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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Flying Qualities Analysis and Piloted Simulation Testing of a Lift+Cruise Vehicle with Propulsion Failures in Hover and Low-Speed Conditions

The recent emergence of electric-Vertical Take-Off and Landing (eVTOL) vehicles for Urban Air Mobility (UAM) applications has resulted in a wide variety of configurations with unique stability and control characteristics. NASA is currently conducting research to develop conceptual design tools to accelerate public acceptance of these vehicles which includes requirements for safety during failure scenarios. This paper summarizes progress toward a toolbox for predicting flying qualities of eVTOL vehicles during critical propulsion failures that could impact the allowable design of the vehicle geometry or control system. Key topics include unique vulnerabilities of eVTOL/multirotor vehicles to propulsion failures, relevant flying qualities design metrics, and simulation modeling requirements for assessing flying qualities degradation due to failures. Results of a piloted simulation study conducted in the NASA Ames Vertical Motion Simulator (VMS) are presented. The VMS experiment was designed to assess and validate key handling qualities and safety design metrics for propulsion failures. These results show the correlation between control system design requirements and the degradation in handling qualities for various propulsion failures.

George Altamirano↗
NASA NTRSDate not supplied

Remotely Administered Psychoacoustic Test for sUAS Noise to Gauge Feasibility of Remote UAM Noise Study

The National Aeronautics and Space Administration (NASA) remotely administered a psychoacoustic test in fall of 2022 as the first of two phases of a cooperative Urban Air Mobility (UAM) vehicle noise human response study. The first phase, the Feasibility Test, described in this paper, determined the feasibility of the remote test method, in contrast to a previous in-person psychoacoustic test that found an annoyance response difference between small unmanned aerial system (sUAS) noise and ground vehicle noise. This paper discusses the Feasibility Test online layout, sound calibration method, remote test software development, stimuli selection, test subject recruitment, and test administration. Test performance is measured through comparison of annoyance response data with the previous in-person test results. The paper also investigates if providing a contextual cue to test subjects influenced their annoyance response. Response differences between test subjects in geographically distinct areas are analyzed. Administrative challenges that were encountered during the test are discussed. The second phase of this study, the implementation phase, will use a remote (web-based) test method and leverage the cooperation of multiple government agencies, academia, and industry to gain human response insights from a wide range of UAM vehicle sounds that would be challenging for a single organization to acquire. Improvements to administering a remote test for the implementation phase of the UAM vehicle noise human response study are recommended.

Remote Psychoacoustic Test↗
NASA NTRSDate not supplied

Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

This paper presents an integration of Differential Dynamic Programming (DDP) with the Optimal Reciprocal Collision Avoidance (ORCA) algorithm as the basis for a new algorithm, titled Combined Bernstein Polynomial Optimal Reciprocal Collision Avoidance DDP (COBRA-DDP), for trajectory replanning and collision avoidance for Urban Air Mobility (UAM) vehicles. State-constrained variants of DDP provide the ability to plan trajectories while avoiding obstacles, but these methods require a large increase in computational time per iteration which hinders the overall speed of the algorithm. ORCA utilizes simplified dynamics to recognize potential collisions along a trajectory and provides an optimal velocity for the avoidance of multiple vehicles. These velocity commands, however, may not result in a dynamically feasible trajectory for DDP to plan around. As such, a Bernstein polynomial curve that considers the general dynamic constraints of the vehicle is generated to approximate a trajectory based on the velocity commands. COBRA-DDP optimizes this suggested trajectory via unconstrained DDP to provide a dynamically feasible trajectory that provides collision avoidance. This new trajectory can be applied to the vehicle or used to warm start the state constrained DDP algorithms to decrease computation time. Its benefits and effectiveness of the algorithm are demonstrated on a UAM Vertical Takeoff and Landing (VTOL) vehicle simulation with highly nonlinear dynamics.

Optimal Reciprocal Collision Avoidance↗
NASA NTRSDate not supplied

Remotely Administered Psychoacoustic Test for sUAS Noise to Gauge Feasibility of Remote UAM Noise Study

The National Aeronautics and Space Administration (NASA) remotely administered a psychoacoustic test in fall of 2022 as the first of two phases of a cooperative Urban Air Mobility (UAM) vehicle noise human response study. The first phase, the Feasibility Test, described in this paper, determined the feasibility of the remote test method, in contrast to a previous in-person psychoacoustic test that found an annoyance response difference between small unmanned aerial system (sUAS) noise and ground vehicle noise. This paper discusses the Feasibility Test online layout, sound calibration method, remote test software development, stimuli selection, test subject recruitment, and test administration. Test performance is measured through comparison of annoyance response data with the previous in-person test results. The paper also investigates if providing a contextual cue to test subjects influenced their annoyance response. Response differences between test subjects in geographically distinct areas are analyzed. Administrative challenges that were encountered during the test are discussed. The second phase of this study, the implementation phase, will use a remote (web-based) test method and leverage the cooperation of multiple government agencies, academia, and industry to gain human response insights from a wide range of UAM vehicle sounds that would be challenging for a single organization to acquire. Improvements to administering a remote test for the implementation phase of the UAM vehicle noise human response study are recommended.

