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Results for “Unmanned Aerial Vehicles (UAV)”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

The Altus Cumulus Electrification Study (ACES): A UAV-Based Science Demonstration

The Altus Cumulus Electrification Study (ACES) is an unmanned aerial vehicle (UAV)- based project that investigated thunderstorms in the vicinity of the Florida Everglades in August 2002. ACES was conducted to investigate storm electrical activity and its relationship to storm morphology, and to validate satellite-based lightning measurements. In addition, as part of the NASA sponsored UAV-based science demonstration program, this project provided a scientifically useful demonstration of the utility and promise of UAV platforms for Earth science and applications observations. ACES employed the Altus II aircraft, built by General Atomics - Aeronautical Systems, Inc. Key science objectives simultaneously addressed by ACES are to: (1) investigate lightning-storm relationships, (2) study storm electrical budgets, and provide Lightning Imaging Sensor validation. The ACES payload included electrical, magnetic, and optical sensors to remotely characterize the lightning activity and the electrical environment within and around thunderstorms. ACES contributed important electrical and optical measurements not available from other sources. Also, the high altitude vantage point of the UAV observing platform (up to 55,000 feet) provided cloud-top perspective. By taking advantage of its slow flight speed (70 to 100 knots), long endurance, and high altitude flight, the Altus was flown near, and when possible, over (but never into) thunderstorms for long periods of time that allowed investigations to be conducted over entire storm life cycles. An innovative real time weather system was used to identify and vector the aircraft to selected thunderstorms and safely fly around these storms, while, at the same time monitor the weather near our base of operations. In addition, concurrent ground-based observations that included radar (Miami and Key West WSRBD, NASA NPOL), satellite imagery, and lightning (NALDN and Los Alamos EDOT) enable the UAV measurements to be more completely interpreted and evaluated in the context of the thunderstorm structure, evolution, and environment.

Blakeslee, R. J.↗
DOE OSTI2020

Data Exploration of UAV Flights Recorded on Smartphones

The increasing accessibility and technological advancements of unmanned aerial vehicles (UAVs) pose legitimate concerns to nuclear non-proliferation efforts. To deter and combat unwanted or nefarious UAV activity near or around nuclear sensitive sites, the ability to quickly and easily detect drones becomes vital. Our team is exploring the use of ubiquitous smartphones as multi-modal sensors (microphone, accelerometer, gyroscope, etc.) to meet this challenge. In conjunction with Idaho National Lab, two UAV flight tests and one stationary in-air test were conducted and recorded with eight Samsung Galaxy S8 smartphones. This work presents initial characterization and annotation of acoustic signals associated with UAV activity.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRSDate not supplied

3D Representation of UAV-obstacle Collision Risk Under Off-nominal Conditions

Safe operations of autonomous unmanned aerial vehicles (UAVs) in low-altitude airspace with beyond visual line-of-sight (BVLOS) flights demand robust risk monitoring of airspace as well as of people and property on ground. One of the safety critical factors for UAV flights is the risk of collision with static and dynamic obstacles in proximity to its flight path. This paper presents a detailed formulation of risk of obstacle collision incorporating the effects of off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts. The risk is represented in terms of a matrix with rows corresponding to the likelihood of occurrence of collision and columns representing severity of collision to the vehicle and surrounding structures. Risk likelihood is generated using a Bayesian Belief Network (BBN) that compiles knowledge from related Failure Modes and Effects Analysis (FMEAs) and Subject Matter Experts (SMEs) to determine the probability of collision based on on-board sensor measurements indicative of vehicle health and controllability. Risk severity is computed utilizing a point-mass 3D kinematic model of the vehicle in presence of wind. The proposed risk factor is demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in presence of simulated obstacles and wind conditions. Effect of varying wind conditions, level of controllability and obstacle measurement noise on the risk factor is demonstrated. The proposed approach enables risk-informed decision making for timely mitigation of current and future unsafe events in autonomous systems.

risk analysis↗
NASA NTRS2016

Spline Trajectory Algorithm Development: Bezier Curve Control Point Generation for UAVs

A greater need for sophisticated autonomous piloting systems has risen in direct correlation with the ubiquity of Unmanned Aerial Vehicle (UAV) technology. Whether surveying unknown or unexplored areas of the world, collecting scientific data from regions in which humans are typically incapable of entering, locating lost or wanted persons, or delivering emergency supplies, an unmanned vehicle moving in close proximity to people and other vehicles, should fly smoothly and predictably. The mathematical application of spline interpolation can play an important role in autopilots' on-board trajectory planning. Spline interpolation allows for the connection of Three-Dimensional Euclidean Space coordinates through a continuous set of smooth curves. This paper explores the motivation, application, and methodology used to compute the spline control points, which shape the curves in such a way that the autopilot trajectory is able to meet vehicle-dynamics limitations. The spline algorithms developed used to generate these curves supply autopilots with the information necessary to compute vehicle paths through a set of coordinate waypoints.

