics of the line frequency and comparing to the tones in the narrowband acoustic spectra and phased microphone array data. The acoustic far field was found to be about 100 ft away from the vehicle, but additional microphones are needed to provide a better assessment. Results show the presence of modulation for some test conditions. The work reported here is only for ground tests.

Acoustics↗
NASA NTRSDate not supplied

Noise Measurements from Ground Tests of the Moog SureFly Vehicle

Noise measurements from a ground test of a small vertical lift research vehicle are presented. The proof-of-concept all-electric vehicle called “SureFly” was developed by Moog, Inc. A cooperative effort between NASA and Moog, Inc. has led to one of the first acoustic test datasets from an Urban Air Mobility (UAM) vehicle being developed for passenger and cargo. Results show propeller and possibly motor tones are important for the overall noise levels. The vehicle has four support arms each with a pair of contra-rotating propellers. Noise measurements show higher noise levels from the lower propellers, likely due to inflow distortion from the arms and top propellers. Possible motor noise was identified by calculating harmonics of the line frequency and comparing to the tones in the narrowband acoustic spectra and phased microphone array data. The acoustic far field was found to be about 100 feet away from the vehicle, but additional microphones are needed to provide a better assessment. Results show the presence of modulation for some test conditions. The work reported here is only for ground tests.

Acoustics↗
NASA NTRSDate not supplied

Defining Services, Functions, and Capabilities for an Advanced Air Mobility (AAM) In-time Aviation Safety Management System (IASMS)

NASA’s vision for Advanced Air Mobility (AAM) Mission is to help emerging aviation markets to safely develop an air transportation system that moves people and cargo between places previously not served or underserved by aviation. The integration of new operational paradigms and vehicle classes in this system requires a transformation of the National Airspace System (NAS) that includes substantive changes critical for assuring safety. These changes are compelled by unique challenges posed by AAM to the safety management system (SMS). These challenges were assessed by committees of the National Academies in their reports on a vision for an In-time Aviation Safety Management System (IASMS) and a blueprint for AAM [1,2]. In their description of an IASMS, the top recommendation was development of a concept of operations (ConOps) for IASMS. This paper describes the high-priority recommendations from the National Academies for its IASMS vision and how they are addressed through a distributed system-of-systems architecture. The IASMS architecture is structured on the services, functions, and capabilities (SFCs) necessary for In-time System-wide Safety Assurance (ISSA)initially developed for urban air mobility (UAM). The paper then posits where these SFCs would reside across vehicles, airspace, or service suppliers such as Supplemental Data Service Providers (SDSPs), and how SFCs scale with increasing complexity in design and operations of AAM. SFCs are foundational building blocks for a system that targets an individual or family of risks using a Monitor-Assess-Mitigate risk paradigm for anomalies, precursors and trends. An IASMS could be conceived that uses a portfolio of SFCs for AAM in general or prioritizes SFCs for a specific domain or operation.

K Ellis↗
NASA NTRSDate not supplied

Power Quality Analysis for a High Voltage Power System for Urban Air Mobility Application

Maturation of electric power technologies has opened the door for deployment of new types of aircraft within urban air mobility (UAM) markets. These new types of aircraft use non-conventional designs, which do not fall within existing regulatory requirements; this is especially true for the design and verification of the high voltage primary power systems which are being proposed for many of these aircraft. The purpose of this paper is to investigate and inform integration requirements, mainly related to power quality, based on a point design of a NASA Lift-plus-Cruise Vehicle Electrical Power System (EPS) and Utilization Equipment (UE). The results will be used to inform normal and abnormal operating performance of the EPS and UE for future standards in regards to Power Quality.

Nuha S Nawash↗
NASA NTRS2021

Revolutionary Vertical Lift Technology (RVLT) Side-By-Side Hybrid Concept Vehicle Powertrain Dynamic Model

The Side-by-Side (SBS) Hybrid is one of several Revolutionary Vertical Lift Technology (RVLT) concept aircraft identified by NASA to investigate Urban Air Mobility (UAM) requirements. This paper presents a dynamic model of the SBS Hybrid powertrain built using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) and the Electrical Modeling and Thermal Analysis Toolbox (EMTAT). The model consists of the rotors, electrical power system, and turboshaft engines connected through freewheeling clutches, gearboxes, and multiple shafts. This research effort models the complex behavior of the powertrain, including the operation of the freewheeling clutches and electrical power system at the simulation time scale of the shaft dynamics. Several simulations highlight the key features present in the model and demonstrate its operation.

powertrain↗
NASA NTRSDate not supplied

Dynamic Spectrum Allocation in Urban Air Transportation System via Deep Reinforcement Learning

