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At least 775 records · Page 43

Simulation Studies for an Urban Air Mobility Aircraft using Hardware-In-Loop Experiments

Urban Air Mobility seeks to transport passengers, deliver cargo, and provide emergency medical transportation in major metropolitan areas. This will be accomplished with distributed electric powered vertical takeoff and landing aircraft vehicles. The low specific energy of the current generation lithium-ion battery packs limit the operational range of the electric aircraft. Limited range impacts safety by reducing the amount of time available for analyzing the potential impact of errors and failures and responding to them, and for flying to an alternative landing area or returning to the base. It is therefore critical to understand the impact of flight and environmental conditions on the onboard lithium-ion battery pack’s health. With this as the motivation, the procedure for evaluating the performance of battery packs in a laboratory setting and the results obtained using this procedure on battery packs subject to power draw characteristics of a simulated flight of a NASA conceptual quadrotor aircraft model are described. The fully charged battery is allowed to discharge at specific C-rates based on the power draw profile during the experiment, and the current and voltages are recorded as a function of time. Observed results under different operating conditions and mission profiles are discussed.

UAM↗

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS↗

Recent NASA Research into the Psychoacoustics of Urban Air Mobility Vehicles

NASA maintains multiple psychoacoustic laboratories across the United States. One focus of research in these facilities is to investigate the human reaction to the noise of notional UAM vehicles. This effort will look for answers to several questions: What does a “good” UAM sound like? What might be the impact on existing urban soundscapes? What will people think when there are an [economically viable] number of these machines operating? Although this effort is ongoing, a number of advances have already been made: A psychoacoustic test to guide UAM sound design has been recently completed. Several algorithms to assess the audibility of a UAM vehicle in an existing background soundscape have been put forward. A technical memorandum detailing best practices for recording and reproduction of background sounds for UAM psychoacoustic research has been published (TM 20210017504). Flexible data analysis methods that could be agile to changes in perception that occur when large numbers of vehicles are flying have been developed by extending existing metrics. This presentation gives an overview of this completed and continuing research.

UAM↗

Wake Vortex Effects Between Urban Air Mobility Aircraft

This study models the wake-induced downwash of an Urban Air Mobility (UAM) aircraft and the wake’s effects on a trailing aircraft’s dynamic stability when intersecting the wake trail. The Proctor wake vortex model is used to compute the wake-induced downwash over a 0.8 × 0.8 nautical mile flight area. The model is complemented by core radius growth, Proctor single phase wake decay, wake propagation, and Lamb wake aging. The wake data is then stored and loaded to the trailing aircraft as an atmospheric condition to affect the dynamics. Preliminary simulations include modeling the downwash from multiple UAM aircraft over the flight area and determining the normalized wake reduction at the ICAO 5 nautical mile separation criteria for a LIGHT aircraft trailing a MEDIUM aircraft.

Wake Vortex↗

Preliminary Electric Motor Drivetrain Optimization Studies for Urban Air Mobility Vehicles

Electric and hybrid electric aircraft require high performance and reliable electric motor drivetrains. These drivetrains, consisting of a motor, an inverter, a gearbox, and a thermal management system, are highly coupled systems where the design of individual components in the drivetrain will significantly affect the sizing and performance of the other components in the system. In this paper, a preliminary co-optimization tool for electric motor drivetrains for Urban Air Mobility vehicles is presented. An example study with the tool is completed for NASA’s RVLT quadrotor concept vehicle.

Thomas Tallerico↗

Feasibility study for remote psychoacoustic testing of human response to urban air mobility vehicle noise

NASA will remotely administer a psychoacoustic test in late summer of 2022 as the first of two phases of a cooperative Urban Air Mobility (UAM) vehicle noise human response study. This study relies on the cooperation of multiple government agencies, academia, and industry to assemble a wide range of UAM vehicle sounds. This database of sounds will be used to create a rich database of human response to UAM noise that would be challenging for a single organization to acquire. The development of the remote test method to study human response to aviation noise was prompted by the novel coronavirus pandemic. The feasibility portion of the study described in this work will demonstrate and refine the remote test method for use in the implementation phase. This paper details the method for remotely administering the psychoacoustic test and the sound stimuli to be used in the Feasibility Test. Comparisons of annoyance response data from previous in-person tests will be used to demonstrate the viability of the remote test method. The paper also describes an effort to determine if providing a contextual cue to test subjects influences the annoyance response.