Remote Psychoacoustic Test↗
NASA NTRS2019

Multidisciplinary Optimization of a Turboelectric Tiltwing Urban Air Mobility Aircraft

Urban air taxis, also known as urban air mobility (UAM) vehicles, are anticipated to be an area of significant market growth in the near future. These vehicles are typically vertical take-off and landing (VTOL) designs which are capable of carrying 1 to 30 passengers in an intra-urban environment with flights of less than 50 nautical miles. Development of UAM vehicles and their integration into the airspace will be enabled by advancements in a number of areas including electrified propulsion systems, structures, acoustics, automation, and controls. However, the strong multidisciplinary interactions for these unique vehicles presents a significant new design challenge. This work describes the development of a multidisciplinary analysis and optimization environment which can be used to support the conceptual design of these UAM vehicles, using efficient gradient based optimization with analytic derivatives. The tools included in this multidisciplinary analysis model the aircraft trajectory, vehicle aerodynamics, structures, and electrified propulsion system. The multidisciplinary environment created in this research is unique in that all the physics tools are tightly integrated together, with the trajectory model directly calling the aerodynamics, structures, and propulsion models. This multidisciplinary analysis environment is then demonstrated in the design optimization of a turboelectric tiltwing UAM vehicle concept.

Hendricks, Eric S.↗
NASA NTRSDate not supplied

A Synthesis Method to Auralize Rotor Noise During Transitional Flight

This paper describes a new capability to synthesize Urban Air Mobility (UAM) vehicle rotor/propeller loading and thickness noise and broadband self noise for transitional flight auralization. A vehicle smoothly transitioning between flight states is approximated here as transitioning in time through a series of trimmed steady-state flight conditions. To generate information that helps synthesize loading and thickness noise for transitional flight, this paper describes the development of a tool that combines blade loading, motion, and geometry data from a series of separate trimmed flight states. This paper also describes a method to combine broadband self noise acoustic predictions, each representing a separate trimmed flight state, to synthesize broadband self noise for transitional flight. Different flight profiles of the six-passenger NASA UAM Quadrotor reference vehicle demonstrate these capabilities, with each profile specified by a series of trimmed flight states.

Auralization↗
NASA NTRSDate not supplied

The AIRNOISE-UAM Tool and its Application to ATM-X

The noise disruption caused by Urban Air Mobility (UAM) vehicles will be a major factor in public acceptance of UAM. The noise exposure caused by fixed-wing aircraft and helicopters is predicted using Aviation Environment and Design Tool (AEDT) software at the airport. The base noise is calculated by interpolation or extrapolation of Noise-Power-Distance (NPD) database in the AEDT. In this presentation, a new noise prediction tool "AIRNOISE-UAM" is developed with a new NPD database for eVTOL vehciles in collaboration with a RVLT team. The noise exposure results have been verified with those from AEDT. Lastly, we demonstrate two use cases of AIRNOISE-UAM to the ATM-X project. The first use case is to develop noise exposure maps for FAA UAM compliance planning. The sceond use case is to develop noise-aware flight route planning algorithm.

Urban Air Mobility↗
NASA NTRS2022

Scheduling For Urban Air Mobility Using Safe Learning

This work considers the scheduling problem for Urban Air Mobility (UAM) vehicles travelling between origin-destination pairs with both hard and soft trip deadlines. Each route is described by a discrete probability distribution over trip completion times (or delay) and over interarrival times of requests (or demand) for the route along with a fixed hard or soft deadline. Soft deadlines carry a cost that is incurred when the deadline is missed. An online, safe scheduler is developed that ensures that hard deadlines are never missed and that average cost of missing soft deadlines is minimized. The system is modelled as a Markov Decision Process (MDP) and safe model based learning is used to find the probabilistic distributions over route delays and demand. Monte Carlo Tree Search (MCTS) Earliest Deadline First (EDF) is used to safely explore the learned models in an online fashion and develop a near-optimal non-preemptive scheduling policy. These results are compared with Value Iteration (VI) and MCTS (Random) scheduling solutions.

