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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Bootstrapping Multi-Agent Unmanned Aerial Vehicle (UAV) System Integration Using Ground-Based Assets: Lessons Learned

In support of the Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project, a fleet of unmanned ground vehicles (UGVs) was developed as a test and evaluation (T\&E) platform to reduce system integration gaps between simulation and live flight hardware. While simulation and hardware-in-the-loop bench testing provide adequate environments for preliminary validation, differences in system deployment architecture, software interfaces, and hardware infrastructure increase the risks to safety, property, and the project. Given ATTRACTOR’s goal of establishing a basis of certification of trust and trustworthiness in multi-agent autonomous systems, bridging these gaps was critical to successful project execution and feasibility assessment. In this paper we present the UGV fleet and its role in speeding up system integration, smoothing the transition from simulation to flight, and providing researchers an easy-to-use hardware test bed. An overview of the hardware and software on-board the vehicles is provided along with supporting infrastructure. The system integration process is documented including results in supporting both the overarching design reference mission (DRM) of ATTRACTOR and individual research efforts conducted since the creation of the fleet. Finally, we discuss the practical lessons learned regarding the testing, deployment, and operation of multi-agent autonomous systems.

Matthew P. Vaughan↗
NASA NTRS2019

Reducing The Noise Impact of Unmanned Aerial Vehicles by Flight Control System Augmentation

The aim of this thesis is to explore methods to reduce the noise impact of unmanned aerial vehicles operating within acoustically sensitive environments by flight control systemaugmentation. Two methods are investigated and include: (i) reduction of sound generatedby vehicle speed control while flying along a nominal path and (ii) reduction of acousticexposure by vehicle path control while flying at a nominal speed. Both methods requireincorporation of an acoustic model into the flight control system as an additional controlobjective and an acoustic metric to characterize primary noise sources dependent on vehiclestate. An acoustic model was developed based on Gutin’s work to estimate propeller noise,both to estimate source noise and observer noise using two separate acoustic metrics. Thesemethods can potentially mitigate the noise impact of unmanned aerial systems operatingnear residential communities.The baseline flight control system of a representative aircraft was augmented with acontrol law to reduce propeller noise using feedback control of the commanded flight speeduntil an acoustic target was met, based on the propeller noise model. This control approachfocuses on modifying flight speed only, with no perturbation to the trajectory. Multipleflight simulations were performed and the results showed that integrating an acoustic metricinto the flight control system of an unmanned aerial system is possible and useful. A secondmethod to mitigate the effects of noise on an observer was also pursued to optimize a tra-jectory in order to avoid an acoustically sensitive region during the path planning process.After the propeller noise model was incorporated into the vehicle system, simulations showedthat it is possible to reduce the noise impact on an observer through an optimization of thetrajectory with no perturbation to the flight speed.

Matthew B Galles↗
NASA NTRS2004

Performance Characterization of a Lithium-ion Gel Polymer Battery Power Supply System for an Unmanned Aerial Vehicle

Unmanned aerial vehicles (UAVs) are currently under development for NASA missions, earth sciences, aeronautics, the military, and commercial applications. The design of an all electric power and propulsion system for small UAVs was the focus of a detailed study. Currently, many of these small vehicles are powered by primary (nonrechargeable) lithium-based batteries. While this type of battery is capable of satisfying some of the mission needs, a secondary (rechargeable) battery power supply system that can provide the same functionality as the current system at the same or lower system mass and volume is desired. A study of commercially available secondary battery cell technologies that could provide the desired performance characteristics was performed. Due to the strict mass limitations and wide operating temperature requirements of small UAVs, the only viable cell chemistries were determined to be lithium-ion liquid electrolyte systems and lithium-ion gel polymer electrolyte systems. Two lithium-ion gel polymer cell designs were selected as candidates and were tested using potential load profiles for UAV applications. Because lithium primary batteries have a higher specific energy and energy density, for the same mass and volume allocation, the secondary batteries resulted in shorter flight times than the primary batteries typically provide. When the batteries were operated at lower ambient temperatures (0 to -20 C), flight times were even further reduced. Despite the reduced flight times demonstrated, for certain UAV applications, the secondary batteries operated within the acceptable range of flight times at room temperature and above. The results of this testing indicate that a secondary battery power supply system can provide some benefits over the primary battery power supply system. A UAV can be operated for hundreds of flights using a secondary battery power supply system that provides the combined benefits of rechargeability and an inherently safer chemistry.