Howell, Lauren R.↗
NASA NTRSDate not supplied

3D Representation of UAV-obstacle Collision Risk under off-nominal conditions

Safe operations of autonomous unmanned aerial vehicles (UAVs) in low-altitude airspace with beyond visual line-of-sight (BVLOS) flights demand robust risk monitoring of airspace as well as of people and property on ground. One of the safety critical factors for UAV flights is the risk of collision with static and dynamic obstacles in proximity to its flight path. This paper presents a detailed formulation of risk likelihood of obstacle collision incorporating the effects of off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts. The deviation in the planned trajectory caused due to wind is computed utilizing a point-mass 3D kinematic simulation model of the vehicle. Likelihood of risk for the flight plan is then analyzed based on generating the probability of collision for each point in the trajectory. The proposed risk factor is demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in presence of simulated obstacles and wind conditions. Effect of varying wind conditions, distance from obstacles, level of controllability and obstacle measurement noise on the risk factor is demonstrated. The proposed approach enables risk-informed decision making for timely mitigation of current and future unsafe events in autonomous systems.

Portia Banerjee↗
NASA NTRS2023

Vibration Anomaly Indicator in UAVs in presence of Wind

One of the critical factors affecting flight safety of unmanned aerial vehicles (UAVs) is the amount of vibration they are exposed during a flight. For UAVs under remote operation, vehicle stabilization and navigation is typically achieved by estimating its attitude and position using onboard miniature sensors such as accelerometers, gyroscopes, and GPS via an onboard autopilot. Since precise control of the UAV relies heavily on the attitude sensing, the vibration levels need to be as low as possible in order to minimize the signal noise. Incorrect sensor data can lead to uncertain state estimation causing the multirotor to drift from its desired position. Moreover, high vibrations can induce faults in the safety-critical components of the UAV such as its on-board sensors, motors and propellers. Hence, it is important to monitor the vibration levels during a UAV flight. This paper specifically looks into effect of wind on the vibrations recorded by the autopilot system in an octocopter. Using data from experimental flights under varying wind conditions, we aim to classify between a nominal and anomalous vibration level and define a safety metric known as the Vibrational Anomaly Indicator (VAI) for small UAV systems. Further, we will study effect of high vibrations on the inertial measurement unit (IMU) of an octocopter under laboratory set-up and compute the VAI from IMU measurements. Results would demonstrate the utility of VAI as an health indicator for unmanned flights either in presence of winds or from degraded on-board IMU sensor.

Vibration↗
NASA NTRS2005

Development of a Low-Cost UAV Doppler Radar Data System

A viewgraph presentation on the design of a low cost unmanned aerial vehicle (UAV) doppler radar data system is presented. The topics include: 1) Science and Mission Background; 2) Radar Requirements and Specs; 3) Radar Realization: RF System; 4) Processing of RF Signal; 5) Data System Design Process; 6) Can We Remove the DSP? 7) Determining Approximate Speed Requirements; 8) Radar Realization: Data System; 9) Data System Operation; and 10) Results.

Knuble, Joseph↗
NASA NTRS2015

EM Modeling of Far-Field Radiation Patterns for Antennas on the GMA-TT UAV

To optimize communication with the Generic Modular Aircraft T-Tail (GMA-TT) unmanned aerial vehicle (UAV), electromagnetic (EM) simulations have been performed to predict the performance of two antenna types on the aircraft. Simulated far-field radiation patterns tell the amount of power radiated by the antennas and the aircraft together, taking into account blockage by the aircraft as well as radiation by conducting and dielectric portions of the aircraft. With a knowledge of the polarization and distance of the two communicating antennas, e.g. one on the UAV and one on the ground, and the transmitted signal strength, a calculation may be performed to find the strength of the signal travelling from one antenna to the other and to check that the transmitted signal meets the receiver system requirements for the designated range. In order to do this, the antenna frequency and polarization must be known for each antenna, in addition to its design and location. The permittivity, permeability, and geometry of the UAV components must also be known. The full-wave method of moments solution produces the appropriate dBi radiation pattern in which the received signal strength is calculated relative to that of an isotropic radiator.

