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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
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 NTRS2001

The Altus Cumulus Electrification Study (ACES): A UAV-based Investigation of Thunderstorms

The Altus Cumulus Electrification Study (ACES) is a NASA-sponsored and -led science investigation that utilizes an uninhabited aerial vehicle (UAV) to investigate thunderstorms in the vicinity of the NASA Kennedy Space Center, Florida. As part of NASA's UAV-based science demonstration program, ACES will provide a scientifically useful demonstration of the utility and promise of UAV platforms for Earth science and applications observations. ACES will employ the Altus 11 aircraft, built by General Atomics-Aeronautical Systems, Inc. By taking advantage of its slow flight speed (70 to 100 knots), long endurance, and high-altitude flight (up to 55,000 feet), the Altus will be flown near, and when possible, above (but never into) thunderstorms for long periods of time, allowing investigations to be conducted over entire storm life cycles. Key science objectives simultaneously addressed by ACES are to: (1) investigate lightning-storm relationships, (2) study storm electrical budgets, and (3) provide Lightning Imaging Sensor validation. The ACES payload, already developed and flown on Altus, includes electrical, magnetic, and optical sensors to remotely characterize the lightning activity and the electrical environment within and around thunderstorms. The ACES field campaign will be conducted during July 2002 with a goal of performing 8 to 10 UAV flights. Each flight will require about 4 to 5 hours on station at altitudes from 40,000 ft to 55,000 ft. The ACES team is comprised of scientists from the NASA Marshall Space Flight Center and NASA Goddard Space Flight Centers partnered with General Atomics and IDEA, LLC.

Blakeslee, Richard↗
NASA NTRS2003

UAV Flight Control Using Distributed Actuation and Sensing

An array of effectors and sensors has been designed, tested and implemented on a Blended Wing Body Uninhabited Aerial Vehicle (UAV). This UAV is modified to serve as a flying, controls research, testbed. This effectorhensor array provides for the dynamic vehicle testing of controller designs and the study of decentralized control techniques. Each wing of the UAV is equipped with 12 distributed effectors that comprise a segmented array of independently actuated, contoured control surfaces. A single pressure sensor is installed near the base of each effector to provide a measure of deflections of the effectors. The UAV wings were tested in the North Carolina State University Subsonic Wind Tunnel and the pressure distribution that result from the deflections of the effectors are characterized. The results of the experiments are used to develop a simple, but accurate, prediction method, such that for any arrangement of the effector array the corresponding pressure distribution can be determined. Numerical analysis using the panel code CMARC verifies this prediction method.

Barnwell, William G.↗
NASA NTRS2004

UAVs: Current and Future Use

Uninhabited Aerial Vehicles (UAVs) provide ideal sampling platforms for atmospheric missions. In this presentation, I will: 1) review the atmospheric science missions that have used UAVs, 2) review and describe UAVs, 3) discuss the future of UAVs in atmospheric science missions.

Newman, P.↗
NASA NTRS2005

Development of an Autonomous Lidar Instrument for Use on a UAV Platform in Support of Homeland Security

Researchers at NASA's Goddard Space Flight Center have developed an autonomous aerosol backscatter lidar instrument for use on the high-altitude ER-2 aircraft (for more information please visit http://cpl.gsfc.nasa.gov). Work is currently underway to transfer this instrument to a UAV platform such as Global Hawk. While the NASA applications are Earth science and satellite validation, there is clearly a Homeland Security application for such an instrument. One novel concept is to have a fleet of UAVs stationed around the country, each UAV having a payload including a lidar instrument. In the event of attack, the appropriate UAV(s) could be launched for purposes of, e.g., plume detection and tracking that are critical for decision support. While the existing lidar instrument is not directly capable of biological species discrimination, it is capable of plume tracking and thus can demonstrate to DHS the capabilities and utility of such instruments. Using NASA funding we will have an instrument ready to fly on Global Hawk by end of 2005. We would like to find partners, either within private industry or within DHS who would be willing to contribute aircraft access and flight hours for a demonstration flight. Longer-term partnerships to develop more advanced and more capable types of lidar instruments are also desirable. In this presentation we will detail the existing ER-2 lidar instrument and show measurement results, show the progress made on adapting to the Global Hawk platform, present concepts for DHS uses of such instruments, and openly pursue partnership opportunities.