Reid, Concha M.↗
NASA NTRSDate not supplied

Bootstrapping Multi-Agent Unmanned Aerial Vehicle (UAV) System Integration Using Ground-Based Assets: Lessons Learned

The highly dynamic nature of UAVs imposes significant challenges when conducting initial testing ranging from safety risks posed by high-capacity lithium batteries and spinning propellers to rigorous timing demands on controllers and the consequences of failures mid-air. Flight testing of a single vehicle is time and labor intensive due to these challenges and more, and the complexity increases exponentially with the number of vehicles. While simulations and hardware-in-the-loop bench testing can provide adequate environments for preliminary validation, differences in system deployment architecture, software interfaces, and hardware infrastructure between simulation and a fleet of real UAVs create a sizable gap that must be navigated carefully during system integration. In support of the Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project, which had the goal of establishing a basis of certification of trust and trustworthiness in multi-agent autonomous systems, this gap was tackled from two directions. First, a novel mixed-reality simulation environment was engineered to blur the transition from simulation to flight hardware. Second, a fleet of Unmanned Surface Vehicles (USVs) was developed as a test and evaluation platform that more closely represented the final aerial fleet while eliminating many of the risks associated with air vehicles. This paper delves into the second element, analyzing the efficacy of the USV platform in performing system integration testing for the UAV system. In this paper we present the USV fleet and its role in reducing the aforementioned gaps in deployment architecture, software interfaces, and hardware infrastructure when moving from simulation to flight. An overview of the hardware and software onboard the vehicles will be provided along with supporting infrastructure. The system integration process will be documented including results in supporting both the overarching design reference mission (DRM) of ATTRACTOR and individual research efforts conducted during the project. Finally, we will discuss some of the practical lessons learned regarding the testing, deployment, and operation of multi-agent autonomous systems.

Matthew P Vaughan↗
NASA NTRS2011

Sitting in the Pilot's Seat; Optimizing Human-Systems Interfaces for Unmanned Aerial Vehicles

One of the pilot-machine interfaces (the forward viewing camera display) for an Unmanned Aerial Vehicle called the DROID (Dryden Remotely Operated Integrated Drone) will be analyzed for optimization. The goal is to create a visual display for the pilot that as closely resembles an out-the-window view as possible. There are currently no standard guidelines for designing pilot-machine interfaces for UAVs. Typically, UAV camera views have a narrow field, which limits the situational awareness (SA) of the pilot. Also, at this time, pilot-UAV interfaces often use displays that have a diagonal length of around 20". Using a small display may result in a distorted and disproportional view for UAV pilots. Making use of a larger display and a camera lens with a wider field of view may minimize the occurrences of pilot error associated with the inability to see "out the window" as in a manned airplane. It is predicted that the pilot will have a less distorted view of the DROID s surroundings, quicker response times and more stable vehicle control. If the experimental results validate this concept, other UAV pilot-machine interfaces will be improved with this design methodology.

Queen, Steven M.↗
DOE OSTI2024

Autonomous Emergency Landing for Fixed-Wing Aircraft with Energy-Constrained Closed-Loop Prediction

Here this paper presents a new approach for autonomous motion planning for aircraft suffering from a loss-of-thrust emergency. Specifically, we show how modifications to the Closed-Loop Rapidly exploring Random Trees (CL-RRT) framework combined with controlled energy dissipation can enable rapid and effective kinodynamic motion planning. This CL-RRT Glide algorithm uses closed-loop prediction not only for node connections but also to estimate the remaining energy and prune infeasible paths. This greatly speeds up the search process, which is essential for emergency situations. In addition, we improve the ability of the gliding aircraft to reach a goal position and energy state. We do so by creating a Dissipative Total Energy Control Scheme (TECS). Dissipative TECS enables the glider to lose excess altitude in order to reach a desired energy level. Simulation results illustrate how the proposed methods enable faster motion planning. We also integrate the system into a small unmanned aerial vehicle system and experimentally demonstrate autonomous glide planning and execution during a motor-failure event. This type of algorithm can primarily benefit unmanned aircraft but can also serve to assist pilots in stressful emergency situations.