Urban Air Mobility↗
NASA NTRSDate not supplied

Scheduling for Urban Air Mobility using Safe Learning

This work considers the scheduling problem for Urban Air Mobility (UAM) vehicles travelling between origin-destination pairs with both hard and soft trip deadlines. Each route is described by a discrete probability distribution over trip completion times (or delay) and over interarrival times of requests (or demand) for the route along with a fixed hard or soft deadline. Soft deadlines carry a cost that is incurred when the deadline is missed. An online, safe scheduler is developed that ensures that hard deadlines are never missed and that average cost of missing soft deadlines is minimized. The system is modelled as a Markov Decision Process (MDP) and safe model based learning is used to find the probabilistic distributions over route delays and demand. Monte Carlo Tree Search (MCTS) Earliest Deadline First (EDF) is used to safely explore the learned models in an online fashion and develop a near-optimal non-preemptive scheduling policy. These results are compared with Value Iteration (VI) and MCTS (Random) scheduling solutions.

Urban Air Mobility↗
NASA NTRSDate not supplied

Uncertainty Propagation in Pre-Flight Prediction of Unmanned Aerial Vehicle Separation Violation

Current forecasts on the future of aeronautics suggest an in- creasing number of unmanned aerial vehicles entering the low- altitude airspace in the next decades (FAA, 2018; Kopardekar et al., 2016). Small vehicles for package delivery as well as larger vehicles for urban air mobility will change the airspace drastically, increasing density of operations both in time, i.e. high number of take-off and landings per unit time, and in space, operating in dense urban environment. This scenario poses challenges to the current approach to air traffic control, and large efforts from academia, industry and regulatory bodies are dedicated to the development of new traffic management strategies that leverage higher computing and simulating capabilities available today. In this paper, we propose a simple look-ahead approach to predict potential minimum separation violations at the strategic level, that is before vehicles start flying, depending on the predefined 4D trajectories and uncertainty affecting the wind acting along those routes. The wind field is extracted from the NOAA North America Mesoscale Forecast System and interpolated using Gaussian process regression, while uncertainty affecting the expected cruise airspeed is propagated through error intervals. The approach allows the prediction of aircraft separation as a function of time, highlighting potential safety violations that would go undetected if uncertainty affecting the expected 4D trajectories is not considered. The paper will also discuss issues related to accuracy and scalability of the approach to multiple vehicle operations.

Trajectory Prediction↗
NASA NTRSDate not supplied

A Preliminary Development of The Intelligent Change Detection System (ICDS): Using Machine Learning to Combat Change Blindness in Remote Operation Environments

The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).

Real-Time Streaming Data Architecture↗
NASA NTRSDate not supplied

A Preliminary Development of The Intelligent Change Detection System (ICDS): Using Machine Learning to Combat Change Blindness in Remote Operation Environments

The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).

Real-Time Streaming Data Architecture↗
NASA NTRSDate not supplied

Evaluation of Heave Disturbance Rejection and Control Response Criteria on the Handling Qualities Evaluation of Urban Air Mobility (UAM) eVTOL Quadrotors Using the Vertical Motion Simulator

The first piloted handling qualities study of an urban air mobility (UAM) vehicle leveraging the Vertical Motion Simulator (VMS) at NASA Ames Research Center was conducted in Spring 2021. The VMS provides a unique capability to reduce risk by assessing and iterating control designs. Minimal sources currently exist to provide performance and handling qualities data for large, rotor speed-controlled vehicles outside of the software environment. The study compares multiple handling qualities performance configurations for rotor speed and blade pitch-controlled variants of a six-passenger quadrotor conceptual design model developed by the NASA Revolutionary Vertical Lift Technology (RVLT) Project. Additionally, both ADS-33 and a tailored set of performance standards (notionally representing the agility required of a UAM mission) are examined under conditions with and without light turbulence. Preliminary results did show significant variation in ratings based on the set of standards utilized, controller tuning to either Level 1 or boundary Level 1/ Level 2 conditions, and presence or lack of turbulence. A custom approach and landing maneuver was also designed to bring these evaluation tasks together in a more comprehensive application.

