Results for “UAs” — Page 41

NASA NTRSDate not supplied

BERT-based Topic Modeling and Information Retrieval to Support Fishbone Diagramming for Safe Integration of Unmanned Aircraft Systems in Wildfire Response

Recent concepts for emerging wildfire response operations have included unmanned aircraft systems (UAS) due to their increasing accessibility and capabilities. To integrate UAS into wildfire response safely, researchers have studied the use of large repositories of historic incident reports to improve the scope of root cause analysis. Recent work has emphasized applying state-of-the-art natural language processing techniques to extract useful information from these repositories. However, it has not yet been studied how these results can be interpreted and integrated into the systems engineering process. In this work, we propose a process in which Bidirectional Encoder Representations from Transformers (BERT)-based topic modeling and information retrieval are applied to a relevant set of documents in order to support the development of a fishbone diagram in a semiautomated process. High-level themes in the document set are identified using topic modeling, which are then refined and interpreted by a human analyst. Then, the themes are used to guide a finer search using information retrieval, which returns specific incident reports of relevance. This provides traceability to specific incidents as well as broader categorizations that comprise the fishbone branches. We apply the proposed process to relevant documents from NASA’s Aviation Safety Reporting System (ASRS). The proposed process is widely applicable when relevant documents are available, and the results from this study will be useful to identifying potential causes of wildfire response UAS incidents.

hazard analysis↗

NASA NTRSDate not supplied

Development of a Safety Hazards Risk Assessment Tool for Uncrewed Aircraft System Traffic Management during Preflight Planning

Tremendous growth in the uncrewed and remotely piloted vehicle market is expected in low-altitude, uncontrolled airspace, resulting in potential decreases in safety without systems that support monitoring, assessing, and mitigating risk. At NASA, the System-Wide Safety (SWS) project has been developing a suite of data-driven tools to predict hazards so that the potential risks that these hazards pose can be mitigated. Services to predict various hazards have been developed, including battery capacity, proximity to static obstacles, population risks, global positioning system signal strength, radio frequency spectrum interference risk, and vertiport congestion. These services can monitor hazards along a flight path and if any risks posed by these hazards exceed a threshold, the uncrewed aircraft system (UAS) fleet manager can be alerted to mitigate the risk by modifying the flight path, changing the scheduled departure or arrival times, and/or diverting the vehicle to an alternate vertiport. These services were originally developed to monitor and assess risks during flight, but they have been adapted to assess hazard risks prior to departure so that a fleet manager can evaluate the potential risks for a fleet of UAS along their planned flight paths. These services have been integrated into a prototype tool called the Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD), developed at NASA Ames Research Center. The tool consists of a dashboard which provides a comprehensive overview for a number of risks and a map display that shows the details of the hazards along each flight’s path. Based on the findings from three previous studies, the SDSP-CD has been updated with new design elements and functions. In this paper, we describe lessons learned from the previous studies, changes made to the interface, and the feedback received during a follow-up usability study. Overall, participants reported that there is a substantial benefit of having a fleet manager use a consolidated dashboard to assess hazards for the vehicles in their fleet and to provide situational awareness to potential risks so that they can be mitigated prior to flight. Once the SDSP-CD matures, it will need to be integrated into flight and mission planning tools. Some initial thoughts on how this integration should be accomplished are shared in this paper. Finally, the functional differences between preflight vs. in-flight risk assessment and the differences in fleet manager vs. UAS pilot roles that may require different information and user interactions are discussed.

preflight↗

NASA NTRS2015

Safely Enabling Low-Altitude Airspace Operations: Unmanned Aerial System Traffic Management (UTM)

Near-term Goal Enable initial low-altitude airspace and UAS operations with demonstrated safety as early as possible, within 5 years Long-term Goal Accommodate increased UAS operations with highest safety, efficiency, and capacity as much autonomously as possible (10-15 years).

SASO↗

NASA NTRS2015

Safely Enabling Low-Altitude Airspace Operations

Near-term Goal: Enable initial low-altitude airspace and UAS operations with demonstrated safety as early as possible, within 5 years. Long-term Goal: Accommodate increased UAS operations with highest safety, efficiency, and capacity as much autonomously as possible (10-15 years).

UTM↗

NASA NTRS2017

An Alternative Time Metric to Modified Tau for Unmanned Aircraft System Detect And Avoid

A new horizontal time metric, Time to Protected Zone, is proposed for use in the Detect and Avoid (DAA) Systems equipped by unmanned aircraft systems (UAS). This time metric has three advantages over the currently adopted time metric, modified tau: it corresponds to a physical event, it is linear with time, and it can be directly used to prioritize intruding aircraft. The protected zone defines an area around the UAS that can be a function of each intruding aircraft's surveillance measurement errors. Even with its advantages, the Time to Protected Zone depends explicitly on encounter geometry and may be more sensitive to surveillance sensor errors than modified tau. To quantify its sensitivity, simulation of 972 encounters using realistic sensor models and a proprietary fusion tracker is performed. Two sensitivity metrics, the probability of time reversal and the average absolute time error, are computed for both the Time to Protected Zone and modified tau. Results show that the sensitivity of the Time to Protected Zone is comparable to that of modified tau if the dimensions of the protected zone are adequately defined.

