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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Exploration of the Trade Space Between Unmanned Aircraft Systems Descent Maneuver Performance and Sense-and-Avoid System Performance Requirements

A need exists to safely integrate Unmanned Aircraft Systems (UAS) into the United States' National Airspace System. Replacing manned aircraft's see-and-avoid capability in the absence of an onboard pilot is one of the key challenges associated with safe integration. Sense-and-avoid (SAA) systems will have to achieve yet-to-be-determined required separation distances for a wide range of encounters. They will also need to account for the maneuver performance of the UAS they are paired with. The work described in this paper is aimed at developing an understanding of the trade space between UAS maneuver performance and SAA system performance requirements, focusing on a descent avoidance maneuver. An assessment of current manned and unmanned aircraft performance was used to establish potential UAS performance test matrix bounds. Then, near-term UAS integration work was used to narrow down the scope. A simulator was developed with sufficient fidelity to assess SAA system performance requirements. The simulator generates closest-point-of-approach (CPA) data from the wide range of UAS performance models maneuvering against a single intruder with various encounter geometries. Initial attempts to model the results made it clear that developing maneuver performance groups is required. Discussion of the performance groups developed and how to know in which group an aircraft belongs for a given flight condition and encounter is included. The groups are airplane, flight condition, and encounter specific, rather than airplane-only specific. Results and methodology for developing UAS maneuver performance requirements are presented for a descent avoidance maneuver. Results for the descent maneuver indicate that a minimum specific excess power magnitude can assure a minimum CPA for a given time-to-go prediction. However, smaller amounts of specific excess power may achieve or exceed the same CPA if the UAS has sufficient speed to trade for altitude. The results of this study will support UAS maneuver performance requirements development for integrating UAS in the NAS. The methods described are being used to help RTCA Special Committee 228 develop requirements.

Jack, Devin P.↗
NASA NTRS2017

Sense and Avoid for Small Unmanned Aircraft Systems

The ability for small Unmanned Aircraft Systems (sUAS) to safely operate beyond line of sight is of great interest to consumers, businesses, and scientific research. In this work, we investigate Sense and Avoid (SAA) algorithms for sUAS encounters using three 4k cameras for separation distances between 200m and 2000m. Video is recorded of different sUAS platforms designed to appear similar to expected air traffic, under varying weather conditions and flight encounter scenarios. University partners and NASA both developed SAA methods presented in this report.

Dolph, Chester V.↗
NASA NTRSDate not supplied

Refined Predictions Compared with the Propulsion Airframe Aeroacoustics and Aircraft System Noise Flight Research Test Data

In a collaboration between NASA and The Boeing Company, the Propulsion Airframe Aeroacoustics and Aircraft System Noise Flight Research Test was executed by the Boeing ecoDemonstrator Program in 2020 with an Etihad Airways Boeing 787-10 aircraft. This ambitious flight research successfully accomplished many objectives and constitutes the most comprehensive and highest quality acoustic flight data available to NASA for a modern commercial subsonic transport aircraft. One purpose of these data is to be the measure of accuracy for the aircraft system noise prediction capabilities of NASA. This research reviews the impact of the major improvements in prediction methods implemented up to this point and tested in the Research version of the NASA Aircraft Noise Prediction Program. The improvements have been to the prediction of jet source and jet-flap interaction, to both fan broadband and tone source prediction, and to the prediction of propulsion airframe aeroacoustic scattering effects. In general, over the engine power range, comparisons between prediction and flight data are within 2 EPNdB including for the intentional sideline-to-sideline asymmetries as implemented in the flight test by flying the aircraft with only one engine at power. Considerable progress has been shown here in the continuing effort to advance the fidelity of NASA aircraft noise prediction capabilities for subsonic aircraft flight acoustics, modern transport aircraft and future aircraft concepts.

aircraft system noise prediction↗
NASA NTRS2022

Remotely Piloted Aircraft Systems

Remotely piloted aircraft range from quadcopter “drones” with endurance measured in minutes, to large, long endurance aircraft powered by jet turbine engines. The central message of this chapter is that the further development of unmanned aviation may be held back more by a lack of attention to human factors, than by technological hurdles. This chapter begins with a brief overview of remotely piloted aircraft, follows with a review of their accident record, and then focuses on human factors principles for Remote Pilot Stations (RPS).

remotely piloted aircraft↗
NASA NTRS2017

Real-Time Risk Assessment Framework for Unmanned Aircraft System (UAS) Traffic Management (UTM)

The new Federal Aviation Administration (FAA) Small Unmanned Aircraft rule (Part 107) marks the first national regulations for commercial operation of small unmanned aircraft systems (sUAS) under 55 pounds within the National Airspace System (NAS). Although sUAS flights may not be performed beyond visual line-of-sight or over non- participant structures and people, safety of sUAS operations must still be maintained and tracked at all times. Moreover, future safety-critical operation of sUAS (e.g., for package delivery) are already being conceived and tested. NASA's Unmanned Aircraft System Trac Management (UTM) concept aims to facilitate the safe use of low-altitude airspace for sUAS operations. This paper introduces the UTM Risk Assessment Framework (URAF) which was developed to provide real-time safety evaluation and tracking capability within the UTM concept. The URAF uses Bayesian Belief Networks (BBNs) to propagate off -nominal condition probabilities based on real-time component failure indicators. This information is then used to assess the risk to people on the ground by calculating the potential impact area and the effects of the impact. The visual representation of the expected area of impact and the nominal risk level can assist operators and controllers with dynamic trajectory planning and execution. The URAF was applied to a case study to illustrate the concept.