Mackenzie, Anne I.↗
NASA NTRS2005

A Collaborative Decision Environment for UAV Operations

NASA is developing Intelligent Mission Management (IMM) technology for science missions employing long endurance unmanned aerial vehicles (UAV's). The IMM groundbased component is the Collaborative Decision Environment (CDE), a ground system that provides the Mission/Science team with situational awareness, collaboration, and decisionmaking tools. The CDE is used for pre-flight planning, mission monitoring, and visualization of acquired data. It integrates external data products used for planning and executing a mission, such as weather, satellite data products, and topographic maps by leveraging established and emerging Open Geospatial Consortium (OGC) standards to acquire external data products via the Internet, and an industry standard geographic information system (GIs) toolkit for visualization As a Science/Mission team may be geographically dispersed, the CDE is capable of providing access to remote users across wide area networks using Web Services technology. A prototype CDE is being developed for an instrument checkout flight on a manned aircraft in the fall of 2005, in preparation for a full deployment in support of the US Forest Service and NASA Ames Western States Fire Mission in 2006.

D'Ortenzio, Matthew V.↗
NASA NTRS2018

High-Fidelity Computational Aerodynamics of the Elytron 4S UAV

High-fidelity Computational Fluid Dynamics (CFD) have been carried out for the Elytron 4S Unmanned Aerial Vehicle (UAV), also known as the converticopter "proto12". It is the scaled wind tunnel model of the Elytron 4S, an Urban Air Mobility (UAM) concept, a tilt-wing, box-wing rotorcraft capable of Vertical Take-Off and Landing (VTOL). The three-dimensional unsteady Navier-Stokes equations are solved on overset grids employing high-order accurate schemes, dual-time stepping, and a hybrid turbulence model using NASA's CFD code OVERFLOW. The Elytron 4S UAV has been simulated in airplane mode and in helicopter mode.

High-Fidelity↗
NASA NTRS2019

Real-Time UAV Trajectory Prediction for Safety Monitoring in Low-Altitude Airspace

The rising number of small unmanned aerial vehicles (UAVs) expected in the next decade will enable a new series of commercial, service, and military operations in low altitude airspace as well as above densely populated areas. These operations may include on-demand delivery, medical transportation services, law enforcement operations, traffic surveillance and many more. Such unprecedented scenarios create the need for robust, efficient ways to monitor the UAV state in time to guarantee safety and mitigate contingencies throughout the operations. This work proposes a generalized monitoring and prediction methodology that utilizes realtime measurements of an autonomous UAV following a series of way-points. Two different methods, based on sinusoidal acceleration profiles and high-order splines, are utilized to generate the predicted path. The monitoring approach includes dynamic trajectory re-planning in the event of unexpected detour or hovering of the UAV during flight. It can be further extended to different vehicle types, to quantify uncertainty affecting the state variables, e.g., aerodynamic and other environmental effects, and can also be implemented to prognosticate safety-critical metrics which depend on the estimated flight path and required thrust. The proposed framework is implemented on a simplified, scalable UAV modeling and control system traversing 3D trajectories. Results presented include examples of real-time predictions of the UAV trajectories during flight and a critical analysis of the proposed scenarios under uncertainty constraints.

UAV trajectory prognosis↗
DOE OSTI2021

Inferring UAV Position Relative to Smartphone Sensor Based on Acoustic Characteristics

As commercial and non-commercial unmanned aerial vehicles (UAVs) improve technologically and increase in accessibility, their potential for use in actions antithetical to nuclear non-proliferation efforts increases as well. The ability to identify and locate UAVs using ubiquitous, inexpensive hardware and software would be advantageous as both a deterrent and an initial warning system. Our team looks to utilize smartphones as acoustic sensors to record and characterize UAV movement based on the sound produced while in flight. Multi-rotor UAVs produce identifiable acoustic spectral characteristics with frequencies and harmonics corresponding to motor revolutions per minute and the propeller characteristics. As the source moves closer to the receiver these spectral patterns remain relatively stable (at slow speeds), while the energy observed from the waves increases. The goal of this work is to utilize a small network of smartphone sensors with known, fixed positions to infer the relative position of an in-flight UAV with respect to the position of the smartphones through the variation in acoustic energy.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRS2018

Conformal Lightweight Antenna Structures for Aeronautical Communication Technologies

This project is to develop antennas which enable beyond line of sight (BLOS) command and control for UAVs (Unmanned Aerial Vehicles). We will take advantage of newly assigned provisional Ku-band spectrum for UAVs and use unique antenna designs to avoid interference with ground systems. This will involve designing antennas with high isotropic effective radiated power (EIRP) and ultra-low sidelobes. The antennas will be made with polymer aerogel as a substrate to both reduce weight and improve performance, as demonstrated in an Aero Seedling. In addition, designing the antennas to be conformal to the aircraft fuselage will reduce drag.

aerogels↗
DOE OSTI2020

Analysis of Double-Output CLL Resonant Converter for All-Electric UAV Applications

This paper presents a double-output resonant converter with high-frequency isolation for unmanned aerial vehicle (UAV) applications. The proposed topology is developed by using a full-bridge resonant inverter and double-output half-bridge active rectifiers. For the control system, a phase-shifted pulse width modulation (PS-PWM) method is utilized to adjusts the power flow among the output rectifiers in a wide voltage range regulation with a central control. The theoretical analysis of the converter is explored using the system model under different load conditions with constant frequency. The proposed system is validated with experimental results using 60 V input source and generating 0 - 100 V in each output at a full power of 500 W with 96% maximum efficiency in the laboratory experimental setup.

