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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

BOREAS Level-0 C-130 Aerial Photography

For BOReal Ecosystem-Atmosphere Study (BOREAS), C-130 and other aerial photography was collected to provide finely detailed and spatially extensive documentation of the condition of the primary study sites. The NASA C-130 Earth Resources aircraft can accommodate two mapping cameras during flight, each of which can be fitted with 6- or 12-inch focal-length lenses and black-and-white, natural-color, or color-IR film, depending upon requirements. Both cameras were often in operation simultaneously, although sometimes only the lower resolution camera was deployed. When both cameras were in operation, the higher resolution camera was often used in a more limited fashion. The acquired photography covers the period of April to September 1994. The aerial photography was delivered as rolls of large format (9 x 9 inch) color transparency prints, with imagery from multiple missions (hundreds of prints) often contained within a single roll. A total of 1533 frames were collected from the C-130 platform for BOREAS in 1994. Note that the level-0 C-130 transparencies are not contained on the BOREAS CD-ROM set. An inventory file is supplied on the CD-ROM to inform users of all the data that were collected. Some photographic prints were made from the transparencies. In addition, BORIS staff digitized a subset of the tranparencies and stored the images in JPEG format. The CD-ROM set contains a small subset of the collected aerial photography that were the digitally scanned and stored as JPEG files for most tower and auxiliary sites in the NSA and SSA. See Section 15 for information about how to acquire additional imagery.

Newcomer, Jeffrey A.↗
NASA NTRS2007

C-20A/GIII Precision Autopilot Development in Support of NASA's UAVSAR Program

The NASA Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) program is developing a Synthetic Aperture Radar (SAR) for ground measurements. A key element for the success of this program is a Platform Precision Autopilot (PPA). An interim vehicle (NASA C-20AJGlll) was selected to carry the radar pod and develop the PPA. The PPA interfaces with the C- 20AIG Ill aircraft by imitating the output of an Instrument Landing System (ILS) approach. This technique retains the safeguards in the aircraft's autopilot. The PPA entered initial flight testing in early 2007. The PPA uses a Kalman filter to generate a real-time position solution with information from the C-20AIGIII and a real-time differential GPS unit designed by JPL. The real-time navigation solution is used to compute commands (Guidance and Control subsystems) which in turn drive two modified ILS testers. The ILS tester units produce modulated RF signals fed to the onboard navigation receiver. These correction signals allow the C-20NGIII autopilot to fly a simulated ILS approach that meets the PPA requirements for UAVSAR applications. The PPA requirement is to make repeat pass flights within a ten meter tube over a 200 kilometer course in conditions of cairn to light turbulence. Flight test results are expected to be available at the time of the NASA Science Technology Conference 2007

Lee, James A.↗
DOE OSTI2024

Machine and Deep Learning: Artificial Intelligence Application in Biotic and Abiotic Stress Management in Plants

Biotic and abiotic stresses significantly affect plant fitness, resulting in a serious loss in food production. Biotic and abiotic stresses predominantly affect metabolite biosynthesis, gene and protein expression, and genome variations. However, light doses of stress result in the production of positive attributes in crops, like tolerance to stress and biosynthesis of metabolites, called hormesis. Advancement in artificial intelligence (AI) has enabled the development of high-throughput gadgets such as high-resolution imagery sensors and robotic aerial vehicles, i.e., satellites and unmanned aerial vehicles (UAV), to overcome biotic and abiotic stresses. These High throughput (HTP) gadgets produce accurate but big amounts of data. Significant datasets such as transportable array for remotely sensed agriculture and phenotyping reference platform (TERRA-REF) have been developed to forecast abiotic stresses and early detection of biotic stresses. For accurately measuring the model plant stress, tools like Deep Learning (DL) and Machine Learning (ML) have enabled early detection of desirable traits in a large population of breeding material and mitigate plant stresses. In this review, advanced applications of ML and DL in plant biotic and abiotic stress management have been summarized.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

Verification of Prognostic Algorithms to Predict Remaining Flying Time for Electric Unmanned Vehicles