McGill, Matthew↗
NASA NTRS2020

Vibration-based health characterization of multiple IMUs in UAV applications

Inertial measurement units (IMUs) are vital in UAV navigation for vehicle attitude and position estimation, especially in the frequently-occurring case of temporary loss of GPS capabilities. Degradation in these units could yield inaccurate position estimates, resulting in incorrect input for vehicle control systems. A wide variety of these units exist to meet the needs of UAV operators, general aviation, and military vehicles. In recent decades, lightweight and inexpensive MEMS sensors have grown in popularity with respect to UAVs. Studies into the failure modes of MEMS devices suggest that vibration is one of the leading causes of MEMS degradation. MEMS sensors are generally encased in their own hermetic packaging, as their small size and sensitivity cause them to be particularly vulnerable to air damping and particulate contamination when exposed. Exposure to excessive vibration can cause cracking in this packaging as well as damage to connecting electronics, with recorded results that cause sensors to act outside of their specifications, potentially providing unreliable input to controllers. A prior study from the Politecnico di Torino looked into the degradation of MEMS IMUs, specifically the AXIS-AIS402, for aerospace and vibrating environments. In the study, the authors found that after exposing MEMS IMUs to simulated vibrations from working conditions of aerospace applications, the sensors showed increased noise and increased bias instability. At NASA Ames, several widely-used MEMS IMUs were selected for a new IMU degradation study, comparing accelerometer performance before and after exposure to similar levels of vibration simulating aerospace conditions. The IMUs were selected from the Pixhawk autopilot systems, hobby sUAS, or prior experimental studies at NASA. Additionally, the industrial grade VectorNav-100 IMU was selected as a ground truth reference point to which the performance of the test sensors can be compared. In the study, each sensor is exposed to functional levels of UAV vibration as replicated on a single-frequency vibratory table in the NASA Ames SHARP Laboratory, and each accelerometer is characterized for bias, drift, and noise characteristics both before and after vibratory exposure. The focus of this study is to monitor the health of the IMU sensors and determine if sensor degradation can be detected from output error and frequency spectrum analysis, rather than from microscopic examination of the sensors. In this case, sensor degradation and faulty data can be more easily detectable by non-experts hoping to use these sensors as an important piece of an integrated package. In addition, specific sensor degradation modes potentially leading to in-flight hazards could be identified, such as accelerated levels of drift and altered temperature response. The overall goal of this work is to increase levels of safety for future users of these sensors and to provide a clear analysis of sensor limitations currently lacking in most sensor specification documentation.

IMUs↗
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↗
DOE OSTI2026

Supervised Learning-Based Spatial Position Estimation with Vertical Displacement for Hovering UAV Wireless Power Transfer

This study presents a supervised learning-based spatial position estimation approach for wireless power transfer (WPT) systems supporting hovering unmanned aerial vehicle (UAV) charging. Unlike stationary charging scenarios, hovering UAVs introduce continuous lateral misalignment and vertical displacement, leading to variations in magnetic coupling and reduced power transfer efficiency. To address this challenge, the proposed method estimates the relative spatial position of the receiver coil using only electrical measurements obtained at the secondary side. A supervised learning model is trained to map output voltage and current features to spatial coordinates, enabling position awareness without requiring external sensors, vision systems, or communication links. The sensing functionality is inherently integrated into the WPT system, allowing simultaneous power transfer and localization through the same magnetic interface. Experimental validation is conducted on a laboratory-scale prototype under varying lateral offsets and air-gap conditions. In addition, spline-based interpolation is employed to increase spatial data density for training. The results demonstrate that the proposed framework can capture spatial variations associated with both lateral and vertical displacement, providing reliable position estimation under hovering conditions. This work establishes a hardware-efficient, sensorless solution for UAV wireless charging and serves as a baseline for advanced data-driven position estimation methods in dynamic WPT systems.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2024