Ancel, Ersin↗
NASA NTRS2023

Advances in Aircraft System Identification at NASA Langley Research Center

Advances in aircraft system identification at NASA Langley Research Center are discussed. The relevant time period includes the years since the last summary paper of this kind, which was published in the Journal of Aircraft in 2005. Research advances were achieved in flight test experiment design, frequency-domain modeling, real-time autonomous global modeling, rapid simulation development and updating, dynamic modeling in turbulence, flight data corrections, model uncertainty characterization, and aeroelastic modeling using distributed sensing. Possible future developments in the field are identified.

Aircraft system identification↗
NASA NTRS2016

Progress of Aircraft System Noise Assessment with Uncertainty Quantification for the Environmentally Responsible Aviation Project

Aircraft system noise predictions have been performed for NASA modeled hybrid wing body aircraft advanced concepts with 2025 entry-into-service technology assumptions. The system noise predictions developed over a period from 2009 to 2016 as a result of improved modeling of the aircraft concepts, design changes, technology development, flight path modeling, and the use of extensive integrated system level experimental data. In addition, the system noise prediction models and process have been improved in many ways. An additional process is developed here for quantifying the uncertainty with a 95% confidence level. This uncertainty applies only to the aircraft system noise prediction process. For three points in time during this period, the vehicle designs, technologies, and noise prediction process are documented. For each of the three predictions, and with the information available at each of those points in time, the uncertainty is quantified using the direct Monte Carlo method with 10,000 simulations. For the prediction of cumulative noise of an advanced aircraft at the conceptual level of design, the total uncertainty band has been reduced from 12.2 to 9.6 EPNL dB. A value of 3.6 EPNL dB is proposed as the lower limit of uncertainty possible for the cumulative system noise prediction of an advanced aircraft concept.

Thomas, Russell H.↗
NASA NTRS2021

Bell Unmanned Aircraft Systems Integration and Operationalization (SIO) Demonstration: Final Report, Summary of Research

National Aeronautics and Space Administration (NASA) initiated the Unmanned Aircraft Systems Integration and Operationalization (SIO) demonstration as a partnership between NASA and Industry with the goal of accelerating routine unmanned aircraft systems (UAS) operations in the national airspace (NAS). In order to accomplish this goal, NASA partnered separately with Bell and two other industry teams each pioneering the development, integration, and testing of their UAS, with the intent to make progress towards type certification. The program culminated in flight demonstrations representing future commercial operations by each partner.

Flight Demonstration↗
NASA NTRS2015

Human Performance Considerations for Remotely Piloted Aircraft Systems (RPAS)

Successful integration of Remotely Piloted Aircraft Systems (RPAS) into civil airspace will not only require solutions to technical challenges, but will also require that the design and operation of RPAS take into account human limitations and capabilities. Human factors can affect overall system performance whenever the system relies on people to interact with another element of the system. Four types of broad interactions can be described. These are (1) interactions between people and hardware, such as controls and displays; (2) human use of procedures and documentation; (3) impact of the task environment, including lighting, noise and monotony; and lastly, (4) interactions between operational personnel, including communication and coordination. In addition to the human factors that have been identified for conventional aviation, RPAS operations introduce a set of unique human challenges. The purpose of document is to raise human factors issues for consideration by workgroups of the ICAO RPAS panel as they work to develop guidance material and additions to ICAO annexes. It is anticipated that the content of this document will be revised and updated as the work of the panel progresses.

ICAO↗
NASA NTRS2005

Sense-and-Avoid Equivalent Level of Safety Definition for Unmanned Aircraft Systems. Revision 9

Since unmanned aircraft do not have a pilot on-board the aircraft, they cannot literally comply with the "see and avoid" requirement beyond a short distance from the location of the unmanned pilot. No performance standards are presently defined for unmanned Sense and Avoid systems, and the FAA has no published approval criteria for a collision avoidance system. Before the FAA can develop the necessary guidance (rules / regulations / policy) regarding the see-and-avoid requirements for Unmanned Aircraft Systems (UAS), a concise understanding of the term "equivalent level of safety" must be attained. Since this term is open to interpretation, the UAS industry and FAA need to come to an agreement on how this term can be defined and applied for a safe and acceptable collision avoidance capability for unmanned aircraft. Defining an equivalent level of safety (ELOS) for sense and avoid is one of the first steps in understanding the requirement and developing a collision avoidance capability. This document provides a functional level definition of see-and-avoid as it applies to unmanned aircraft. The sense and avoid ELOS definition is intended as a bridge between the see and avoid requirement and the system level requirements for unmanned aircraft sense and avoid systems. Sense and avoid ELOS is defined in a rather abstract way, meaning that it is not technology or system specific, and the definition provides key parameters (and a context for those parameters) to focus the development of cooperative and non-cooperative sense and avoid system requirements.