This paper addresses the problem of building trust in the online prediction of a eUAV’s remaining available flying time powered by lithium-ion polymer batteries. A series of ground tests are described that make use of an electric unmanned aerial vehicle (eUAV) to verify the performance of remaining flying time predictions. The algorithm verification procedure described is implemented on a fully functional vehicle that is restrained to a platform for repeated run-to-functional-failure (charge depletion) experiments. The vehicle under test is commanded to follow a predefined propeller RPM profile in order to create battery demand profiles similar to those expected during flight. The eUAV is repeatedly operated until the charge stored in powertrain batteries falls below a specified limit threshold. The time at which the limit threshold on battery charge is crossed is then used to measure the accuracy of the remaining flying time prediction. In our earlier work battery aging was not included. In this work we take into account aging of the batteries where the parameters were updated to make predictions. Accuracy requirements are considered for an alarm that warns operators when remaining flying time is estimated to fall below the specified limit threshold.

Edward F. Hogge↗
NASA NTRS2002

Flexible Wing Base Micro Aerial Vehicles: Micro Air Vehicles (MAVs) for Surveillance and Remote Sensor Delivery

Micro Air Vehicles (MAVs) will be developed for tracking individuals, locating terrorist threats, and delivering remote sensors, for surveillance and chemical/biological agent detection. The tasks are: (1) Develop robust MAV platform capable of carrying sensor payload. (2) Develop fully autonomous capabilities for delivery of sensors to remote and distant locations. The current capabilities and accomplishments are: (1) Operational electric (inaudible) 6-inch MAVs with novel flexible wing, providing superior aerodynamic efficiency and control. (2) Vision-based flight stability and control (from on-board cameras).

Ifju, Peter↗
DOE OSTI2024

Relating Aerial Infrared Thermography Defects to Photovoltaic Performance: Preprint

In this research, we examine the relationship between aerial IR defect analysis and photovoltaic (PV) performance data for twelve utility- and commercial-scale solar sites in the United States. To do this, we fuse the site diagram geoJSON's, aerial infrared thermography (aIRT) defect analyses, and associated inverter time series, allowing for a direct comparison between site defects and time series data. Defect analyses were provided by Zeitview, under its Solar Insights platform. Following the data fusion process, we look at the relationship between system performance and aIRT defects. We investigate the relationship between degradation and hotspot defects, as well as the relationship between AC power data and offline strings and misaligned modules. In general, system degradation was not affected by long-term or balance-of-system (BoS) defects as they occurred infrequently in the data set. However, for one system, a near statistically significant relationship (p-value=0.057) was found when comparing the degradation of inverter blocks with several multi-hotspot defects to all other inverter blocks without this particular defect. There was strong alignment when comparing short-term recoverable module defects such as stuck trackers and offline strings to time series data. In general, we found that when an inverter block has more than 80% of modules flagged for one of these defects, its AC power time data is flat-lined and the inverter block is not producing.

aerial inspection↗
NASA NTRS2006

NASA Dryden Status

This viewgraph presentation reviews the recent activities of NASA Dryden Flight Research Center. Some of the activities are: the delivery of Ikhana, a platform to conduct Earth Science Missions; work on Autonomous Airborne Refueling Demonstration (AARD); progress in developing Quiet Spike, an extendable boom to reduce sonic boom signature; and work on Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and Crew Exploration Vehicle (CEV)

Bosworth, John T.↗
NASA NTRS2017

An Integrated System for Autonomous Search and Track with a Small Unmanned Aerial Vehicle

This article presents a framework for searching, detecting, and tracking an object of interest with a small unmanned aerial vehicle (sUAV). The vehicle is given an area to search for an object of interest. Once the object is detected, the sUAV follows the target while maintaining a fixed distance and centered on its image plane. This paper describes an architecture for integrating autonomy capabilities for search and track for sUAVs. The system has been implemented in the Robot Operating System (ROS) framework using the Parrot ARDrone platform. In this paper we present our technical approach, the system architecture and demonstrate the principles of the approach in a simulation environment and indoor flight tests.

