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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Self-Contained Avionics Sensing and Flight Control System for Small Unmanned Aerial Vehicle

A self-contained avionics sensing and flight control system is provided for an unmanned aerial vehicle (UAV). The system includes sensors for sensing flight control parameters and surveillance parameters, and a Global Positioning System (GPS) receiver. Flight control parameters and location signals are processed to generate flight control signals. A Field Programmable Gate Array (FPGA) is configured to provide a look-up table storing sets of values with each set being associated with a servo mechanism mounted on the UAV and with each value in each set indicating a unique duty cycle for the servo mechanism associated therewith. Each value in each set is further indexed to a bit position indicative of a unique percentage of a maximum duty cycle for the servo mechanism associated therewith. The FPGA is further configured to provide a plurality of pulse width modulation (PWM) generators coupled to the look-up table. Each PWM generator is associated with and adapted to be coupled to one of the servo mechanisms.

Shams, Qamar A.↗
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.↗
NASA NTRSDate not supplied

Uncertainty Propagation in Pre-Flight Prediction of Unmanned Aerial Vehicle Separation Violation

Current forecasts on the future of aeronautics suggest an in- creasing number of unmanned aerial vehicles entering the low- altitude airspace in the next decades (FAA, 2018; Kopardekar et al., 2016). Small vehicles for package delivery as well as larger vehicles for urban air mobility will change the airspace drastically, increasing density of operations both in time, i.e. high number of take-off and landings per unit time, and in space, operating in dense urban environment. This scenario poses challenges to the current approach to air traffic control, and large efforts from academia, industry and regulatory bodies are dedicated to the development of new traffic management strategies that leverage higher computing and simulating capabilities available today. In this paper, we propose a simple look-ahead approach to predict potential minimum separation violations at the strategic level, that is before vehicles start flying, depending on the predefined 4D trajectories and uncertainty affecting the wind acting along those routes. The wind field is extracted from the NOAA North America Mesoscale Forecast System and interpolated using Gaussian process regression, while uncertainty affecting the expected cruise airspeed is propagated through error intervals. The approach allows the prediction of aircraft separation as a function of time, highlighting potential safety violations that would go undetected if uncertainty affecting the expected 4D trajectories is not considered. The paper will also discuss issues related to accuracy and scalability of the approach to multiple vehicle operations.

Trajectory Prediction↗
NASA NTRSDate not supplied

A Review of Unmanned Aerial Vehicle Technology in Power Line Inspection

The electric power industry is one of the heaviest adopters of Unmanned Aerial Vehicles (UAV) technology, utilizing their versatility to enhance power line maintenance programs. For reliable power grids, routine maintenance operations and rapid repair operations are required across substantial geographical distances. Both maintenance and repair decisions are driven by assessment operations, such as inspections of mechanical structures with visible-band sensors, inspections for the presence of high voltage coronas and hot spots with multispectral sensors, and surveying of equipment and adjacent features (particularly vegetation) with photogrammetric and Light Detection and Ranging (LiDAR) sensors. Assessment was historically accomplished with manned helicopter flights or foot patrols. Recently, this critical economic segment harnessed advances in Unmanned Aerial Systems (UAS)technology to accomplish assessment tasks with faster results, lower cost, and higher levels of safety than historical methods. Adoption of UAVs in high-voltage electric power transmission activities is well underway. Adoption of UAVs for low voltage distribution activities is still emerging, with the important exception of post-storm damage assessment following major hurricanes (Harvey and Maria in 2017 and Michael in 2018). This report reviews the broad UAS adoption in high-voltage electric power transmission operations and early attempts at adoption in distribution operations. The ability to fly beyond visual line of sight (BVLOS) may increase the advantages of UAV inspection over former options, and in the United States, regulators have approved two pilot projects to demonstrate BVLOS methods and their benefits in operating and maintaining the power grid.

UAV↗
NASA NTRS2018

High-Fidelity Computational Aerodynamics of Multi-Rotor Unmanned Aerial Vehicles

High-fidelity Computational Fluid Dynamics (CFD) simulations have been carried out for several multi-rotor Unmanned Aerial Vehicles (UAVs). Three vehicles have been studied: the classic quadcopter DJI Phantom 3, an unconventional quadcopter specialized for forward flight, the SUI Endurance, and an innovative concept for Urban Air Mobility (UAM), the Elytron 4S UAV. The three-dimensional unsteady Navier-Stokes equations are solved on overset grids using high-order accurate schemes, dual-time stepping, and a hybrid turbulence model. The DJI Phantom 3 is simulated with different rotors and with both a simplified airframe and the real airframe including landing gear and a camera. The effects of weather are studied for the DJI Phantom 3 quadcopter in hover. The SUI En- durance original design is compared in forward flight to a new configuration conceived by the authors, the hybrid configuration, which gives a large improvement in forward thrust. The Elytron 4S UAV is simulated in helicopter mode and in airplane mode. Understanding the complex flows in multi-rotor vehicles will help design quieter, safer, and more efficient future drones and UAM vehicles.

