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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Distributed Sensor Fusion of Ground and Air Nodes Using Vision and Radar Modalities for Tracking Multirotor Small Uncrewed Air Systems and Birds

High-density airspace operations with multiple aircraft type and potentially noncooperative aircraft require distributed sensor detection and tracking systems to monitor airspace for safe, autonomous flight operations for advanced air mobility, urban air mobility, and high density small uncrewed air systems (SUAS) flight concepts. This work collected data using a distributed radar and camera sensor framework during the NASA Advanced Air Mobility High Density Vertiplex project SUAS flight operation. Node locations include on an onboard SUAS, affixed to the Landing and Impact Research Facility with approximate 200ft elevation, on a tripod on first-floor roof with an approximate elevation of 20 ft, and on a tripod on a concrete pad that is approximately 4 ft above sea level. Each node includes camera, radar, and GPS.

Beyond Visual Line of Sight↗
NASA NTRS1992

A dynamic study of fragmentation and energy loss during high velocity impact

Research conducted under this contract can be divided into two main areas: hypervelocity (in the range up to 7 km/s) and high velocity (less than 1 km/s). Work in the former was performed at NASA-MSFC using the Light Gas Gun Facility. The lower velocity studies were conducted at Auburn University using the ballistic gun. The emphasis of the project was on the hypervelocity phenomenon especially in the characterization of the debris cloud formed by the primary impact events. Special devices were made to determine the angular distributions of momentum and energy of the debris cloud as a function of impact conditions. After several iteration processes, it was decided to concentrate on the momentum effort. Prototype devices were designed, fabricated, and tested. These devices were based on the conservation of momentum. Distributions of the debris cloud formed were measured by determining the amount of momentum transferred from the debris cloud to strategically placed pendulum measurement devices. The motion of the pendula was monitored using itegrated opto-interrupters. The distribution of momentum in the debris cloud was found to be a strong function of the impact condition. Small projectiles at high velocities were observed to produce finely dispersed debris whereas large projectiles generated discrete particles in the debris. Results also show that the momentum in the forward direction was enhanced due to the impact. This phenomenon of momentum multiplication was also observed in other studies and in computer simulations. It was initially planned to determine the energy distribution using deformation energy in a rod with strain gauges. Results from preliminary studies show that this technique is acceptable but too tedious. A new technique was explored based on measuring the heating effect of the debris cloud using an IR camera. The feasibility and sensitivity was established at Auburn University. This type of energy distribution measurement method can easily be adapted to the gas gun facility at MSFC. The objective of the lower velocity studies at Auburn was to simulate the damage produced in advanced materials by the lower energy debris cloud.

Zee, Ralph H.↗
NASA NTRS2023

Large-Scale Groundwater Monitoring in Brazil Assisted With Satellite-Based Artificial Intelligence Techniques

Here, we develop and test an artificial intelligence (AI)-based approach to monitor major Brazilian aquifers. The approach combines Gravity Recovery and Climate Experiment (GRACE) data and ground-based hydrogeological measurements from Brazil’s Integrated Groundwater Monitoring Network at hundreds of wells distributed in twelve aquifers across the country. We tested model ensembles based on three AI approaches: Extreme Gradient Boost, Light Gradient Boosting Model and CatBoost, followed by a Linear Regression (LR) step. The approach is further boosted with wavelet and seasonal decomposition processes applied to GRACE data. To determine the AI-based model’s sensitivity to data availability, we propose four experiments combining hydrogeological measurements from different aquifers. Groundwater storage estimates from the Global Land Data Assimilation System (GLDAS) are used as benchmark. A sensitivity analysis shows that the LR-based model ensemble is the best suited and to reproduce groundwater storage change in all studied Brazilian aquifers. Results show that the proposed approach outperforms GLDAS in all experiments, with an RMSE value of 2.68cm for the experiment that covers all monitored wells in Brazil. GLDAS resulted in RMSE=6.76cm. Using our AI model outputs, we quantified the groundwater storage change of two major aquifers, Urucuia and Bauru-Caiuá, over the past two decades: -31km 3 and -6km 3 , respectively. Water loss is driven by a prolonged drought across most of the country and intensification of groundwater pumping for irrigation. This study demonstrates that combining satellite data and AI can be a cost-effective alternative to monitor poorly equipped aquifers at the continental scale, with possible global replicability.