Handling Qualities↗
NASA NTRS2022

RVLT Concept Vehicle Powertrain Arrangement Study and Candidate Powertrain System Test Arrangements

This work was motivated by the vision of the NASA’s Revolutionary Vertical Lift Technology (RVLT) Project and project goals to support the Urban Air Mobility mission. A RVLT concept vehicle, namely the side-by-side helicopter with hybrid electric propulsion, was selected to conduct a powertrain study. The specific objectives of this work were to explore powertrain designs for the RVLT side by side hybrid electric concept vehicle to assess powertrain configurations, and in the process identify general trends for design tradeoffs, technology barriers, and research needs. A notional powertrain for the vehicle was created, and this led to identifying some mechanical components for development and testing. Three powertrain component concepts designs were created, namely a pericyclic drive mast gearbox, a control clutch, and an overrunning cutch. The design approach and evolution are documented. A universal combining gearbox was conceived and designed that would extend the capability of a NASA test facility for testing and demonstration of technologies for urban air mobility vehicle powertrains. Candidate powertrain test arrangements as enabled by the proposed universal combining gearbox are explained and depicted.

gears↗
NASA NTRSDate not supplied

An Overview of the Proprotor Performance Test in the 14-­ by 22­-Foot Subsonic Tunnel

This work experimentally investigates the aerodynamic behavior of proprotors across a wide range of angles of attack. These flight conditions are intended to be representative of Urban Air Mobility (UAM) vehicle platforms that utilize articulating propulsors to transition from a vertical takeoff and landing (VTOL) phase typical of a conventional rotor­craft, to an axial mode of forward flight typical of a fixed-­wing aircraft. These data are used to identify the potential limits of lower­ fidelity aerodynamic modeling tools, as well as to inform future acoustic phases of testing. Tests were conducted on two proprotor designs in the NASA Langley 14­- by 22­-Foot Subsonic Tunnel using an articulating propeller test stand. Hover results identified unique flow physics on one of the proprotors, including severe outboard flow separation and perpendicular blade vortex interactions on the outboard portions of the blades. Transition and forward flight conditions yielded very informative trends in terms of both on-­ and off­-axis forces and moments against which low-­fidelity prediction models were compared.

aerodynamics↗
DOE OSTI2024

Battery Electrolyte Design for Electric Vertical Takeoff and Landing (eVTOL) Platforms

Here, the development of robust and high-performance battery systems is crucial for the advancement of Electric Vertical Takeoff and Landing (eVTOL) vehicles for urban air mobility. This study evaluates the performance of different lithium-ion battery chemistries under Electric Vertical Takeoff and Landing (eVTOL) load profiles. The actual flight data coupled with physical models is used to create discharge profiles for testing on developed lithium-ion cells for eVTOLs. The performance of a standard liquid electrolyte (1.2 M LiPF 6 in EC:EMC), labeled Gen-2, is benchmarked and compared with a fast-charging electrolyte (1.2 M LiFSI in EC:EMC), labeled XFC. Cell analysis involves the use of various techniques, such as impedance spectroscopy, polarization curves, and capacity retention measurements. Capacity retention is stable for both systems over 500 cycles, but unique discharge capacity trends are observed for different mission segments. During the initial takeoff hover stages, Gen-2 electrolytes experience substantial voltage fade, while XFC electrolytes maintain consistent behavior. In general, the Gen-2 electrolyte demonstrated lower discharge overpotentials and higher decay during cycling compared to the XFC electrolyte. This work highlights the complexity of eVTOL battery behavior and provides insights into battery system design, contributing to the advancement of battery energy storage solutions for urban air mobility.

25 ENERGY STORAGE↗
NASA NTRS2019

Gradient-Based Propeller Optimization with Acoustic Constraints

Urban Air Mobility (UAM) vehicles are intended to operate near or within large cities, where a significant portion of the public will be exposed to the noise they create. If these vehicles are to become acceptable to the public, designers must be able to manage the amount of noise they generate, and understand the relationship between traditional performance metrics (thrust, efficiency, etc.) and noise. As a first step to addressing this need, this work combines a Blade Element Momentum Theory tool (OpenBEMT) with an acoustic prediction tool (ANOPP2) to optimize a propeller subject to both aerodynamic and acoustic constraints. These tools are developed within a optimization framework (OpenMDAO (Multidisciplinary Design Analysis Optimization)) that allows analytic derivatives to be propagated through the models and passed to a gradient-based optimizer. This tool chain is exercised on the cruise propellers from the X-57 Maxwell, and yields propeller designs that reduced the overall sound pressure level by about 8 decibels for a cost of 3 percent propeller efficiency.

Acoustics↗
NASA NTRS2021

Fit2Fly Project

NASA’s Fit2Fly project wants to make future commercial drone fleet operations routine, safe, and boring. How can future operators of commercial drone fleets know without a doubt that their aircraft are fit to fly? It is a tough problem, because every flight will effectively break the chain of custody for their aircraft, and having technicians do detailed inspections after each flight is not viable for large, busy fleets.

airworthiness↗