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Results for “advanced aerial mobility (AAM)”

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40 records · Page 3

Assessment of Secondary Pitot Probe Locations on a Small UAS

Urban Air Mobility (UAM) and Advanced Air Mobility (AAM) have been at the forefront of many aeronautical discussions because of the potential revolutionary improvement to urban transportation. In this study, a representative Research Aircraft for eVTOL Enabling techNologies, Sub-scale Wind Tunnel Flight Test (RAVEN SWFT) nosecone was placed inside the NASA Langley Research Center’s 12-Foot Low-Speed Wind Tunnel with a pitot-static assembly installed. The study aimed to determine a suitable location and orientation of the pitot-static assembly on the nose of the vehicle, which consists of two airspeed sensors: one for the flight controller and one for data collection. The dynamic pressure was varied from 0.5 to 5psf for each test point. Additionally, three different offset distances from the center boom and three different angles for the flight controller pitot tube were tested. The data from both of the pitot tube assemblies were compared to the wind tunnel and the Aeroprobe pitot tube. The results show the flight controller pitot tube performs better when it is placed further away from the nosecone, regardless of the angle. The results also show that the angle does not affect the accuracy of the pitot tube when the vehicle yaws or pitches regardless of the mounting angle and location. The study provides useful insights for the design of the airspeed measurement systems on small Uncrewed Aerial Systems (sUAS), which can be applied to other UAM and AAM applications.

AAM↗

Dynamic Channel Assignments for Efficient Use of Aviation Spectrum Allocations

The demand for voice and data communications continues to rise with the emergence of new aerial vehicles into the airspace and the continued growth of aviation operations throughout the National Airspace System (NAS). Recent studies have shown that the anticipated growing demand for spectrum resources will exceed the capacity of existing aviation spectrum allocations. Further, airspace configurations, via assignment of fixed channel allocations within standard service volumes, do not allow for the dynamic and efficient distribution of spectrum resources based on airspace demand; as a result, a new approach to aviation spectrum management is needed to support the forecasted needs of new airspace users. The National Aeronautics and Space Administration (NASA) is investigating applications of artificial intelligence (AI), machine learning (ML), and other advanced concepts to solve a dynamic constraint satisfaction problem which is analogous to the frequency assignment problem faced by aviation. Procedures and strategies for dynamic channel allocation can be borrowed from other large-scale mobile services (i.e., 4G/5G applications) and can provide a novel spectrum management approach that allows for the intelligent utilization of aviation spectrum throughout the airspace while maintaining the strict quality of service prescribed by aeronautical standards.

communications↗

Dynamic Channel Assignments for Efficient Use of Aviation Spectrum Allocations

The demand for voice and data communications continues to rise with the emergence of new aerial vehicles into the airspace and the continued growth of aviation operations throughout the National Airspace System (NAS). Recent studies have shown that the anticipated growing demand for spectrum resources will exceed the capacity of existing aviation spectrum allocations. Further, airspace configurations, via assignment of fixed channel allocations within standard service volumes, do not allow for the dynamic and efficient distribution of spectrum resources based on airspace demand; as a result, a new approach to aviation spectrum management is needed to support the forecasted needs of new airspace users. The National Aeronautics and Space Administration (NASA) is investigating applications of artificial intelligence (AI), machine learning (ML), and other advanced concepts to solve a dynamic constraint satisfaction problem which is analogous to the frequency assignment problem faced by aviation. Procedures and strategies for dynamic channel allocation can be borrowed from other large-scale mobile services (i.e., 4G/5G applications) and can provide a novel spectrum management approach that allows for the intelligent utilization of aviation spectrum throughout the airspace while maintaining the strict quality of service prescribed by aeronautical standards.

Communications↗

Concept, Design, & Implementation of a Remote Vehicle Operations Center for Autonomous Missions

The National Aeronautics and Space Administration is supporting research to develop a prototype remote vehicle operations center at Langley Research Center to explore current and future advanced air mobility operations using small unmanned aerial systems vehicles as surrogates for future, larger-scale passenger carrying vehicles. The prototype facility known as the Remote Operations for Autonomous Missions (ROAM) Unmanned Aerial Systems (UAS) Operations Center is being used to explore different roles and responsibilities of remote operators managing multiple autonomous vehicles, with the goal of exploring human-autonomy teaming concepts that enable m:N operations (i.e., m operators managing N vehicles). ROAM has developed into a world-class research, development, and technology (RD&T) environment that can support both the collection of human factors data and the command and control of remote vehicles in beyond visual line of sight conditions. ROAM provides a key capability to enable full end-to-end hardware- and human-in-the-loop simulation testing, connecting with simulated small-UAS and creating a seamless Live-Virtual-Constructive (LVC) environment. This report describes the development of the ROAM UAS Operations Center from concept through design, culminating in the current implementation at NASA’s Langley Research Center.

CERTAIN↗