GRACE↗
DOE OSTI2021

Synchronized Waveforms – A Frontier of Data-Based Power System and Apparatus Monitoring, Protection, and Control

Voltage and current waveforms contain the most authentic and granular information on the behaviors of power systems. In recent years, it has become possible to synchronize waveform data measured from different locations. Thus large-scale coordinated analyses of multiple waveforms over a wide area are within our reach. This development could unleash a set of new concepts, strategies, and tools for monitoring, protecting, and controlling power systems and apparatuses. This paper presents an in-depth review and analysis of the advancements in synchronized waveform data, including measurement devices, data characteristics, use cases, and comparisons with synchrophasor data. Based on the findings, five strategies are proposed to discover and develop synchronized waveform based applications over multiple application areas. The paper also presents three complementary measurement platforms and two data screening algorithms for application implementation. It further discusses committee activities and standard developments useful to explore the full potential of the data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Dynamic Heat Flow and Current Distribution Analysis in the Bottom Anode of an Electric Arc Furnace Using Fiber-Optic Sensors

A reliable method for monitoring bottom anode wear during DC Electric Arc Furnace (DC-EAF) operation is of critical importance for safe and efficient steel production. Underestimation of bottom wear poses a serious safety risk that must be avoided, while overestimation of bottom wear also poses challenges, as premature anode replacement is expensive and affects EAF productivity. Previously, we demonstrated that fiber-optic sensors can be successfully deployed to create a spatially distributed temperature map to monitor the health of the anode. The present work explores the heat flow and current density distribution in bottom anode pins to predict bottom wear, steel penetration events, and monitor refractory erosion. Small dynamic variations in pin temperature induced by joule heating during arcing also provide a means to observe local current flows in each pin. When mapped, these measurements provide a real-time view of the non-uniform and dynamic current flow in the bottom anode during EAF operation that can affect bottom wear.

Bottom Anode↗
DOE OSTI2021

Sequential Perturbation-based FDIA Detection using DERs for Unbalanced Distribution System

The power distribution system with its reliance on automated monitoring and control infrastructure makes it a complicated cyber-physical system and vulnerable to various cyber-attacks. This paper proposes a moving target defense inspired false data injection attack (FDIA) detection mechanism for an unbalanced distribution system. In the proposed grid diagnosis service framework, the distribution system operator judiciously manipulates power outputs of a subset of inverter-based distribution energy resources (DERs) to create secret low magnitude voltage perturbations which are inconsequential to the normal operation of the grid. A mixed-integer-linear-programming algorithm is developed to select the optimal set of DERs that can create a voltage perturbation signal of the required magnitude at each sensor location at a minimum cost. Then, a sequential detector is applied that detects for the FDIA as measurements are received from individual sensors. The performance of the proposed perturbation-based FDIA detection framework is demonstrated via simulation of the IEEE 123 bus test system.

Attack Detection↗
NASA NTRS2012

Biases in Long-term NO2 Averages Inferred from Satellite Observations Due to Cloud Selection Criteria

Retrievals of atmospheric trace gas column densities from space are compromised by the presence of clouds, requiring most studies to exclude observations with significant cloud fractions in the instrument's field of view. Using NO2 observations at three ground stations representing urban, suburban, and rural environments, and tropospheric vertical column densities measured by the Ozone Monitoring Instrument (OMI) over each site, we show that the observations from space represent monthly averaged ground-level pollutant conditions well (R=0.86) under relatively cloud-free conditions. However, by analyzing the ground-level data and applying the OMI cloud fraction as a filter, we show there is a significant bias in long-term averaged NO2 as a result of removing the data during cloudy conditions. For the ground-based sites considered in this study, excluding observations on days when OMI-derived cloud fractions were greater than 0.2 causes 12:00-14:00 mean summer mixing ratios to be underestimated by 12%+/-6%, 20%+/-7%, and 40%+/-10% on average (+/-1 standard deviation) at the urban, suburban, and rural sites respectively. This bias was investigated in particular at the rural site, a region where pollutant transport is the main source of NO2, and where longterm observations of NOy were also available. Evidence of changing photochemical conditions and a correlation between clear skies and the transport of cleaner air masses play key roles in explaining the bias. The magnitude of a bias is expected to vary from site to site depending on meteorology and proximity to NOx sources, and decreases when longer averaging times of ground station data (e.g. 24-h) are used for the comparison.

