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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Fundamental Aeroelastic Analysis of an Urban Air Mobility Rotor

A computational investigation was conducted of the aeroelastic characteristics of a representative rotor typical of aircraft for Urban Air Mobility. A rotorcraft comprehensive analysis was used to examine the aeroelastic characteristics of the model, both in hover and in forward flight. Throughout the study, parameters examined included rotor rotational speed, forward flight speed, blade torsion stiffness, and chordwise locations of the blade elastic axis and center of gravity. Three sets of airfoil properties were analyzed: NACA 0012, VR8, and VR12. For hover, the effect of dynamic inflow was studied via a comparison of uniform inflow and dynamic inflow models. Thrust coefficient and blade tip twist were analyzed to ascertain performance characteristics, and eigen analysis was employed to determine stability. For the forward flight cases, rpm and forward flight speed were swept separately, and the effect of each on performance and stability was assessed. Thrust coefficient and mean drag coefficient were used to evaluate performance of the rotor, and eigen analysis was invoked to study rotor stability. Forward flight stability results generated via a constant coefficient analysis were compared with results generated via Floquet Theory.

Fundamental Aeroelastic Analysis↗
NASA NTRS2021

A Data & Reasoning Fabric to Enable Advanced Air Mobility

A Data & Reasoning Fabric (DRF) is envisioned to enable the full potential of advanced air mobility by providing all data and reasoning where they are needed. The DRF marketplace is based on an open foundational ecosystem of data and reasoning exchange between the many systems that must seamlessly interplay to manage the envisioned highly complex and dense airspace operations. DRF activities will identify, test and - as needed - research and develop critical core technologies, and collaboratively test these technologies, open standards and architectures, and the integrated framework with end-users so as to deliver reference designs and development environments that catalyze broad private and public sector buy-in and self-sustaining development of it and associated standards.

Urban Air Mobility↗
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 NTRS1993

L-Band Mobile Terminal Antennas for Helicopters

The feasibility of using a low gain antenna (LGA) as a mobile terminal antenna for helicopters is described in this paper. The objectives are 1) to select the lowest cost antenna system which can be easily mounted on a helicopter and capable of communicating with a satellite, and 2) to determine the best antenna position on the helicopter to mitigate the signal blockage due to rotor blades and the multipath effect from the helicopter's body. The omni-directional low gain antenna (LGA) is selected because it is simple, reliable, and low cost. The helix antenna is selected among the many LGAs because it is the most economical one and has the widest elevation beamwidth. Both 2-arm and 4-arm helices are studied experimentally to determine the antenna's performance and the scattering effects from the helicopter's body. It is found that the LGA should be located near the tail section and at least 8 inches above the helicopter.

helicopter↗
NASA NTRS1993

Pseudo-Coherent Demodulation for Mobile Satellite Systems

This paper proposes three so-called pseudo-coherent demodulation schemes for use in land mobile satellite channels. The schemes are derived based on maximum-likelihood (ML) estimation and detection of an N-symbol observation of the received signal.

Mobile↗
NASA NTRS2020

Advanced Air Mobility (AAM) Vertiport Automation Trade Study

The NASA Advanced Air Mobility (AAM) Vertiport Automation Trade Study seeks to understand the barriers to scaling AAM takeoff and landing facilities, described in this study as vertiplaces. This trade study provides an overview of AAM, vertiplaces, and insight into the gaps in capability, regulatory certainty, and knowledge needed to sufficiently manage the volume of expected traffic anticipated for vertiplaces. The study also outlines potential mitigations to those gaps based on research conducted by the project team and interviews with 23 individuals in government and industry. In this report, the elements that make up a vertiport are discussed. The study then defines a vertiplace and introduces a concept for vertiplace categorization based on capability. Capability gaps and mitigations to increasing scale and automation of vertiplaces are then discussed based around four cross-cutting themes the research of our project team found in the interviews and research: Technology, Physical Infrastructure, Policy, and Community Acceptance. The study then concludes by discussing topics requiring further research that were identified by interviewees.

Vertiport↗
NASA NTRS2021

Advanced Air Mobility and Safety Management Systems

Our current air transportation system has underserved markets, including local, regional, intraregional, and urban transportation of both people and cargo. Recent advances in aviation technology such as small highly-automated vehicles, electric aircraft, and automated air traffic are enabling business opportunities in these markets. Advanced Air Mobility, or AAM, refers to a community effort to overcome the gaps in operational rules, safety analysis, and overall acceptance, so that these new operations will be possible. For full details, please see: https://www.nasa.gov/aam As we think about how we can safely introduce these new operations, fundamental questions about how the structure of Safety Management Systems can be applied to AAM, and how that structure can be used to help us overcome the necessary technical and societal obstacles arise. Two of these questions are: • How do we tailor the requirements and desired level of monitoring and assessment to achieve safety given the breadth of possible operations and the associated risk of those operations? • How do we aid innovation by rapidly evaluating the safety of novel operations without losing associated rigor? We assume that a Safety Management System that enables these future systems will incorporate knowledge of the acceptable level of risk, and will utilize data science to automate the core monitor, assess and mitigate functions that will allow us to respond to risks and hazards in time to prevent safety incidents. In 2018, the National Academies proposed an In-Time Aviation Safety Management System (IASMS) that would advance these goals. (https://www.nap.edu/catalog/24962/in-time-aviation-safety-management-challenges-and-research-for-an) The National Academies made a clear distinction between in-time systems, in which hazards could be identified and risks mitigated in time to prevent incidents, and real-time systems, since many hazards and risks do not need real-time data and analysis to detect and mitigate.