Asa, Erdem↗
DOE OSTI2026

A System Level Comparative Study of SecondarySide Rectifiers for UAV Wireless Power Transfer in High-Altitude Airborne Energy Platforms

Wireless power transfer (WPT) systems for unmanned aerial vehicles (UAVs) must satisfy stringent design requirements to ensure reliable operation under constraints related to efficiency, thermal performance, altitude, weight, and reliability, particularly in airborne and high-altitude environments. Thermal management becomes increasingly challenging at higher altitudes due to reduced air density, while reliability is strongly affected by the number and complexity of active components. The weight and compactness of secondary-side rectifiers directly impact UAV flight endurance and system integration, influencing energy consumption and payload allocation. These factors collectively define the practical feasibility of UAV WPT systems and guide rectifier topology selection. This paper presents a comparative and experimentally validated evaluation framework for secondary-side rectifiers under UAV-specific constraints. Three representative rectifier architectures are analyzed using component-based assessment of weight, thermal behavior, and reliability, together with experimental efficiency measurements obtained from a 1 kW WPT prototype. The results show that the single-switch active rectifier achieves the highest peak efficiency of approximately 93.2% and an overall efficiency of 91%, while also offering advantages in weight and reliability. The findings demonstrate how constraint-oriented analysis, combined with experimental validation, enables informed selection of secondary-side rectifiers for UAV wireless power transfer applications, including emerging airborne and high-altitude platforms.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
NASA NTRS1997

The UAV: A unique platform for electrodynamic studies of upward lightning in the middle atmosphere

The use of unmanned aerial vehicles (UAVs), a platform for investigations in an environment hostile to manned spacecraft, is discussed. A program which includes the use of UAVs coupled with ground-based measurements to conduct scientific studies on the electrical state of the atmosphere during electrically active periods is proposed. The radiating power from alternate current and transient components of the storm electrification was investigated.

Goldberg, Richard A.↗
NASA NTRS2014

Towards a Biosynthetic UAV

We are currently working on a series of projects towards the construction of a fully biological unmanned aerial vehicle (UAV) for use in scientific and humanitarian missions. The prospect of a biologically-produced UAV presents numerous advantages over the current manufacturing paradigm. First, a foundational architecture built by cells allows for construction or repair in locations where it would be difficult to bring traditional tools of production. Second, a major limitation of current research with UAVs is the size and high power consumption of analytical instruments, which require bulky electrical components and large fuselages to support their weight. By moving these functions into cells with biosensing capabilities - for example, a series of cells engineered to report GFP, green fluorescent protein, when conditions exceed a certain threshold concentration of a compound of interest, enabling their detection post-flight - these problems of scale can be avoided. To this end, we are working to engineer cells to synthesize cellulose acetate as a novel bioplastic, characterize biological methods of waterproofing the material, and program this material's systemic biodegradation. In addition, we aim to use an "amberless" system to prevent horizontal gene transfer from live cells on the material to microorganisms in the flight environment.

Biological↗
NASA NTRSDate not supplied

Uncertainty Quantification of Expected Time-of-Arrival in UAV Flight Trajectory

One of the foremost requirements for accurate in-flight safety monitoring of autonomous unmanned aerial vehicles (UAVs) is tracking of their flight trajectory. Existing UAVs leverage autonomous flight functionalities based on trajectory generation algorithms developed in robotic applications such as polynomial or spline curves in order to facilitate kinematic smoothness, minimum vibrations and fuel efficiency. However in practice, the actual path may be subjected to unexpected local weather conditions, unexpected obstacles along the path or abrupt traffic changes in the low-altitude airspace resulting in large errors of the predicted time-of-arrival at way-points. In this study, an approach to quantify and propagate uncertainty in 4D trajectories is proposed. The paper presents a simple error interval propagation method based on the expected cruise speed of the UAV and its associated uncertainty. The uncertainty is then propagated in time to estimate reasonable confidence intervals on the times-of-arrival of the vehicle at each way-point as well as along the entire flight-path. The uncertainty propagation is demonstrated on a state-of-the-art trajectory generation algorithm based on non-uniform rational B-spline (NURBS) curves. Further, the effect of a stationary wind field is incorporated in the uncertainty propagation approach. The proposed method is implemented on synthetic and real data obtained from flight experiments with a small UAV.

Uncertainty Quantification↗