The emerging concepts of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM) open a new paradigm for urban air transportation. A big challenge is that these new aerial vehicles will quickly saturate the already crowded aviation spectrum, which is an essential resource to ensure reliable communications for safe operations. In this paper, we consider an air transportation system where multiple aerial vehicles are operated to transport passengers or cargo from different sources to destinations along their pre-defined paths. During the flight, the minimum communication Quality of Service (QoS) requirement must be achieved to ensure flight safety. Our objective is to minimize the average mission completion time by jointly optimizing the velocity selection and spectrum allocation for all aerial vehicles. We formulate the optimization problem as a multi-stage Markov Decision Process (MDP) where the optimization variables are coupled together. A multi-agent Deep Reinforcement Learning (DRL) based solution is proposed where Value Decomposition Networks (VDN) algorithm is utilized to take discrete actions. Additionally, we propose a heuristic greedy algorithm as a baseline solution. Simulation results show that our learning based solution outperforms the heuristic greedy algorithm and another Orthogonal Multiple Access (OMA) solution in minimizing the mission completion time.

Ruixuan Han↗
NASA NTRSDate not supplied

AAM Ecosystem Aircraft Working Group: Pilot's Perspective

NASA’s Urban Air Mobility (UAM) Sub-Project is engaged in research to support the introduction of air taxis into the National Airspace System. This presentation is for an AAM Ecosystem Working Group presentation on the pilot's perspective about flying an air taxi or flying a conventional aircraft in the same airspace as an air taxi. It introduces the aircraft and operating environment and includes questions for a pilot panel and the audience.

aeronautics↗
NASA NTRSDate not supplied

Experiments for Securing Air Traffic Against Cyber-Physical System Attacks

This presentation describes experiments conducted with single board computers to investigate methods for creating trust for enabling the development of cyber-resilient air transportation systems. Methods included secure communication to prevent unauthorized access to data, consistency of data obtained via sensors and by processing, and built-in safeguards to prevent mission failure. The motivation for this work are the following. The future air transportation system needs to ensure availability, integrity, confidentiality and safety of operations. Safety of vehicles and operations is paramount for successful integration of Urban Air Mobility (UAM), Unmanned Aerial Systems (UAS), supersonic aircraft and launch vehicles with conventional aviation operations in the National Airspace System. Security is becoming critical because the sensors, networks and computers are far more vulnerable to bad actors than their mechanical or human predecessors. The goal therefore is to design and develop cyber-resilient systems that continue to function even in degraded states. The main findings are (1) off-the-shelf hardware can support development of cyber-resilient onboard flight computers and (2) trust in system design and implementation can be accomplished by integrating layers in depth (detail) and in breadth (scope).

cyber-resilient autonomy, trust, secure communicat↗
NASA NTRSDate not supplied

Cybersecurity - Host-based Intrusion Detection Systems (HIDS)

Given a set of flight trajectories, can we classify the trajectories that do not follow a normal path? By identifying abnormal trajectories, further analysis can be done to determine the reasoning for these actions. Addressing these scenarios can bring possible solutions for holding and rerouting problems when its time to incorporate UAM in the airspace.

DFR↗
NASA NTRSDate not supplied

Cluster-Based Flight Trajectory Outlier Detection

Given a set of flight trajectories, can we classify the trajectories that do not follow a normal path? By identifying abnormal trajectories, further analysis can be done to determine the reasoning for these actions. Addressing these scenarios can bring possible solutions for holding and rerouting problems when its time to incorporate UAM in the airspace.

Machine Learning↗
NASA NTRSDate not supplied

Dynamic Spectrum Allocation in Urban Air Transportation System via Deep Reinforcement Learning

The emerging concepts of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM) open a new paradigm for urban air transportation. A big challenge is that these new aerial vehicles will quickly saturate the already crowded aviation spectrum, which is an essential resource to ensure reliable communications for safe operations. In this paper, we consider an air transportation system where multiple aerial vehicles are operated to transport passengers or cargo from different sources to destinations along their pre-defined paths. During the flight, the minimum communication Quality of Service (QoS) requirement must be achieved to ensure flight safety. Our objective is to minimize the average mission completion time by jointly optimizing the velocity selection and spectrum allocation for all aerial vehicles. We formulate the optimization problem as a multi-stage Markov Decision Process (MDP) where the optimization variables are coupled together. A multi-agent Deep Reinforcement Learning (DRL) based solution is proposed where Value Decomposition Networks (VDN) algorithm is utilized to take discrete actions. Additionally, we propose a heuristic greedy algorithm as a baseline solution. Simulation results show that our learning based solution outperforms the heuristic greedy algorithm and another Orthogonal Multiple Access (OMA) solution in minimizing the mission completion time.

Ruixuan Han↗