NASA aerospace database subject scope: An overview

Outlined here is the subject scope of the NASA Aerospace Database, a publicly available subset of the NASA Scientific and Technical (STI) Database. Topics of interest to NASA are outlined and placed within the framework of the following broad aerospace subject categories: aeronautics, astronautics, chemistry and materials, engineering, geosciences, life sciences, mathematical and computer sciences, physics, social sciences, space sciences, and general. A brief discussion of the subject scope is given for each broad area, followed by a similar explanation of each of the narrower subject fields that follow. The subject category code is listed for each entry

An OpenEaagles Framework Extension for Hardware-in-the-Loop Swarm Simulation

Unmanned Aerial Vehicle (UAV) swarm applications, algorithms, and control strategies have experienced steady growth and development over the past 15 years. Yet, to this day, most swarm development efforts have gone untested and thus unimplemented. Cost of aircraft systems, government imposed airspace restrictions, and the lack of adequate modeling and simulation tools are some of the major inhibitors to successful swarm implementation. This thesis examines how the OpenEaagles simulation framework can be extended to bridge this gap. This research aims to utilize Hardware-in-the-Loop (HIL) simulation to provide developers a functional capability to develop and test the behaviors of scalable and modular swarms of autonomous UAVs in simulation with high confidence that these behaviors will prop- agate to real/live ight tests. Demonstrations show the framework enhances and simplifies swarm development through encapsulation, possesses high modularity, pro- vides realistic aircraft modeling, and is capable of simultaneously accommodating four hardware-piloted swarming UAVs during HIL simulation or 64 swarming UAVs during pure simulation

Agent Transparency for Intelligent Target Identification in the Maritime Domain, and its impact on Operator Performance, Workload and Trust

This item is only available electronically.Objective: To examine how increasing the transparency of an intelligent maritime target identification system impacts on operator performance, workload and trust in the intelligent agent. Background: Previous research has shown that operator accuracy improves with increased transparency of an intelligent agent’s decisions and recommendations. This can be at the cost of increased workload and response time, although this has not been found by all studies. Prior studies have predominately focussed on route planning and navigation, and it is unclear if the benefits of agent transparency would apply to other tasks such as target identification. Method: Twenty seven participants were required to identify a number of tracks based on a set of identification criteria and the recommendation of an intelligent agent at three transparency levels in a repeated-measures design. The intelligent agent generated an identification recommendation for each track with different levels of transparency information displayed and participants were required to determine the identity of the track. For each transparency level, 70% of the recommendations made by the intelligent agent were correct, with incorrect recommendation due to additional information that the agent was not aware of, such as information from the ship’s radar. Participants’ identification accuracy and identification time were measured, and surveys on operator subjective workload and subjective trust in the intelligent agent were collected for each transparency level. Results: The results indicated that increased transparency information improved the operators’ sensitivity to the accuracy of the agent’s decisions and produced a greater tendency Agent Transparency for Intelligent Target Identification 33 to accept the agent’s decision. Increased agent transparency facilitated human-agent teaming without increasing workload or response time when correctly accepting the intelligent agent’s decision, but increased the response time when rejecting incorrect intelligent agent’s decisions. Participants also reported a higher level of trust when the intelligent agent was more transparent. Conclusion: This study shows the ability of agent transparency to improve performance without increasing workload. Greater agent transparency is also beneficial in building operator trust in the agent. Application: The current study can inform the design and use of uninhabited vehicles and intelligent agents in the maritime context for target identification. It also demonstrates that providing greater transparency of intelligent agents can improve human-agent teaming performance for a previously unstudied task and domain, and hence suggests broader applicability for the design of intelligent agents.Thesis (M.Psych(Organisational & Human Factors)) -- University of Adelaide, School of Psychology, 201

EXPLORING THE POTENTIAL USE OF LONG-RANGE UNMANNED AERIAL SYSTEMS TO ADDRESS CAPABILITY GAPS IN THE UNITED STATES COAST GUARD

There is a growing threat to international order, specifically in the maritime environment. The United States Coast Guard (USCG), with its unique authorities, is perfectly positioned to respond to these threats in means that can avoid undesired conflict. Increased mission demand for intelligence, surveillance, and reconnaissance coupled with an ever-aging fleet of aircraft, reveal an expanding capability gap in the USCG’s resources. There is an opportunity for the USCG to leverage the capabilities of current and future unmanned aerial systems (UAS), which can be strategically utilized in specific, key mission sets to augment the service’s existing and evolving fleet. By utilizing Department of Defense acquisition frameworks and methods, a standardized approach is employed to analyze the potential benefits and costs of adding UAS capabilities into the USCG’s aviation portfolio, which includes a capabilities based assessment (CBA), DOTmLPF-P analysis, and an analysis of alternatives (AoA). The study found that a capability gap of approximately 13,000 flight hours will come about in the next decade. This gap can be met with commercial materiel UAS solutions that are able to provide persistent surveillance and detection abilities in contested maritime environments.Approved for public release. Distribution is unlimited.Outstanding ThesisLieutenant Commander, United States Coast Guar

Aeronautical Engineering: A special bibliography with indexes, supplement 72, July 1976

This bibliography lists 184 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1976