High-Fidelity↗
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 NTRS2010

Conceptual Design of a Vertical Takeoff and Landing Unmanned Aerial Vehicle with 24-HR Endurance

This paper describes a conceptual design study for a vertical takeoff and landing (VTOL) unmanned aerial vehicle (UAV) that is able to carry a 25-lb science payload for 24 hr and is able to land and take off at elevations as high as 15,000 ft without human intervention. In addition to the science payload, this vehicle must be able to carry a satellite communication system, and the vehicle must be able to be transported in a standard full-size pickup truck and assembled by only two operators. This project started with a brainstorming phase to devise possible vehicle configurations that might satisfy the requirements. A down select was performed to select a near-term solution and two advanced vehicle concepts that are better suited to the intent of the mission. Sensitivity analyses were also performed on the requirements and the technology levels to obtain a better understanding of the design space. This study found that within the study assumptions the mission is feasible; the selected concepts are recommended for further development.

Fredericks, William J.↗
NASA NTRS2011

Delivery of Unmanned Aerial Vehicle Data

To support much of NASA's Upper Atmosphere Research Program science, NASA has acquired two Global Hawk Unmanned Aerial Vehicles (UAVs). Two major missions are currently planned using the Global Hawk: the Global Hawk Pacific (GloPac) and the Genesis and Rapid Intensification Processes (GRIP) missions. This paper briefly describes GloPac and GRIP, the concept of operations and the resulting requirements and communication architectures. Also discussed are requirements for future missions that may use satellite systems and networks owned and operated by third parties.

Ivancic, William D.↗
NASA NTRS2018

Auralization of an Unmanned Aerial Vehicle Under Propeller Phase Control

Community noise has been identified as a major barrier to entry into service of unmanned aerial vehicle platforms. Common among such vehicle architectures is a distributed electric propulsion system, in which many propellers and/or rotors are used for thrust and/or lift. A promising noise reduction technique was recently developed to favorably modify the vehicle source noise directivity, by adjusting the relative azimuthal position of the prop/rotor blades between propulsors. Un- der idealized conditions, such phase control can yield noise reductions on the order of 20 dB at a ground observer relative to the average case having a random phase distribution. However, human perception of the resulting noise may not be fully captured by such a simple acoustic measure. To this end, this paper under- takes the auralization of the tonal vehicle noise. Specifically, total propeller tonal noise is optimized over a set of observer zones, e.g., 45 deg. wedges, around the vehicle. Each zone represents a unique set of relative phases. The forward flight of the vehicle adjacent to a noise-sensitive area is simulated by prescribing a series of zones over the flight path having minimum noise in the direction of the ob- server. Auralizations and their associated metrics are compared with a reference condition.

Pascioni, Kyle A.↗
NASA NTRS2010

Methods for In-Flight Wing Shape Predictions of Highly Flexible Unmanned Aerial Vehicles: Formulation of Ko Displacement Theory

The Ko displacement theory is formulated for a cantilever tubular wing spar under bending, torsion, and combined bending and torsion loading. The Ko displacement equations are expressed in terms of strains measured at multiple sensing stations equally spaced on the surface of the wing spar. The bending and distortion strain data can then be input to the displacement equations to calculate slopes, deflections, and cross-sectional twist angles of the wing spar at the strain-sensing stations for generating the deformed shapes of flexible aircraft wing spars. The displacement equations have been successfully validated for accuracy by finite-element analysis. The Ko displacement theory that has been formulated could also be applied to calculate the deformed shape of simple and tapered beams, plates, and tapered cantilever wing boxes. The Ko displacement theory and associated strain-sensing system (such as fiber optic sensors) form a powerful tool for in-flight deformation monitoring of flexible wings and tails, such as those often employed on unmanned aerial vehicles. Ultimately, the calculated displacement data can be visually displayed in real time to the ground-based pilot for monitoring the deformed shape of unmanned aerial vehicles during flight.