Unmanned Aerial Vehicle↗
NASA NTRS2004

An L-band SAR for repeat pass deformation measurements on a UAV platform

We are proposing to develop a miniaturized polarimetric L-band synthetic aperture radar (SAR) for repeatpass differential interferometric measurements of deformation for rapidly deforming surfaces of geophysical interest such as volcanoes or earthquakes that is to be flown on a unmanned aerial vehicle (UAV or minimally piloted vehicle (MPV).

repeat pass interferometry↗
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 NTRS2020

Autonomous Aerial Vehicles (AAVs) as a Tool for Improving the Spatial Resolution of Snow Albedo Measurements in Mountainous Regions

We present technical advances and methods to measure effective broadband physical albedo in snowy mountain headwaters using a prototype dual-sensor pyranometer mounted on an Autonomous Aerial Vehicle (an AAV). Our test flights over snowy meadows and forested areas performed well during both clear sky and snowy/windy conditions at an elevation of ~2650 m above mean sea level (MSL). Our AAV-pyranometer platform provided high spatial (m) and temporal resolution (sec) measurements of effective broadband (310–2700 nm) surface albedo. The AAV-based measurements reveal spatially explicit changes in landscape albedo that are not present in concurrent satellite measurements from Landsat and MODIS due to a higher spatial resolution. This AAV capability is needed for validation of satellite snow albedo products, especially over variable montane landscapes at spatial scales of critical importance to hydrological applications. Effectively measuring albedo is important, as annually the seasonal accumulation and melt of mountain snowpack represent a dramatic transformation of Earth’s albedo, which directly affects headwaters’ water and energy cycles.

albedo↗
NASA NTRS1979

A Mars Airplane . . . Oh really

This paper describes the mission design, scientific utilization, and prototypical design of a Mars Airplane. As a scientific platform, the airplane provides an excellent means of obtaining data in a resolution range intermediate to surface vehicles and orbiters. It has great versatility to perform a variety of missions: conduct aerial surveys, land instrument packages, collect samples, and perform atmospheric sounding. The Mars Airplane has many characteristics of a competition glider on earth. Two versions of the plane, a cruiser, and one with soft landing and takeoff capability, have been designed. Maximum range and endurance are 10,000 km and 31.1 hours with a 40-kg payload.

Clarke, V. C., Jr.↗
NASA NTRSDate not supplied

Uninhabited Aerial System Drop-in Balloon-Borne Radiosonde Alternative for Lower Tropospheric Flights

Balloon-borne radiosonde sensors are a well characterized way of gathering data into the stratosphere; however, balloon launches have limitations such as the need to replace the balloon and sensors after each flight, as well the overall drift of the balloon over the course of the launch. Using sensors mounted on an uninhabited aerial system (UAS) allows for higher temporal-resolution vertical profiles in the lower troposphere and allows for full control of the flight profile of the sensors. This paper presents a drop-in solution for a balloon-borne radiosonde in which it is mounted on an uninhabited aerial system in lieu of a balloon with an additional connection to a 3D anemometer streaming atmospheric and wind data in near real-time to a ground station. This alternative platform for balloon-borne radiosondes has undergone extensive flight testing with the wind results being compared against a ground-based wind LiDAR for validation and the atmospheric results undergoing further data analysis against a wide variety of sensors for future validation. Indoor tests were also conducted and are discussed in order to determine the propeller’s influence on the anemometer. This alternative platform will allow for higher temporal and spatial resolution of atmospheric data collection in near-real time.