Mid-IR UAV-based sensing platform with deep learning to Identify and Quantify Gaseous Emission in Gas Flares

This report details the development and evaluation of a Mid-Infrared (Mid-IR) Unmanned Aerial Vehicle (UAV)-based sensing platform integrated with deep learning algorithms for the identification and quantification of gaseous emissions in gas flares. The project, spearheaded by Omega Optics, Inc., aimed to address environmental monitoring challenges by leveraging advanced photonic technologies and autonomous UAV operations. The research focused on designing, optimizing, and fabricating photonic crystal waveguides and grating couplers to enhance the sensitivity and accuracy of gas detection. A comprehensive drone-based system was developed, featuring a miniaturized sensor, GPS module, and microcontroller communication network for real-time gas concentration monitoring. The system's adaptive sampling algorithm, implemented using the Robot Operating System (ROS), enables autonomous detection and localization of gas emission sources. Preliminary results demonstrate the platform's capability to detect and monitor gas emissions with high precision, cost-effectiveness, and scalability. Future work will expand upon this foundation by introducing 3D wind model-based learning for dynamic environmental conditions and further enhancing the user interface and data processing algorithms to support broader environmental monitoring applications. Overall, this project represents a significant step forward in UAV-based environmental sensing technologies, offering robust solutions for detecting and mitigating the impacts of gaseous emissions on public health and safety.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Implementing Spatio-Temporal 3D-Convolution Neural Networks and UAV Time Series Imagery to Better Predict Lodging Damage in Sorghum

Unmanned aerial vehicle (UAV)-based remote sensing is gaining momentum in a variety of agricultural and environmental applications. Very-high-resolution remote sensing image sets collected repeatedly throughout a crop growing season are becoming increasingly common. Analytical methods able to learn from both spatial and time dimensions of the data may allow for an improved estimation of crop traits, as well as the effects of genetics and the environment on these traits. Multispectral and geometric time series imagery was collected by UAV on 11 dates, along with ground-truth data, in a field trial of 866 genetically diverse biomass sorghum accessions. We compared the performance of Convolution Neural Network (CNN) architectures that used image data from single dates (two spatial dimensions, 2D) versus multiple dates (two spatial dimensions + temporal dimension, 3D) to estimate lodging detection and severity. Lodging was detected with 3D-CNN analysis of time series imagery with 0.88 accuracy, 0.92 Precision, and 0.83 Recall. This outperformed the best 2D-CNN on a single date with 0.85 accuracy, 0.84 Precision, and 0.76 Recall. The variation in lodging severity was estimated by the best 3D-CNN analysis with 9.4% mean absolute error (MAE), 11.9% root mean square error (RMSE), and goodness-of-fit (R2) of 0.76. This was a significant improvement over the best 2D-CNN analysis with 11.84% MAE, 14.91% RMSE, and 0.63 R2. The success of the improved 3D-CNN analysis approach depended on the inclusion of “before and after” data, i.e., images collected on dates before and after the lodging event. The integration of geometric and spectral features with 3D-CNN architecture was also key to the improved assessment of lodging severity, which is an important and difficult-to-assess phenomenon in bioenergy feedstocks such as biomass sorghum. This demonstrates that spatio-temporal CNN architectures based on UAV time series imagery have significant potential to enhance plant phenotyping capabilities in crop breeding and Precision agriculture applications.

3D-convolution neural networks↗
NASA NTRS1997

Electric Power System for High Altitude UAV Technology Survey

Electric powertrain technologies with application to high altitude Unmanned Aerial Vehicles (UAV) are assessed. One hundred twenty five solar electric UAV configurations and missions were simulated. Synergistic design opportunities were investigated with the premise that specific benefits may be realized, for example, if a single component can serve multiple functions, such as a battery being used for energy storage as well as for a structural component of the aircraft. For each UAV mission simulation, the airframe structure, powertrain configuration (type of solar cells, energy storage options) and performance baseline (1997 or 2001) were specified. It has been found that the use of the high efficiency (multijunction) solar cells or the use of the synergistic amorphous silicon solar cell configuration yields aircraft that can accomplish the majority of the missions of interest for any latitude between 0 deg and 55 deg, hence, a single versatile aircraft can be constructed and implemented to accomplish these missions.