alert↗

NASA NTRS2017

An Alternative Time Metric to Modified Tau for Unmanned Aircraft System Detect And Avoid

A new horizontal time metric, Time to Protected Zone, is proposed for use in the Detect and Avoid (DAA) Systems equipped by unmanned aircraft systems (UAS). This time metric has three advantages over the currently adopted time metric, modified tau: it corresponds to a physical event, it is linear with time, and it can be directly used to prioritize intruding aircraft. The protected zone defines an area around the UAS that can be a function of each intruding aircraft's surveillance measurement errors. Even with its advantages, the Time to Protected Zone depends explicitly on encounter geometry and may be more sensitive to surveillance sensor errors than modified tau. To quantify its sensitivity, simulation of 972 encounters using realistic sensor models and a proprietary fusion tracker is performed. Two sensitivity metrics, the probability of time reversal and the average absolute time error, are computed for both the Time to Protected Zone and modified tau. Results show that the sensitivity of the Time to Protected Zone is comparable to that of modified tau if the dimensions of the protected zone are adequately defined.

UAS↗

NASA NTRS2017

UTM Weather Presentation

Presentation highlighting how weather affected UAS operations during the UTM field tests. Research to develop UAS weather translation models with a description of current and future work for UTM weather.

UTM↗

NASA NTRS2018

Information Displays and Crew Configurations for UTM Operations

In this paper we discuss how team configuration may influence how infor-mation is shared among team members for low-altitude Unmanned Aircraft Systems (UAS) operations. NASA collected and analyzed observation data gathered during a series of field tests for the UAS Traffic Management (UTM) project. The field tests were part of a larger effort aimed at advancing the UTM concept, conducted at six test-sites spread across the USA. Ground control station (GCS) concepts, flight-crew composition, and crew-size var-ied within and across test-sites. Flight crews took two strategic approaches to organizing their teams. The first of the two approaches was implemented by one third of the flight crews. These crews integrated the role of UTM opera-tor into the duties of existing crew members, merging the current roles with this new one, keeping the UTM Operator collocated with the flight crew. The remaining two thirds implemented a distributed team configuration, where a single UTM operator distributed support across multiple crews. Results from our data collection efforts revealed that UTM Operator location influenced whether flight crews used verbal communication versus displays to acquire UTM information.

teams↗

NASA NTRSDate not supplied

Human-system Interaction Issues and Proposed Solutions To Promote Successful Maturation of the UTM System

Over five years, NASA, together with partnering organizations, has been developing and successfully demonstrating the maturing capabilities of the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) system and its ability to support communication and coordination among small UAS operations through a series of flight tests. During these flight tests, human-system interaction (HSI) elements were also explored in order to identify the barriers to implementation as human operators transitionally fulfill roles that will be ultimately tasked to future automation. Throughout the tests, similar issues were regularly documented and are expected to persist if not formally addressed by consistent procedures or regulation. Documented here, along with suggested mitigations, are the most frequently noted HSI items, which include operator training, data standardization, and information quantity.

UTM↗

NASA NTRSDate not supplied

Human-system interaction issues and proposed solutions to promote successful maturation of the UTM system

Over five years, NASA, together with partnering organizations, has been developing and successfully demonstrating the maturing capabilities of the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) system and its ability to support communication and coordination among small UAS operations through a series of flight tests. During these flight tests, human-system interaction (HSI) elements were also explored in order to identify the barriers to implementation as human operators transitionally fulfill roles that will be ultimately tasked to future automation. Throughout the tests, similar issues were regularly documented and are expected to persist if not formally addressed by consistent procedures or regulation. Documented here, along with suggested mitigations, are the most frequently noted HSI items, which include operator training, data standardization, and information quantity.

UTM↗

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 NTRSDate not supplied

Studying Human-System Interaction within the UTM System

Over five years, NASA, together with partnering organizations, has been developing and successfully demonstrating the maturing capabilities of the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) system and its ability to support communication and coordination among small UAS operations through a series of flight tests. During these flight tests, human-system interaction (HSI) elements were also explored in order to identify the barriers to implementation as human operators transitionally fulfill roles that will be ultimately tasked to future automation. Throughout the tests, similar issues were regularly documented and are expected to persist if not formally addressed by consistent procedures or regulation. Documented here, along with suggested mitigations, are the most frequently noted HSI items, which include operator training, data standardization, and information quantity. .