Application of UASs to augment ground surveys in cranberry agriculture development: a proof of concept for the integration of UAS into the site identification and monitoring of cranberry farms in Newfoundland

Assessing the potential for developing wetland environments into cranberry agricultural lands is time consuming and expensive. The addition of unmanned aerial systems (UAS) to augment current ground survey techniques has the potential to increase assessment accuracy and cranberry production while reducing costs. Newfoundland’s extensive wetlands offer significant opportunities for the development of cranberry agricultural lands. Due to a large international demand for raw cranberries, there is great potential economic benefit in the rapid development of cranberry farms. This study focused on using UASs to assess wetland areas in Newfoundland by applying suitability criteria developed by the Newfoundland Government. This was done through the use of GIS, image classification, and photogrammetry to assess these criteria over three site locations. The viability of expanding UAS data collection over larger areas to develop a province-wide model was explored through an assessment of current fixed wing UAS technology. Given the novelty of this area of study, this research aimed to serve as a proof of concept where the validity of results was measured against real world applicability, not statistical analysis. The results showed that because UASs cannot assess all of the required wetland criteria, they are not a viable replacement for current ground surveys, but do have the potential to augment current techniques. UASs make it possible to survey larger areas, as well as reduce time and cost. The assessment of current fixed wing UAS technology concluded that given the continuously improving technology and further testing, there is the potential for these systems to collect comparable data over a larger area. Overall, the study concluded that through the strategic integration of the UAS techniques developed in this study with existing ground survey methods, Newfoundland has the potential to increase cranberry agricultural development and capitalize on the global demand for this crop

University of Colorado and Black Swift Technologies RPAS-based measurements of the lower atmosphere during LAPSE-RATE

Between 14 and 20&nbsp;July&nbsp;2018, small remotely piloted aircraft systems (RPASs) were deployed to the San Luis Valley of Colorado (USA) together with a variety of surface-based remote and in situ sensors as well as radiosonde systems as part of the Lower Atmospheric Profiling Studies at Elevation &ndash; a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE). The observations from LAPSE-RATE were aimed at improving our understanding of boundary layer structure, cloud and aerosol properties, and surface&ndash;atmosphere exchange and provide detailed information to support model evaluation and improvement work. The current paper describes the observations obtained using four different types of RPASs deployed by the University of Colorado Boulder and Black Swift Technologies. These included the DataHawk2, the Talon and the TTwistor (University of Colorado), and the S1 (Black Swift Technologies). Together, these aircraft collected over 30&thinsp;h of data throughout the northern half of the San Luis Valley, sampling altitudes between the surface and 914&thinsp;m&thinsp;a.g.l. Data from these platforms are publicly available through the Zenodo archive and are co-located with other LAPSE-RATE data as part of the Zenodo LAPSE-RATE community (https://zenodo.org/communities/lapse-rate/, last access: 27&nbsp;May&nbsp;2021). The primary DOIs for these datasets are https://doi.org/10.5281/zenodo.3891620 (DataHawk2, de Boer et al., 2020a, e), https://doi.org/10.5281/zenodo.4096451 (Talon, de Boer et al., 2020d), https://doi.org/10.5281/zenodo.4110626 (TTwistor, de Boer et al., 2020b), and https://doi.org/10.5281/zenodo.3861831 (S1, Elston and Stachura, 2020). &nbsp;</p

Project Shearwater Ground Effect UAV

The Shearwater unmanned aerial vehicle is a maritime fixed-wing drone that is designed to use ground effect force generated between the aircraft and a body of water to efficiently propel itself near the surface of a body of water. Shearwater features a virtual reality pilot interface and will act as a hybrid underwater vehicle that will eventually be able to operate both above and beneath the ocean’s surface. The Shearwater team developed existing design work to produce major subsystems that culminated in a flyable functioning prototype. An existing airframe was updated with working control surfaces tested in simulation and in practice, an electrical control system, and a working virtual reality (VR) pilot view. The Shearwater team tested a practical prototype and developed an optimized virtual reality command and control system

Vision-based autonomous aircraft payload delivery system

This research sought to design and develop an autonomous aircraft payload delivery system which utilised an onboard computer vision system for drop-zone identification. The research was tasked at achieving a modular system which could be used in the delivery of a given payload within a 5 m radius of designated drop-zone identifier. An integrated system was developed, where an autonomous flight controller, an onboard companion computer and computer vision system formed the physical hardware utilised to achieve the desired objectives. A Linux-based Robotic Operating System software architecture was used to develop the control algorithms which governed the autonomous flight control, object recognition and tracking through image processing, and payload release trajectory modelling of the system. The hardware and software architectures were integrated into a remote control fixed-wing aircraft for testing. Implementation of the system through simulation and physical testing proved successful and payload delivery was achieved at an altitude of 75 m, within an average displacement of 1.82 m from the true drop-zone location, where drop-zone detection and location were determined through autonomous survey over the approximate drop-zone’s location. This research furthered the development of autonomous aircraft delivery systems by introducing computer vision as a means of drop-zone location confirmation and authentication, allowing for greater payload delivery security and efficiency. The results gathered in this research illustrated the possible applications of modular airborne payload delivery systems into Industry 4.0 through the use of such a system in the service delivery sector