Source record↗
NASA NTRS2002

Demonstrating Acquisition of Real-Time Thermal Data Over Fires Utilizing UAVs

A disaster mitigation demonstration, designed to integrate remote-piloted aerial platforms, a thermal infrared imaging payload, over-the-horizon (OTH) data telemetry and advanced image geo-rectification technologies was initiated in 2001. Project FiRE incorporates the use of a remotely piloted Uninhabited Aerial Vehicle (UAV), thermal imagery, and over-the-horizon satellite data telemetry to provide geo-corrected data over a controlled burn, to a fire management community in near real-time. The experiment demonstrated the use of a thermal multi-spectral scanner, integrated on a large payload capacity UAV, distributing data over-the-horizon via satellite communication telemetry equipment, and precision geo-rectification of the resultant data on the ground for data distribution to the Internet. The use of the UAV allowed remote-piloted flight (thereby reducing the potential for loss of human life during hazardous missions), and the ability to "finger and stare" over the fire for extended periods of time (beyond the capabilities of human-pilot endurance). Improved bit-rate capacity telemetry capabilities increased the amount, structure, and information content of the image data relayed to the ground. The integration of precision navigation instrumentation allowed improved accuracies in geo-rectification of the resultant imagery, easing data ingestion and overlay in a GIS framework. We focus on these technological advances and demonstrate how these emerging technologies can be readily integrated to support disaster mitigation and monitoring strategies regionally and nationally.

Ambrosia, Vincent G.↗
NASA NTRS2002

Fielding An Amphibious UAV: Development, Results, and Lessons Learned

This report summarizes the work completed on the design and flight-testing of a small, unmanned, amphibious demonstrator aircraft that flies autonomously. The aircraft named ACAT (Autonomous Cargo Amphibious Transport) is intended to be a large cargo carrying unmanned aircraft that operates from water to avoid airspace and airfield conflict issues between manned and unmanned aircraft. To demonstrate the feasibility of this concept, a demonstrator ACAT was designed, built, and flown that has a six-foot wingspan and can fly autonomously from land or water airfield. The demonstrator was designed for a 1-hour duration and 1-mile telemetry range. A sizing code was used to design the smallest demonstrator UAV to achieve these goals. The final design was a six-foot wingspan, twin hull configuration that distributes the cargo weight across the span, reducing the wing structural weight. The demonstrator airframe was constructed from balsa wood, fiberglass, and plywood. A 4-stroke model airplane engine powered by methanol fuel was mounted in a pylon above the wing and powers the ACAT UAV. Initial flight tests from land and water were conducted under manual radio control and confirmed the amphibious capability of the design. Flight avionics that were developed by MLB for production UAVs were installed in the ACAT demonstrator. The flight software was also enhanced to permit autonomous takeoff and landing from water. A complete autonomous flight from ahard runway was successfully completed on July 5, 2001 and consisted of a take-off, rectangular flight pattern, and landing under complete computer control. A completely autonomous flight that featured a water takeoff and landing was completed on October 4, 2001. This report describes these activities in detail and highlights the challenges encountered and solved during the development of the ACAT demonstrator. hard runway was successfully completed on July 5, 2001 and consisted of a take-off, rectangular flight pattern, and landing under complete computer control. A completely autonomous flight that featured a water takeoff and landing was completed on October 4, 2001. This report describes these activities in detail and highlights the challenges encountered and solved during the development of the ACAT demonstrator.