Source record↗
NASA NTRSDate not supplied

Alert Timing Assessment for Unmanned Aircraft System Terminal Area Operations

A Detect and Avoid (DAA) system is an essential enabler for integrating Unmanned Aircraft Systems (UAS) into the U.S. National Airspace System. A DAA system uses a suite of sensors, trackers and alerting and guidance algorithms to assist a remote pilot in maintaining separation from airborne traffic. The initial minimum performance standards focused on en route operations; in order to facilitate operations in and around the airport environment, this paper presents the derivation of the early alert threshold for UAS terminal operations.

Unmanned Aircraft Systems↗
NASA NTRS2018

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: Project Overview

NASA's Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project (UAS-NAS) and the UAS Executive Committee (EXCOM) Science and Research Panel (SARP) invite you to attend the 2nd Workshop on Human-Automation Interaction Considerations for UAS Integration. A follow on to the workshop hosted by the National Academies of Science, Engineering and Medicine, this two-day workshop aims to tackle two critical issues for UAS integration in the NAS being addressed by NASA and the SARP: control of multiple UAS by a single, or multiple, operators (multi-UAS), and automatic collision avoidance (auto-CA). Attendees will be asked to generate real humanautomation architecture and human machine interface solutions for these problems during interactive breakout sessions. Attendance is limited to select government and academia invitees only. This presentation is an overview to the project.

Human-Automation Interactions↗
NASA NTRS2023

Operational Integration Potential of Regional Uncrewed Aircraft Systems Into the Airspace System

As part of newly developing aviation markets, fixed-wing Uncrewed Aircraft Systems (UAS) are projected to impact airspace systems and conventional air traffic in the future. The initial introduction of fixed-wing cargo UAS for regional operations is anticipated to occur at smaller under-utilized airports. Therefore, this paper assesses the integration potential of regional fixed-wing cargo UAS into the airspace system. A baseline is established to identify potential airports for cargo UAS operations in different areas. Additionally, using 2022 data, regional aircraft eligible for future cargo UAS operations are investigated. Finally, the accessibility of these regional aircraft at the identified airports was analysed. Based on the availability of current certified landing systems needed for initial UAS operations, potential airports in the areas Germany, Texas, and California for UAS operations are compared. Additionally, based on the maximum takeoff weight allowances of airport runways, current air transport operations at airports, and airspace classes, individual airports with a high potential for the introduction of initial cargo UAS operations with and without the availability of landing systems needed for UAS are identified and compared among the investigated areas. Despite a total of 173 identified airports for potential UAS operations in Germany, 376 in Texas, and 231 in California, only eleven of these airports currently have the certified landing systems needed for initial UAS operations. However, other landing system technologies that are currently under development, such as vision-based landing systems, might support UAS accessibility at the identified airports for potential UAS operations in the future.

Uncrewed aircraft systems↗
NASA NTRS2015

An Evaluation of Detect and Avoid (DAA) Displays for Unmanned Aircraft Systems: The Effect of Information Level and Display Location on Pilot Performance

A consortium of government, industry and academia is currently working to establish minimum operational performance standards for Detect and Avoid (DAA) and Control and Communications (C2) systems in order to enable broader integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS). One subset of these performance standards will need to address the DAA display requirements that support an acceptable level of pilot performance. From a pilot's perspective, the DAA task is the maintenance of self separation and collision avoidance from other aircraft, utilizing the available information and controls within the Ground Control Station (GCS), including the DAA display. The pilot-in-the-loop DAA task requires the pilot to carry out three major functions: 1) detect a potential threat, 2) determine an appropriate resolution maneuver, and 3) execute that resolution maneuver via the GCS control and navigation interface(s). The purpose of the present study was to examine two main questions with respect to DAA display considerations that could impact pilots' ability to maintain well clear from other aircraft. First, what is the effect of a minimum (or basic) information display compared to an advanced information display on pilot performance? Second, what is the effect of display location on UAS pilot performance? Two levels of information level (basic, advanced) were compared across two levels of display location (standalone, integrated), for a total of four displays. The authors propose an eight-stage pilot-DAA interaction timeline from which several pilot response time metrics can be extracted. These metrics were compared across the four display conditions. The results indicate that the advanced displays had faster overall response times compared to the basic displays, however, there were no significant differences between the standalone and integrated displays. Implications of the findings on understanding pilot performance on the DAA task, the development of DAA display performance standards, as well as the need for future research are discussed.

detect and avoid↗
NASA NTRS2017

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project

This presentation summarizes the simulation work conducted by the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project. It focuses on the contribution of that research to the development of RTCA Special Committee 228's (SC-228) Minimum Operational Performance Standards (MOPS) for UAS. The research objectives and primary findings from four different human-in-the-loop simulations are discussed, along with the specific requirements these studies led to in the final MOPS document.

unmanned aircraft systems↗