42 ENGINEERING↗
DOE OSTI2021

Building envelope anomaly characterization and simulation using drone time-lapse thermography

Defects in building envelopes deteriorate over time without being visible to the human eye, while significantly impacting energy performance due to unaccounted heat transfer. Defects can be characterized in the infrared (IR) spectrum. However, IR readings are typically recorded at singular points in time, when in several cases anomalies can only be revealed at specific times of the day, possibly in different seasons of the year. This paper presents a novel workflow for 3D envelope defect characterization and modeling using aerial time-lapse IR data collection using drones. A comprehensive envelope thermal profile is developed for a case study building employing the photogrammetry software Agisoft Photoscan, which generates temporal IR inspections of building skins using multiple thermography orthomosaics. Point-cloud data is then translated into a CAD model and thermal zones for whole Building Energy Modeling (BEM) using Honeybee as a frontend to EnergyPlus to showcase the potential of inclusion of detailed 4D data. Envelope contributions in this case study’s anomalies showed heat losses of 6447.6 kWh, and Energy Use Intensity (EUI) differences of ~2 kWh/m 2 /year from the baseline. Finally, why there is currently little translation of this work in BEM software is discussed, while identifying limitations and future research in the employment of time-lapse thermography using drones for more accurate building envelope inspection and modeling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2014

UAS Integration into the NAS: Phase 1 Human Systems Integration Activities

This presentation addresses the work conducted by the Human Systems Integration (HSI) subproject during Phase 1 of the UAS in the NAS project. This includes information on the HSI technical barriers to UAS integration into the NAS, as well as the HSI objectives that address these barriers. The presentation includes brief discussions of the human-in-the-loop simulations conducted by HSI in Phase 1 and concludes with a look at the activities planned for Phase 2.

human-systems integration↗
NASA NTRSDate not supplied

Intelligent Change Detection System: Autonomous Intelligent Machine Agent Model Development

NASA’s significant role in facilitating the harmonious integration of unmanned aircraft systems (UAS), with other aerial vehicles operating in the National Airspace System (NAS), has revealed a need for more advanced technological tools than are being utilized currently. This technology would lend itself to significantly assisting Direct-Action Aviation Personnel (DAAP) with the ingress and egress of UAS operations within the NAS. Providing research findings that would reduce technical barriers, associated with UAS-NAS integration, has been a persistent effort by both NASA and the FAA. One such research effort, pursued by NASA’s Transformative Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) project, is the development of an autonomous intelligent machine (AIM) agent that would aid DAAP functioning as implemented in remote ground control stations (RGCS). This evolution of the “human-machine” symbiosis, within the aviation environment, is necessary for many reasons. For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs. It is evident, that due to the projected increase of UASs and their generated data, the human-agent’s data managing capabilities will be quickly overwhelmed by the enormous amounts of data emanating in the NAS. The research efforts presented in this paper puts forward results from the development, assessment, and verification of a previously conceptualized AIM-Agent that combats actionable-data (information) errors resulting from the visual perception phenomenon known as “change blindness” (CB). CB has been identified as one of the main culprits of information erroring encountered within the ground control station operator (GCSO) community.

Change Blindness↗
DOE OSTI2023

ARM Aerial Facility (AAF) - Unmanned Aircraft Systems, Cloud Droplet Probe

The Cloud Droplet Probe (CDP) is designed to measure cloud droplet size distribution from 2 µm to 50 µm. The CDP and an appropriate data system can also calculate various other parameters including particle concentrations, effective diameter (ED), Median Volume Diameter (MVD), and Liquid Water Content (LWC).

54 ENVIRONMENTAL SCIENCES↗