SEASONAL-VARIATIONS↗
DOE OSTI2024

Trust Model Measurements for the Energy Grid of Things

Information security is essential for the reliable operation of an Energy Grid of Things (EGoT). In addition to basic information security protocols as defined by published standards, there is a need for a monitoring function that measures the trustworthiness of the various actors participating in an EGoT. We describe in this paper the implementation and evaluation of a Distributed Trust Model that was developed specifically for monitoring communication within an EGoT. We then show how the model parameters are set using statistical measures for hypothesis testing.

Energy Grid of Things, EGoT, Smart Grid Security, ↗
NASA NTRS2025

Distributed Sensing Node Configuration

A vision and radar sensor integration strategy for surveillance of Advance Air Mobility Mission concept of airspace is contained in the CAD drawing in this publication developed as part of NASA's Transformational Tools and Technology project. High-density airspace operations with multiple aircraft type and potentially noncooperative aircraft require distributed sensor detection and tracking systems to monitor airspace for safe, autonomous flight operations for advanced air mobility, urban air mobility, and high density small uncrewed air systems (SUAS) flight concepts. Contained herein are drawings that are available in the stp and creo file formats of the distributed sensing nodes. Additional dovetail integration is included to enable rapid changing of embedded system. A day in the life node deployment is included in the 2023_last_flight_day.mp4. Please cite this publication if you use these drawings. This sensor configuration methodology is presented in detail in the publication reference below. Chester Dolph, Thomas Lombaerts, Corey A. Ippolito, Vahram Stepanyan, Evan Kawamura, Keerthana Kannan, George Szatkowski, Todd Ferante, Christopher Morris, Federica Vitiello, Flavia Causa, Roberto Opromolla and Giancarmine Fasano. "Distributed Sensor Fusion of Ground and Air Nodes using Vision and Radar Modalities for Tracking Multirotor Small Uncrewed Air Systems and Birds," AIAA 2024-1781. AIAA SCITECH 2024 Forum. January 2024.

Chester V Dolph↗
DOE OSTI2020

Leveraging operational information from wastewater injection wells to evaluate CO 2 injection performance for carbon storage applications in the Appalachian Basin

Abstract Geologic parameters, geophysical logging, injection testing, and operational metrics from wastewater injection wells were integrated to develop a preliminary design of a carbon storage facility in the Appalachian Basin. A scattered group of 10–20 commercial wastewater injection wells dispose off produced water from oil and gas wells in the region, utilizing a sequence of stacked deep saline formations for injection zones. These wastewater injection wells provide practical benchmarks for understanding the feasibility of carbon dioxide (CO 2 ) storage. Geologic models were developed based on characterization data from the wastewater injection wells. Reservoir simulations were calibrated according to injection testing and operational data from the wastewater injection wells. Long‐term operational data on injection flow rates and pressures measured in the wastewater injection wells were especially useful to evaluate the performance of carbon storage applications. The simulations were used to estimate injection pressures, radius of CO 2 saturation, and pressure response for industrial scale CO 2 storage applications. Results were also used to provide a design basis in terms of number of injection wells, well spacing, area of review, injection system components, monitoring plan, and CO 2 pipeline distribution system. The analysis demonstrates that there is sufficient injectivity in the deep saline formations in the west‐central Appalachian Basin to store commercial volumes of anthropogenic CO 2 . The geologic system appears suitable for supporting CO 2 injection rates of 0.5–1.0 million metric tons per year at injection pressures below formation fracture pressure in a single well. The long‐term operational data of wastewater injection wells within the study area suggested a lower permeability‐thickness values than indicated by initial reservoir tests. A workflow for developing realistic permeability values for input into reservoir simulations is presented. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.