Remote psychoacoustic test↗

A Comprehensive eVTOL Performance Evaluation Framework in Urban Air Mobility

In this paper, we developed an open-source simulation framework for the evaluation of electric vertical takeoff and landing vehicles (eVTOLs) in the context of Unmanned Traffic Management (UTM) and under the concept of Urban Air Mobility (UAM). Unlike most existing studies, the proposed framework combines the utilization of UTM and eVTOLs to develop a realistic UAM testing platform. For this purpose, we first develop an UTM simulator to simulate the real-world UAM environment. Then, instead of using a simplified eVOTL model, a high-fidelity eVTOL design tool, namely SUAVE, is employed and an dilation sub-module is introduced to bridge the gap between the UTM simulator and SUAVE eVTOL performance evaluation tool to elaborate the complete mission profile. Based on the developed simulation framework, experiments are conducted and the results are presented to analyze the performance of eVTOLs in the UAM environment.

Mrinmoy Sarkar↗

Diesel Passenger Vehicle Shares Influenced Covid-19 Changes in Urban Nitrogen Dioxide Pollution

Diesel-powered vehicles emit several times more nitrogen oxides than comparable gasoline-powered vehicles, leading to ambient nitrogen dioxide (NO2) pollution and adverse health impacts. The COVID-19 pandemic and ensuing changes in emissions provide a natural experiment to test whether NO2 reductions have been starker in regions of Europe with larger diesel passenger vehicle shares. Here we use a semi-empirical approach that combines in-situ NO2 observations from urban areas and an atmospheric composition model within a machine learning algorithm to estimate business-as-usual NO2 during the first wave of the COVID-19 pandemic in 2020. These estimates account for the moderating influences of meteorology, chemistry, and traffic. Comparing the observed NO2 concentrations against business-as-usual estimates indicates that diesel passenger vehicle shares played a major role in the magnitude of NO2 reductions. European cities with the five largest shares of diesel passenger vehicles experienced NO2 reductions ∼ 2.5 times larger than cities with the five smallest diesel shares. Extending our methods to a cohort of non-European cities reveals that NO2 reductions in these cities were generally smaller than reductions in European cities, which was expected given their small diesel shares. We identify potential factors such as the deterioration of engine controls associated with older diesel vehicles to explain spread in the relationship between cities’ shares of diesel vehicles and changes in NO2 during the pandemic. Our results provide a glimpse of potential NO2 reductions that could accompany future deliberate efforts to phase out or remove passenger vehicles from cities.

Nitrogen Dioxide↗

Sources, Transport and Visibility Impact of Ambient Submicrometer Particle Size Distributions in an Urban Area of Central Taiwan

This study applied positive matrix factorization (PMF) to identify the sources of size-resolved submicrometer (10–1000 nm) particles and quantify their contributions to impaired visibility based on the particle number size distributions (PNSDs), aerosol light extinction (b p ), air pollutants (PM 10 , PM 2.5 , SO 2 , O 3 , and NO), and meteorological parameters (temperature, relative humidity, wind speed, wind direction, and ultraviolet index) measured hourly over an urban basin in central Taiwan between 2017 and 2021. The transport of source-specific PNSDs was evaluated with wind and back trajectory analyses. The PMF revealed six sources to the total particle number (TPN), surface (TPS), volume (TPV), and b p . Factor 1 (F1), the key contributor to TPN (35.0 %), represented nucleation (<25 nm) particles associated with fresh traffic emission and secondary new particle formation, which were transported from the west-southwest by stronger winds (>2.2 m s -1 ). F2 represented the large Aitken (50–100 nm) particles transported regionally via northerly winds, whereas F3 represented large accumulation (300–1000 nm) particles, which showed elevated concentrations under stagnant conditions (<1.1 m s −1 ). F4 represented small Aitken (25–50 nm) particles arising from the growth and transport of the nucleation particles (F1) via west-southwesterly winds. F5 represented large Aitken particles originating from combustion-related SO 2 sources and carried by west-northwesterly winds. F6 represented small accumulation (100–300 nm) particles emitted both by local sources and by the remote SO 2 sources found for F5. Overall, large accumulation particles (F3) played the greatest role in determining the TPV (66.4 %) and TPS (34.8 %), and their contribution to bp increased markedly from 17.3 % to 40.7 % as visibility decreased, indicating that TPV and TPS are better metrics than TPN for estimating b p . Furthermore, slow-moving air masses—and therefore stagnant conditions—facilitate the build-up of accumulation mode particles (F3 + F6), resulting in the poorest visibility.