Tyler L. Willhite↗
DOE OSTI2024

Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems

Abstract. Ozone is a pollutant formed in the atmosphere by photochemical processes involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) when exposed to sunlight. Tropospheric boundary layer ozone is regularly measured at ground stations and sampled infrequently through balloon, lidar, and crewed aircraft platforms, which have demonstrated characteristic patterns with altitude. Here, to better resolve vertical profiles of ozone within the atmospheric boundary layer, we developed and evaluated an uncrewed aircraft system (UAS) platform for measuring ozone and meteorological parameters of temperature, pressure, and humidity. To evaluate this approach, a UAS was flown with a portable ozone monitor and a meteorological temperature and humidity sensor to compare to tall tower measurements in northern Wisconsin. In June 2020, as a part of the WiscoDISCO20 campaign, a DJI M600 hexacopter UAS was flown with the same sensors to measure Lake Michigan shoreline ozone concentrations. This latter UAS experiment revealed a low-altitude structure in ozone concentrations in a shoreline environment showing the highest ozone at altitudes from 20–100 m a.g.l. These first such measurements of low-altitude ozone via a UAS in the Great Lakes region revealed a very shallow layer of ozone-rich air lying above the surface.

Meteorology & Atmospheric Sciences↗
NASA NTRS1965

Waveguide feeder system for the Goonhilly satellite-communication earth station

There are two features which distinguish the feeder arrangements at a satellite earth station from those used in conventional microwave line-of-sight links. The first is the importance of low loss in all waveguides and components and the second is the need for rotating joints. Losses are important in the receive direction because they contribute significantly to the overall system noise temperature while, in the transmit direction, not only do they waste expensive transmitter power but localized points of high loss can give rise to the formation of arcs when the power is applied. Rotating joints are required on the elevation axis of the aerial to permit waveguide connection between apparatus in the turntable cabin and on the dish. In the installation at Goonhilly, three separate waveguide connections are required between the turntable cabin and the focus platform; one each for the Telstar and Relay transmitters operating at 6390 and 1725 Mc/s respectively, and one for the receiver feed, routed via the maser cabin on the back of the dish and operating at 4170 and 4080 Mc/s. Dominate-mode rectangular waveguide is used for these runs, and the components and installation practices used follow normal practice as far as possible.

GROUND STATION↗
NASA NTRS2017

Coastal California's Fog as a Unique Habitable Niche: Design for Autonomous Sampling and Preliminary Aerobiological Characterization

Just as on the land or in the ocean, atmospheric regions may be more or less hospitable to life. The aerobiosphere, or collection of living things in Earth's atmosphere, is poorly understood due to the small number and ad hoc nature of samples studied. However, we know viable airborne microbes play important roles, such as providing cloud condensation nuclei. Knowing the distribution of such microorganisms and how their activity can alter water, carbon, and other geochemical cycles is key to developing criteria for planetary habitability, particularly for potential habitats with wet atmospheres but little stable surface water. Coastal California has regular, dense fog known to play a major transport role in the local ecosystem. In addition to the significant local (1 km) geographical variation in typical fog, previous studies have found that changes in height above surface of as little as a few meters can yield significant differences in typical concentrations, populations and residence times. No single current sampling platform (ground-based impactors, towers, balloons, aircraft) is capable of accessing all of these regions of interest.A novel passive fog and cloud water sampler, consisting of a lightweight passive impactor suspended from autonomous aerial vehicles (UAVs), is being developed to allow 4D point sampling within a single fog bank, allowing closer study of small-scale (100 m) system dynamics. Fog and cloud droplet water samples from low-altitude aircraft flights in nearby coastal waters were collected and assayed to estimate the required sample volumes, flight times, and sensitivity thresholds of the system under design.125 cloud water samples were collected from 16 flights of the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS) instrumented Twin Otter, equipped with a sampling tube collector, occurring between 18 July and 12 August 2016 below 1 km altitude off the central coast. The collector was flushed first with 70 ethanol, then with sterile DI water, between sampling regions. Collected volumes ranged from 100 L to 12 mL. All samples were diluted serially and plated on two different types of agar, nutrient-dense (PCA) and sparse (R-2A). Plates were incubated at room temperature and counted when colonies first appeared and again at 2 weeks.Preliminary results from seven flights are consistent with generally reported colony-forming unit (CFU) values for terrestrial fog water (e.g., [4]). The PCA assay ranged from 400 to 125,000 CFU/mL, R-2A from 700 to 130,000 CFU/mL. PCA and R-2A counts were not significantly different from each other at I^ plus or minus +/- 0.05, although observationally, the R2A plates had more pigmented colonies. CFU counts from the majority of flights were not different from each other in mean at the same level of significance, but about half differed in median, indicating differences in underlying distribution. These results validate the presence of viable microorganisms in coastal California fog at levels that should be easily detectable by our sampling system. The indicated distribution differences underscore the need for small-scale, long-term sampling surveys. Future planned work includes ion chromatography for limiting nutrients, ATP quantification, and qPCR for several microbial classes of interest.