Valluri, Manoj↗
DOE OSTI2025

Litter production and foliar nutrient resorption in fast- and slow-growing tree species in the Central Amazon

Litterfall is crucial for forest maintenance, serving as a primary mechanism for nutrient return to the nutrient-poor soils of tropical forests. Foliar nutrient resorption likewise represents an important nutrient-conservation mechanism. Yet, little is known about how these processes vary between fast- and slow-growing species in post-logging areas of the Amazon forest. Here, the objective of this study was to quantify litterfall production and the resorption of foliar nutrients in fast-growing and slow-growing tree species of the Central Amazon, in a forest that was experimentally logged in 1987. The study was conducted from May 2022 to April 2023. Litterfall was collected biweekly using four collectors that were systematically distributed beneath the canopy of each monitored tree, totaling 72 collectors. Three fast-growing and three slow-growing species were selected, each with three replicates, totaling 18 monitored individuals. Species-specific samples of fresh (green) and senesced (litter) leaves were collected and analyzed for their nutrient content and resorption efficiency. Fast-growing species had a monthly leaf litter deposition of 13.53 ± 1.6 g m −2 month −1 , compared to 2.59 ± 0.4 g m −2 month −1 for slow-growing species. The average annual litter production across both functional types was 8.6 ± 2.6 Mg ha −1 year −1 . Nutrient inputs through litterfall were higher in fast-growing species for all elements, particularly nitrogen (N), with 21.92 ± 4.9 kg ha −1 year −1 . Phosphorus (P) and potassium (K) exhibited the highest foliar resorption. P resorption efficiency was 68.3 % in fast-growing species and 57.8 % in slow-growing species. For K, efficiencies were 59.0 % and 41.7 %, respectively. These results highlight the substantial role that fast-growing species play in restoring forest productivity in managed Amazon forests, both through higher litter deposition and nutrient fluxes, and through nutrient conserving-mechanisms such as foliar nutrient resorption.

Amazon forest↗
DOE OSTI2020

Towards real-time monitoring: data assimilated time-lapse full waveform inversion for seismic velocity and uncertainty estimation

SUMMARY Rapid development of time-lapse seismic monitoring instrumentations has made it possible to collect dense time-lapse data for tomographically retrieving time-lapse (even continuous) images of subsurface changes. While traditional time-lapse full waveform inversion (TLFWI) algorithms are designed for sparse time-lapse surveys, they lack of effective temporal constraint on time-lapse data, and, more importantly, lack of the uncertainty estimation of the TLFWI results that is critical for further interpretation. Here, we propose a new data assimilation TLFWI method, using hierarchical matrix powered extended Kalman filter (HiEKF) to quantify the image uncertainty. Compared to existing Kalman filter algorithms, HiEKF allows to store and update a data-sparse representation of the cross-covariance matrices and propagate model errors without expensive operations involving covariance matrices. Hence, HiEKF is computationally efficient and applicable to 3-D TLFWI problems. Then, we reformulate TLFWI in the framework of HiEKF (termed hereafter as TLFWI-HiEKF) to predict time-lapse images of subsurface spatiotemporal velocity changes and simultaneously quantify the uncertainty of the inverted velocity changes over time. We demonstrate the validity and applicability of TLFWI–HiEKF with two realistic CO2 monitoring models derived from Frio-II and Cranfield CO2 injection sites, respectively. In both 2-D and 3-D examples, the inverted high-resolution time-lapse velocity results clearly reveal a continuous velocity reduction due to the injection of CO2. Moreover, the accuracy of the model is increasing over time by assimilating more time-lapse data while the standard deviation is decreasing over lapsed time. We expect TLFWI-HiEKF to be equipped with real-time seismic monitoring systems for continuously imaging the distribution of subsurface gas and fluids in the future large-scale CO2 sequestration experiments and reservoir management.

58 GEOSCIENCES↗
NASA NTRS1966

OSO spacecraft manual

Spacecraft manual for OSO - telemetry system, command system, power supply and distribution, antenna system, experiment complement, temperature monitoring, and launch program

OSO↗
NASA NTRS1972

Studies of the inner shelf and coastal sedimentation environment of the Beaufort Sea from ERTS-1