source apportionment↗

Secondary Inorganic Aerosol Chemistry and Its Impact on Atmospheric Visibility Over an Ammonia-Rich Urban Area in Central Taiwan

This study investigated the hourly inorganic aerosol chemistry and its impact on atmospheric visibility over an urban area in Central Taiwan, by relying on measurements of aerosol light extinction, inorganic gases, and PM 2.5 water-soluble ions (WSIs), and simulations from a thermodynamic equilibrium model. On average, the sulfate (SO 4 2− ), nitrate (NO 3 − ), and ammonium (NH 4 + ) components (SNA) contributed ∼90% of WSI concentrations, which in turn made up about 50% of the PM 2.5 mass. During the entire observation period, PM 2.5 and SNA concentrations, aerosol pH, aerosol liquid water content (ALWC), and sulfur and nitrogen conversion ratios all increased with decreasing visibility. In particular, the NO 3 − contribution to PM 2.5 increased, whereas the SO 4 2− contribution decreased, with decreasing visibility. The diurnal variations of the above parameters indicate that the interaction and likely mutual promotion between NO 3 − and ALWC enhanced the hygroscopicity and aqueous-phase reactions conducive for NO 3 − formation, thus led to severely impaired visibility. The high relative humidity (RH) at the study area (average 70.7%) was a necessary but not sole factor leading to enhanced NO 3 − formation, which was more directly associated with elevated ALWC and aerosol pH. Simulations from the thermodynamic model depict that the inorganic aerosol system in the study area was characterized by fully neutralized SO 4 2− (i.e. a saturated factor in visibility reduction) and excess NH 4 + amidst a NH 3 -rich environment. As a result, PM 2.5 composition was most sensitive to gas-phase HNO 3 , and hence NOx, and relatively insensitive to NH 3 . Consequently, a reduction of NOx would result in instantaneous cuts of NO 3 − , PM 2.5 , and ALWC, and hence improved visibility. On the other hand, a substantial amount of NH 3 reduction (>70%) would be required to lower the aerosol pH, driving more than 50% of the particulate phase NO 3 − to the gas phase, thereby making NH 3 a limiting factor in shifting PM 2.5 composition.

aerosol chemistry↗

Sirius: Simulation and Evaluation of Tactical Conflict Management in an Urban Environment

This presentation provides an overview of the SIRIUS framework, updates to the ICAROUS core modules, and highlights the results of recent simulation and evaluation of tactical deconfliction in an urban environment. The SIRIUS simulation framework provides a fast time method for simulation a large number of aircraft in parallel. Updates to the ICAROUS core modules highlighted in the presentation include the evaluation of the encounter type geometry and changes to the resolution type selection based on the encounter type and following right of way (ROW) rules. The main objective of the simulation was to evaluate the use of strategic and tactical conflict management strategies using a set of simulated UAM scenarios.

Andrew Peters↗

Development of a Weather Capability for the Urban Air Mobility Airspace Research Roadmap

Traditionally, the transportation system’s resiliency to the impacts of weather is an area where neglected or incorrect assumptions can lead to difficulties later in the research and development lifecycle. To mitigate this, NASA has ongoing efforts to develop a set of research roadmaps for organizing, integrating, and communicating research into new aviation infrastructure and transportation modalities, within which weather is being addressed early on. An effort has been undertaken to add weather assumptions and requirements to an already-existing roadmap for the Urban Air Mobility (UAM) airspace, seeking to integrate weather requirements early in the system design. This effort addresses the way in which state-of-the art and evolving weather science and technology can enable safe and efficient travel with increasing tempo of UAM operations over time. This paper describes the addition of weather as one of 10 capabilities into the UAM Airspace research roadmap, laying out the anticipated weather technology and information requirements needed to facilitate operations at various UAM Maturity Levels. The process developed and exercised by MIT Lincoln Laboratory researchers produced 41 unique requirements to be satisfied by a Weather capability for the UAM ecosystem, with more than 300 dependencies identified across the system. These requirements cover measurement, analysis, modeling, forecasting, decision support, dissemination, and overarching policy, and are provided with an overview of weather challenges for UAM. The requirements were mainly defined based on subject matter expert review of existing UAM Airspace system requirements, and refined based on iterative feedback with various stakeholders including regulators, academia, and industry. Going forward, this roadmap will help researchers and developers align to a common vision in ensuring that weather is appropriately considered in the UAM ecosystem.