Ko, William L.↗
NASA NTRS2004

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

Dufrene, Warren R., Jr.↗
NASA NTRS2004

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Dufrene, Warren R., Jr.↗
NASA NTRS1994

Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

Photovoltaic electric-powered flight is receiving a great deal of attention in the context of the United States' Unmanned Aerial Vehicle (UAV) program. This paper addresses some of the enabling technical areas and their potential solutions. Of particular interest are the long-duration, high-altitude class of UAV's whose mission it is to achieve altitudes between 60,000 and 100,000 feet, and to remain at those altitudes for prolonged periods performing various mapping and surveillance activities. Addressed herein are studies which reveal the need for extremely light-weight and efficient solar cells, high-efficiency electric motor-driven propeller modules, and power management and distribution control elements. Since the potential payloads vary dramatically in their power consumption and duty cycles, a typical load profile has been selected to provide commonality for the propulsion power comparisons. Since missions vary widely with respect to ground coverage requirements, from repeated orbiting over a localized target to long-distance routes over irregular terrain, we have also averaged the power requirements for on-board guidance and control power, as well as ground control and communication link utilization. In the context of the national technology reinvestment program, wherever possible we modeled components and materials which have been qualified for space and defense applications, yet are compatible with civilian UAV activities. These include, but are not limited to, solar cell developments, electric storage technology for diurnal operation, local and ground communications, power management and distribution, and control servo design. And finally, the results of tests conducted by Wright Laboratory on ultralight, highly efficient MOCVD GaAs solar cells purchased from EPI Materials Ltd. (EML) of the UK are presented. These cells were also used for modeling the flight characteristics of UAV aircraft.

Geis, Jack↗
NASA NTRS1993

Transition aerodynamics for 20-percent-scale VTOL unmanned aerial vehicle

An investigation was conducted in the Langley 14- by 22-Foot Subsonic Tunnel to establish a transition data base for an unmanned aerial vehicle utilizing a powered-lift ejector system and to evaluate alterations to the ejector system for improved vehicle performance. The model used in this investigation was a 20-percent-scale, blended-body, arrow-wing configuration with integrated twin rectangular ejectors. The test was conducted from hover through transition conditions with variations in angle of attack, angle of sideslip, free-stream dynamic pressure, nozzle pressure ratio, and model ground height. Force and moment data along with extensive surface pressure data were obtained. A laser velocimeter technique for measuring inlet flow velocities was demonstrated at a single flow condition, and also a low order panel method was successfully used to numerically simulate the ejector inlet flow.

Kjerstad, Kevin J.↗
NASA NTRSDate not supplied

Hybrid Modeling of Unmanned Aerial Vehicle Electric Powertrain for Fault Detection and Diagnostics

This paper shows the application of hybrid physics-informed machine learning to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived principles and empirical equations, as well as fully connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage. It has already been applied to Li-ion batteries in the past, and in this work, we extend the applications to other components of an electric powertrain, namely electronic speed controller with pulse-width modulation, and brushless DC motor with connected propeller. Training and testing of the model is carried out using experimental data from Li-ion battery discharge and powertrain testing in a laboratory environment.

Physics-Informed Machine Learning↗
NASA NTRS2005

Application of Adaptive Autopilot Designs for an Unmanned Aerial Vehicle

This paper summarizes the application of two adaptive approaches to autopilot design, and presents an evaluation and comparison of the two approaches in simulation for an unmanned aerial vehicle. One approach employs two-stage dynamic inversion and the other employs feedback dynamic inversions based on a command augmentation system. Both are augmented with neural network based adaptive elements. The approaches permit adaptation to both parametric uncertainty and unmodeled dynamics, and incorporate a method that permits adaptation during periods of control saturation. Simulation results for an FQM-117B radio controlled miniature aerial vehicle are presented to illustrate the performance of the neural network based adaptation.

Shin, Yoonghyun↗
NASA NTRS2007

An Analysis of Fuel Cell Options for an All-electric Unmanned Aerial Vehicle

A study was conducted to assess the performance characteristics of both PEM and SOFC-based fuel cell systems for an all-electric high altitude, long endurance Unmanned Aerial Vehicle (UAV). Primary and hybrid systems were considered. Fuel options include methane, hydrogen, and jet fuel. Excel-based models were used to calculate component mass as a function of power level and mission duration. Total system mass and stored volume as a function of mission duration for an aircraft operating at 65 kft altitude were determined and compared.

Kohout, Lisa L.↗