The author has identified the following significant results. Field studies of the initiation of river flow onto the frozen Arctic Ocean were made by a group of scientists from May 15 to June 10, 1972. A time lapse camera mounted on a 40-ft. tower near the mouth of the Kaparuk River, west of Prudhoe Bay, provided a detailed 10-day record (24 hours a day) of flow direction and water level. It is believed that wind build-up, discharge variance of the river, and through-ice drainage rates are the prime factors influencing overflow onto the sea ice. Current meter, transmissometer, temperature, salinity, and thermoprobe data were collected from holes drilled in the shorefast ice from seal holes and from the river water overflow. Depth and a real distribution of the overflow water were monitored from the ice using snowmobiles, and from the air using helicopters and fixed-wing aircraft. Photographic records were made on 35mm KII, KX, Ektachrome IR, Plus X, and IR black and white film. A simple two camera frame permitted simultaneous exposures of two types of film. Preliminary comparisons of the IR and conventional films, both color and black and white, showed no advantage to using the infrared film. However, the low altitude photography taken during this study will be very helpful in the interpretation of ERTS-1 imagery.

Reimnitz, E.↗
NASA NTRS1973

Variable features on Mars. II - Mariner 9 global results.

Systematic Mariner 9 monitoring of the space and time distribution of Martian bright and dark markings, the streaks and splotches, indicates a range of global correlations. The time-variable classical dark markings owe their configurations and variability to their constituent streaks and splotches, produced by windblown dust. Streaks and splotches are consistent wind direction indicators. Correlation of global streak patterns with general circulation models shows that velocities of about 50 to 90 m/sec above the boundary layer are necessary to initiate grain motion on the surface and to produce streaks and splotches. Detailed examples of changes in Syrtis Major, Lunae Palus, and Promethei Sinus are generally consistent with removal of bright sand and dust and uncovering of darker underlying material as the active agent in such changes, although dark mobile material probably also exists on Mars. The generation of streaks and the progressive albedo changes observed require only threshold velocities of about 2 m/sec for about 1 day at the grain surface.

Sagan, C.↗
NASA NTRS1974

Recent advances in satellite observations of solar variability and global atmospheric ozone

The launch of Nimbus 4 in April 1974 has made possible simultaneous measurements of the ultraviolet solar irradiance and the global distribution of atmospheric ozone by the monitor of ultraviolet solar energy (MUSE) and backscatter ultraviolet (BUV) experiments respectively. Two long lived ultraviolet active solar regions which are about 180 deg apart in solar longitude were observed to be associated with central meridian passages of solar magnetic sector boundaries. The boundaries may be significant in the evaluation of correlations between solar magnetic sector structure and atmospheric circulation.

Heath, D. F.↗
NASA NTRS1973

Opportunities for space surveys of moisture anomalies

Review of a combination of infrared scanning, unsupervised spectroscopic classification, change detection, and perturbation spectroscopy for monitoring anomalous moisture exchange from space. Infrared sensors have been developed which can monitor the solar reflectance from droplet distributions in vegetation and clouds, the absorption of thermal radiation by water vapor, and the microwave attenuation by atmospheric water. Unsupervised spectroscopic classification techniques are emerging which have the potential to subdivide strip maps from infrared scanners into different moisture targets. Intersecting and parallel spacecraft orbits provide opportunities to study the change of recognized targets between two scans and to recognize anomalous moisture exchange from those changes which significantly exceed the statistical uncertainty of the spectroscopic target signature. The new concept of perturbation spectroscopy shows a potential to quantitatively determine the change of integrated water vapor pressure with a minimum of 'atmospheric truth' and with low spectroscopic resolution that is typical of simple interference filters.

Krause, F. R.↗
NASA NTRS1974

Analysis of satellite measurements of terrestrial radio noise

Worldwide distributions of terrestrial radio noise as monitored by Radio Astronomy Explorer 1 (RAE 1) generated and compared with CCIR predictions. These contour maps show the global morphology of radio noise at 6.55 and 9.18 MHz for fall, winter, spring and summer during the local time blocks of 00-08 LT and 16-24 LT. These computer produced maps show general agreement with CCIR predictions over large land masses. The RAE and CCIR maps diverge at high latitudes over Asia and frequently over ocean regions. Higher noise levels observed by RAE at high latitudes are attributed to magnetospheric emission while higher noise levels observed by RAE over Asia are attributable to high power transmitters. Analysis of RAE noise observations in conjunction with various geophysical phenomena showed no obvious correlation.

Bakalyar, G.↗