In-Time Aviation Safety Management System↗
NASA NTRSDate not supplied

Simulations of Urban Air Mobility Operations

Urban Air Mobility (UAM) aims to offer air taxi service as an alternative to driving on the congested roads. Integration of UAM operations into the National Airspace System (NAS) has been the focus of the research conducted at NASA Ames Research Center. In this talk, I present results from simulations performed during FY2019 to investigate if NASA’s UAS Traffic Management (UTM) architecture and its implementation are extensible for UAM operations. These simulations also tested a set of core airspace management services tailored to controlled airspace access. In the latter half of this talk, I present the efforts made towards the integration of two such services – a strategic scheduling and a tactical separation service – in a simulation environment under ideal conditions. I will conclude this talk by presenting the future work planned towards enabling UAM operations

Urban Air Mobility↗
NASA NTRS2021

Simulations of Urban Air Mobility Operations

Urban Air Mobility (UAM) aims to offer air taxi service as an alternative to driving on the congested roads. Integration of UAM operations into the National Airspace System (NAS) has been the focus of the research conducted at NASA Ames Research Center. In this talk, I present results from simulations performed during FY2019 to investigate if NASA’s UAS Traffic Management (UTM) architecture and its implementation are extensible for UAM operations. These simulations also tested a set of core airspace management services tailored to controlled airspace access. In the latter half of this talk, I present the efforts made towards the integration of two such services – a strategic scheduling and a tactical separation service – in a simulation environment under ideal conditions. I will conclude this talk by presenting the future work planned towards enabling UAM operations

Urban Air Mobility↗
NASA NTRSDate not supplied

Community Noise Assessment of Urban Air Mobility Vehicle Operations using the FAA Aviation Environmental Design Tool

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate in communities close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration’s Aviation Environmental Design Tool (AEDT), does not support analysis of such operations due to a combined lack of a UAM aircraft performance model and aircraft noise data. This paper discusses the initial development of a method to assess the acoustic impact of UAM fleet operations on the community using AEDT and demonstrates its use for representative UAM operations. In particular, methods were developed using fixed-point flight profiles and user-supplied noise data in a manner that avoids unwanted behavior in AEDT. A set of 32 routes in the Dallas-Ft. Worth area were assessed for single and multiple (fleet) operations for two concept vehicles.

urban air mobility↗
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 NTRSDate not supplied

Comparison of Two Community Noise Models Applied to a NASA Urban Air Mobility Concept Vehicle

Predictions of community noise exposure from a NASA urban air mobility (UAM) concept vehicle have been conducted for representative operations using the FAA Aviation Environmental Design Tool (AEDT) in order to demonstrate modeling tool interoperability and assess applicability, capabilities and limitations of integrated noise modeling tools. To both quantify limitations and highlight other capabilities, a comparative analysis is performed using a time-domain simulation method, in particular, using the Volpe Advanced Acoustic Model (AAM). Using the same source noise model, the 3D directivity of a UAM concept vehicle is predicted in terms of aeroacoustic pressure time histories at a sphere of observer positions near the vehicle. In addition to distilling those data to a set of noise-power-distance data for input to AEDT, the data are processed preserving spectral directivity, into one-third and one-twelfth octave bands for input to AAM. Results from AEDT and AAM modeling are provided for a variety of metrics to demonstrate the effect that source noise directivity and propagation modeling fidelity have on predicted results at receptors over a study area.

urban air mobility↗
NASA NTRSDate not supplied

AIRNOISEUAM: An Urban Air Mobility Noise-Exposure Prediction Tool

A new software tool called AIRNOISEUAM is introduced that models the noise exposure of Urban Air Mobility (UAM) operations. Given relevant UAM aircraft performance models, mission profiles, and Noise-Power-Distance data, AIRNOISEUAM predicts the noise exposure footprint for receptors on the ground. The performance of AIRNOISEUAM using a Robinson R66 helicopter model and a six-passenger quadrotor model, and a diverse set of scenarios from NASA’s UAM human-in-the-loop simulations is compared to that of the industry-standard tool with the same inputs. The predicted noise exposure results from both tools are found to be nearly identical. AIRNOISEUAM offers a fast-time, flexible interface and modular design to facilitate the dynamic requirements of the aviation research community.

Urban air mobility↗