UTM↗

NASA NTRSDate not supplied

Studying Human-System Interaction with the UTM System

Over five years, NASA, together with partnering organizations, has been developing and successfully demonstrating the maturing capabilities of the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) system and its ability to support communication and coordination among small UAS operations through a series of flight tests. During these flight tests, human-system interaction (HSI) elements were also explored in order to identify the barriers to implementation as human operators transitionally fulfill roles that will be ultimately tasked to future automation. Throughout the tests, similar issues were regularly documented and are expected to persist if not formally addressed by consistent procedures or regulation. Documented here, along with suggested mitigations, are the most frequently noted HSI items, which include operator training, data standardization, and information quantity.

UTM↗

NASA NTRS2022

Evaluation and Improvement of System-of-Systems Resilience in a Simulation of Wildfire Emergency Response

Because of the increasing threat that wildfires pose, there is interest in leveraging new technologies to improve firefighting. Specifically, Unmanned Aerial Systems (UAS) and UAS Traffic Management (UTM) promise to improve firefighters’ situational awareness, coordination, communications, safety, and strategy. While these technologies could be beneficial, there has been little formal investigation into how much benefit would occur and whether these benefits would outweigh hazards introduced by these systems. To better understand the impacts of these technologies, this paper presents a high-level dynamic simulation for evaluating wildfire response performance and resilience incorporating fire propagation, surveillance and communication, response planning, and the resulting mitigation actions. This simulation is then used to study the impact of communications and surveillance improvement, considering (1) the effect on fire containment and ground crew injuries and (2) the effect of introduced and existing disruptive fault scenarios. Simulating this model over a large number of scenarios finds that these changes can improve containment and reduce ground crew injuries. While these improvements generalize over both existing and introduced single-fault scenarios and thus result in a more resilient system, they could be negated if the introduced communications infrastructure is prone to full-scale outages.

modeling↗

NASA NTRSDate not supplied

UASs in the VOG/Edge/FOG Sensor Web Environment

This paper will describe the evolution of information collection, derivation and delivery mechanisms in sensor webs utilizing Uninhabited Aerial Systems (UAS).We will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, UASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary UASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. The Author will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing UASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to other UAS development This paper will focus on applications, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

UAS↗

NASA NTRS2023

m:N Working Group Spring Meeting Summary

On May 9th and 11th, 2023, the NASA-led MultiVehicle (m:N) Working Group and its subgroups [small Unmanned Aircraft Systems (sUAS), Large UAS, High Altitude Pseudo Satellite (HAPS), and Urban Air Mobility (UAM)] met in Denver, CO at XPONENTIAL 2023, co-hosted by the Association for Uncrewed Vehicle Systems International (AUVSI) and Messe Düsseldorf North America (MDNA), for an in-person meeting. The subgroups meet multiple times throughout the year, virtually. Twice a year, however, participants from all the subgroups come together to brief each other on progress, challenges, and path forward ideas for incorporating UAS into the airspace. The m:N working group is co-chaired by Jay Shively (Adaptive Aerospace) and Andy Thurling (Thurling Aero Consulting) and is comprised of members from government, industry, and academia in an effort to identify and reduce barriers to m:N operations. This effort also includes identifying requirements, use cases, and metrics to support organizations and groups, including the FAA and RTCA’s SC-228 Detect and Avoid.

multi-vehicle↗

NASA NTRSDate not supplied

Identifying Human Factors Research for Unmanned Aircraft Systems and Advanced Air Mobility

This paper identifies some of the key human factors (HF) challenges when integrating Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) into the civil airspace. Unique HF considerations—those which are derived from the key differentiating aspects of UAS/AAM compared to conventional aviation—are the primary basis for identifying HF research opportunities. By identifying what makes UAS and AAM fundamentally different from conventional aviation, from a human integration perspective, HF research can be targeted to effectively inform best practices, standards, policy, guidance, and regulations associated with aircraft and air traffic systems and operations. HF research areas are discussed within the following topic areas: Sustained low-altitude operations; loss of natural sensing; novel aircraft; novel operations; link management and lost link; link performance; distributed pilot teams; and increased automation. The identified research descriptions are intended to serve as illustrative examples of what research is fundamental, and why. They are not intended to prescribe, prioritize or exclude research.

AAM↗

NASA NTRS1989

Effects of aging condition on the fracture toughness of 2XXX and 7XXX series aluminum alloy composites

Results are presented on the effects of matrix aging condition (i.e., matrix temper) on the fracture toughness of 2XXX and 7XXX Al matrix alloys reinforced with SiC particulates, and the results are compared with the mechanical behavior. Fracture toughness testing was conducted on fatigue precracked bend specimens, and fracture surfaces were examined using SEM. Results revealed dramatic differences in the effect of matrix microstructure on the fracture properties of the two composite series. In the 7XXX material, the toughness values decreased from the underaged (UA) condition to the overaged (OA) condition by approximately 40 percent, while in the 2XXX series composite, the effect of matrix microstructure was marginal. In the 7XXX series composites, a transition in fracture mode from particle cracking (in UA) to matrix and linear-interface failure (in OA) was observed, while the 2XXX series composite failed predominantly by particle cracking.

Manoharan, M.↗