Pisanich, Greg↗
NASA NTRS2003

Lessons Learned from NASA UAV Science Demonstration Program Missions

During the summer of 2002, two airborne missions were flown as part of a NASA Earth Science Enterprise program to demonstrate the use of uninhabited aerial vehicles (UAVs) to perform earth science. One mission, the Altus Cumulus Electrification Study (ACES), successfully measured lightning storms in the vicinity of Key West, Florida, during storm season using a high-altitude Altus(TM) UAV. In the other, a solar-powered UAV, the Pathfinder Plus, flew a high-resolution imaging mission over coffee fields in Kauai, Hawaii, to help guide the harvest.

Wegener, Steven S.↗
NASA NTRS2003

NASA Earth Science Research and Applications Using UAVs

The NASA Earth Science Enterprise sponsored the UAV Science Demonstration Project, which funded two projects: the Altus Cumulus Electrification Study (ACES) and the UAV Coffee Harvest Optimization experiment. These projects were intended to begin a process of integrating UAVs into the mainstream of NASA s airborne Earth Science Research and Applications programs. The Earth Science Enterprise is moving forward given the positive science results of these demonstration projects to incorporate more platforms with additional scientific utility into the program and to look toward a horizon where the current piloted aircraft may not be able to carry out the science objectives of a mission. Longer duration, extended range, slower aircraft speed, etc. all have scientific advantages in many of the disciplines within Earth Science. The challenge we now face are identifying those capabilities that exist and exploiting them while identifying the gaps. This challenge has two facets: the engineering aspects of redesigning or modifying sensors and a paradigm shift by the scientists.

Guillory, Anthony R.↗
NASA NTRS2005

GPS Remote Sensing Measurements Using Aerosonde UAV

In February 2004, a NASA-Langley GPS Remote Sensor (GPSRS) unit was flown on an Aerosonde unmanned aerial vehicle (UAV) from the Wallops Flight Facility (WFF) in Virginia. Using direct and surface-reflected 1.575 GHz coarse acquisition (C/A) coded GPS signals, remote sensing measurements were obtained over land and portions of open water. The strength of the surface-reflected GPS signal is proportional to the amount of moisture in the surface, and is also influenced by surface roughness. Amplitude and other characteristics of the reflected signal allow an estimate of wind speed over open water. In this paper we provide a synopsis of the instrument accommodation requirements, installation procedures, and preliminary results from what is likely the first-ever flight of a GPS remote sensing instrument on a UAV. The correct operation of the GPSRS unit on this flight indicates that Aerosonde-like UAV's can serve as platforms for future GPS remote sensing science missions.

Grant, Michael S.↗
NASA NTRS2005

Technology Challenges in Small UAV Development

Development of highly capable small UAVs present unique challenges for technology protagonists. Size constraints, the desire for ultra low cost and/or disposable platforms, lack of capable design and analysis tools, and unique mission requirements all add to the level of difficulty in creating state-of-the-art small UAVs. This paper presents the results of several small UAV developments, the difficulties encountered, and proposes a list of technology shortfalls that need to be addressed.

Logan, Michael J.↗
NASA NTRS2006

AirSTAR: A UAV Platform for Flight Dynamics and Control System Testing

As part of the NASA Aviation Safety Program at Langley Research Center, a dynamically scaled unmanned aerial vehicle (UAV) and associated ground based control system are being developed to investigate dynamics modeling and control of large transport vehicles in upset conditions. The UAV is a 5.5% (seven foot wingspan), twin turbine, generic transport aircraft with a sophisticated instrumentation and telemetry package. A ground based, real-time control system is located inside an operations vehicle for the research pilot and associated support personnel. The telemetry system supports over 70 channels of data plus video for the downlink and 30 channels for the control uplink. Data rates are in excess of 200 Hz. Dynamic scaling of the UAV, which includes dimensional, weight, inertial, actuation, and control system scaling, is required so that the sub-scale vehicle will realistically simulate the flight characteristics of the full-scale aircraft. This testbed will be utilized to validate modeling methods, flight dynamics characteristics, and control system designs for large transport aircraft, with the end goal being the development of technologies to reduce the fatal accident rate due to loss-of-control.

Jordan, Thomas L.↗