Timothy Bonin↗

Simulation of the Rotorwash Induced by a Quadrotor Urban Air Taxi in Ground Effect

A rotorcraft hovering near the ground causes downwash and outwash. The impact of these induced velocities on urban air mobility operations has not been extensively quantified. This paper explores the opportunity of using CFD to perform dedicated studies on the aerodynamics of rotorcraft in ground effect (IGE). For this purpose, we compare load and flow predictions obtained with the high-fidelity CFD solver OVERFLOW and with a medium-fidelity vortex particle-mesh (VPM) method, for a single rotor IGE. We show that the computational cost of high-fidelity simulation makes it impractical to sweep through a large number of configurations or operating conditions. However, a small set of cases can be used to verify a medium-fidelity tool. The latter provides a better trade-off between “accuracy” and computational intensity, which enables numerous, longer simulations at a more affordable cost. As an example, the outwash flow is computed for two different designs of a quadrotor air taxi in hover and reveals the existence of increased velocities between the rotors. This work illustrates how CFD can help identify dangerous areas for passengers and ground personnel when they approach the vehicle.

HECC↗

A Psychoacoustic Test for Urban Air Mobility Vehicle Sound Quality

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

UAM↗

An On-Board Off-Board Framework for Online Replanning: Applied to UAVs in Urban Environments

Autonomous systems are being used in a multitude of areas at an increasing rate and require a high level of adaptivity and intelligence to operate safely, especially under faulty conditions. This paper introduces a novel genetic algorithm tailored for UAV trajectory replanning, with an improved execution time via search space reduction based on the operating conditions of the UAV and its remaining mission. A unique characteristic of the replanning agent is its fast-start and adaptive properties, pre-seeding candidates with partial solutions and dynamically tuning elitism, crossover, and mutation rates in correspondence to the average fitness and diversity of the population. A population restart mechanism and early stopping mechanism are evaluated as well to assess their effect on solution quality and runtime. Previous work on genetic algorithms for UAV replanning were conducted with short trajectories in a small state space. Our UAV operates in a 56,000 square meter simulated urban environment, with static obstacles and a total of 53 possible waypoints. The agent increases the safety and reliability of UAV autonomy when operating under faulty conditions and when replanning is required.

Machine Learning↗

Benchmark Problem for Autonomous Urban Air Mobility

This paper introduces a Community Benchmark Problem (CBP) for Intelligent Contingency Management (ICM) for Urban Air Mobility (UAM) aircraft. The CBP aims to provide a common framework for measuring and comparing the progress of autonomy solutions for UAM aircraft in handling emergency situations. The paper proposes a methodology for defining and quantifying five measures of complexity that capture the challenges and requirements of ICM for UAM: Mission, Environmental, Autonomy, Decision-Making, and Mission Fault. In addition, it proposes a methodology for defining and quantifying mission risk acceptability with the same goals: Contingency Management, Mission Success, Operational, Mission Redefinition, and Environmental. We describe how to use these measures to track progress of the development of ICM capability, as well as to create scenarios and evaluate the performance of different autonomy solutions.

autonomy↗

Enhancing In-Flight Structural Health Monitoring of Vertical Lift Vehicles Operating in an Urban Environment

In-situ airframe sensors have long been considered a potential solution for structural health monitoring that could change the design, certification, operation and maintenance paradigms of flight vehicles. In this approach, large networks of sensors covering the entire, or most of, an airframe throughout its operational lifetime would support real-time decisions on airworthiness and obviate the need to overbuild components or perform multiple cycles of structural qualification testing and inspections. This concept would go beyond the current practice of placing select sensors in strategic locations or relying on such sensors only during airframe qualification flights and inspections. For vehicles in the emerging urban air mobility space, reducing weight associated with overbuilds and shortening down-time associated with inspections are critical for improving safety and affordability. In practice, the wide-scale use of in-situ sensors as primary assurance for structural health has not been demonstrated to be feasible or the best solution. A sensor integration testbed was developed as a platform to evaluate the potential of multiple sensor types to enable decision making on airworthiness. We report on the initial runs of this testbed with multiple sensors attached to a common test article. Metal foil strain gauges, eddy current, fiber optic, guided wave (acoustic emission and ultrasonic)and carbon nanotube roving sensors were affixed to the test article. Baseline as well as post damage initiation and fatiguing data are presented and discussed. Despite the relative simplicity of the test article, the interpretation of the as-captured test data was generally not conclusive or did not have wide enough coverage. This result emphasizes the challenges and current limitations both in testing and the practical broad application of embedded sensors as the determinative elements in critical decision making on wide-scale structural health.

Vertical Lift Vehicles↗