Coastal↗
NASA NTRS2020

Alaska Transportation & Infrastructure - Identifying Permafrost Subsidence Using NASA Earth Observations to Pinpoint Road & Infrastructure Vulnerability in Fairbanks, Alaska

A rapidly warming Arctic has compromised the structural integrity of critical infrastructure through accelerated permafrost thaw and thermokarst development underlying these areas. Infrastructure, including roads, bridges, and airports across the state of Alaska are particularly at risk, as permafrost underlies ~85% of the state. However, monitoring the impacts of permafrost thaw on infrastructure is largely limited to in situ observations and frequently identified after the damage is evident. In order to assist transportation and infrastructure decision-makers in Alaska, this project identified and quantified areas of surface subsidence near critical infrastructure. Seasonal interferograms were created using Sentinel-1 C-band Synthetic Aperture Radar (SAR) and L-band Uninhabited Aerial Vehicle SAR (UAVSAR) data to identify areas experiencing surface deformation. Additionally, Light Detection and Ranging (LiDAR) datasets were used to validate select interferograms created between 2017 and 2019. Validation of subsidence detection across platforms was performed over a 7x8 sq. kilometer field site for 2017. UAVSAR and Sentinel-1 seasonal deformation returns produced consistent spatial deformation patterns with residual root mean squared errors of 13 and 21 millimeters, respectively. These results suggest that both UAVSAR and Sentinel-1 platforms are capable of detecting surface subsidence. The higher resolution of UAVSAR is better able to resolve localized subsidence features of less than 80 meters, but is limited by temporal resolution.In conjunction, UAVSAR and Sentinel-1 can provide complementary spatial and temporal resolutions for subsidence analysis in the absence of in situ data.

Patrick Saylor↗
NASA NTRS2020

Alaska Transportation & Infrastructure Identifying Permafrost Subsidence Using NASA Earth Observations to Pinpoint Road and Infrastructure Vulnerability in Fairbanks, Alaska

A rapidly warming Arctic has compromised the structural integrity of critical infrastructure through accelerated permafrost thaw and thermokarst development underlying these areas. Infrastructure, including roads, bridges, and airports across the state of Alaska are particularly at risk, as permafrost underlies ~85% of the state. However, monitoring the impacts of permafrost thaw on infrastructure is largely limited to in situ observations and frequently identified after the damage is evident. In order to assist transportation and infrastructure decision-makers in Alaska, this project identified and quantified areas of surface subsidence near critical infrastructure. Seasonal interferograms were created using Sentinel-1 C-band Synthetic Aperture Radar (SAR) and L-band Uninhabited Aerial Vehicle SAR (UAVSAR) data to identify areas experiencing surface deformation. Additionally, Light Detection and Ranging (LiDAR) datasets were used to validate select interferograms created between 2017 and 2019. Validation of subsidence detection across platforms was performed over a 7x8 sq. kilometer field site for 2017. The strongest relationship in spatial deformation is observed between Sentinel-1 and UAVSAR with a residual root mean square error of 20 mm. These results suggest that both UAVSAR and Sentinel-1 platforms are capable of detecting surface subsidence. The higher resolution of UAVSAR is better able to resolve localized subsidence features of less than 80 meters, but is limited by temporal resolution. In conjunction, UAVSAR and Sentinel-1 can provide complementary spatial and temporal resolutions for subsidence analysis in the absence of in situ data.

DEVELOP Tech Paper↗