Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data fusion”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 811 records · Page 45

Multi-Sensor Registration of Earth Remotely Sensed Imagery

Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30m), MODIS (500m), and SeaWIFS (1000m).

LeMoigne, Jacqueline↗

Ultra-Lightweight Borosilicate Gas-Fusion Mirror for Cryogenic Testing

Hextek Corporation fabricated a 250 mm diameter ultra-lightweight borosilicate mirror substrate for cryogenic testing at NASA MSFC XRCF facility in Huntsville AL under contract# H-34475D. The objectives of the program were to demonstrate that the Hextek Gas-Fusion technology is capable of meeting the 15kg/sq m areal density target required for future space missions, and to provide a demonstration substrate for NASA MSFC to finish and test at cryogenic temperature. This presentation reviews company background and capabilities, features and benefits of the Gas-Fusion technology, historical data on cryogenic performance of borosilicate glass showing near zero cte at 30-35 degrees Kelvin, design and fabrication results of the 250 mm 15kg/sq m areal density substrate, and finally, projected scaling, lightweighing and fabrication lead-times for meter class segments.

Voevodsky, Michael↗

An improved method for precise automatic co-registration of moderate and high-resolution spacecraft imagery

Improvements to the automated co-registration and change detection software package, AFIDS (Automatic Fusion of Image Data System) has recently completed development for and validation by NGA/GIAT. The improvements involve the integration of the AFIDS ultra-fine gridding technique for horizontal displacement compensation with the recently evolved use of Rational Polynomial Functions/ Coefficients (RPFs/RPCs) for image raster pixel position to Latitude/Longitude indexing. Mapping and orthorectification (correction for elevation effects) of satellite imagery defies exact projective solutions because the data are not obtained from a single point (like a camera), but as a continuous process from the orbital path. Standard image processing techniques can apply approximate solutions, but advances in the state-of-the-art had to be made for precision change-detection and time-series applications where relief offsets become a controlling factor. The earlier AFIDS procedure required the availability of a camera model and knowledge of the satellite platform ephemeredes. The recent design advances connect the spacecraft sensor Rational Polynomial Function, a deductively developed model, with the AFIDS ultrafine grid, an inductively developed representation of the relationship raster pixel position to latitude /longitude. As a result, RPCs can be updated by AFIDS, a situation often necessary due to the accuracy limits of spacecraft navigation systems. An example of precision change detection will be presented from Quickbird.

co-registration↗

ESTIMATING IMPURITIES IN SURPLUS PLUTONIUM FOR DISPOSITION

The United States holds at least 61.5 metric tons (MT) of plutonium that is permanently excess to use in nuclear weapons programs, including 47.2 MT of weapons-grade plutonium. Surplus inventories will be stored safely by the Department of Energy (DOE) and then transferred to facilities that will prepare the plutonium for permanent disposition. The Savannah River National Laboratory (SRNL) operates a Feed Characterization program for the Office of Fissile Materials Disposition of the National Nuclear Security Administration and the DOE Office of Environmental Management. Many of the items that require disposition are only partially characterized, and SRNL uses a variety of techniques to predict the isotopic and chemical properties that are important for processing through the Mixed Oxide Fuel Fabrication Facility and alternative disposition paths. Recent advances in laboratory tools, including Prompt Gamma Analysis and Peroxide Fusion treatment, provide data on the existing inventories that will enable disposition without additional, costly sampling and destructive analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Ignition and pusher adiabat

In the last five years, large amounts of high quality experimental data in inertial confinement fusion (ICF) were produced at the National Ignition Facility (NIF). From the NIF data, we have significantly advanced our scientific understanding of the physics of thermonuclear (TN) ignition in ICF and identified the critical physical issues important to achieve ignition, such as implosion energetics, pusher adiabat, tamping effects in fuel confinement, and confinement time. In this article, we will present recently developed TN ignition theory and implosion scaling laws [1, 2] characterizing the thermodynamic properties of the hot spot and the TN ignition metrics at NIF. We compare our theoretical predictions with NIF data with good agreement between theory and experiments. We will also demonstrate the fundamental effects of the pusher adiabat on the energy partition between the cold shell and the hot deuterium-tritium and on the neutron yields of ICF capsules. Applications [3–5] to NIF experiments and physical explanations of the discrepancies among theory, data and simulations will be presented. In our theory, the actual adiabat of the cold DT fuel can be inferred from neutron image data of a burning capsule. With the experimentally inferred hot spot mix, the CH mix in the cold fuel could be estimated, as well as the preheat. Lastly, possible path forwards to reach high yields are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Conflation of Geospatial POI Data and Ground-level Imagery

The code solves the problem of conflating POI (Points of Interest) geospatial data and geo-tagged ground-level imagery data. The main challenges with fusion or conflation of these two types of data has been that these two data entities are represented not only in several ways in current state-of-the-art, but also there is mismatch of representation format of these two data types. This source code/software brings POI datapoints and ground-level imagery datapoints into same representation format, and then generates valuable Knowledge Graph combining POI and images data (so that it can be used for multitude of applications).

De, Debraj↗

Registration and fusion of large-scale melt pool temperature and morphology monitoring data demonstrated for surface topography prediction in LPBF

In-situ monitoring technologies for laser powder bed fusion (LPBF) additive manufacturing often face one key challenge, extracting the ultrafast melt pool (MP) signatures for understanding the localized part properties. Further, the spatial information of each monitored MP signature is essential for correlating the MP – part property. This spatial information is often unavailable especially from commercial LPBF printers. Many MP monitoring methods have been reported and utilized. However, very few of these have the MP’s spatial information. To overcome this challenge, in this work we report a method for spatially registering the key MP signatures (MP intensity, temperature, and area) to the monitored print parts. The MP signatures are obtained from our coaxial high-speed single-camera based two-wavelength imaging pyrometry (STWIP) system and the MP spatial information is obtained from an off-axis camera system. A machine learning aided image analysis method is employed to retrieve the spatial distribution of MPs within the corresponding part’s coordinates system. Then, the MP signature maps (MPSMs) are reconstructed by mapping the STWIP measured MP signatures to the registered MP coordinates. Further, a long short-term memory (LSTM) neural network is developed for estimating the layer surface topography from the registered MPSMs. The obtained results indicate that the layer surface topography can be more accurately estimated by using MP temperature signature rather than MP intensity and/or area signatures as in common practice. Finally, our developed methods for MP monitoring, registration, and MP-surface topography prediction offer advanced capabilities for the online detection of process anomalies and part defects.

36 MATERIALS SCIENCE↗

Neutron and photon in-vivo materials characterization at the evolving plasma-material interface in plasma-burning fusion environments

This report includes the first set of MOSS data collected in the context of fusion-relevant plasma-material interactions. The data collected show that the surface curvature and stress irreversibly change during low-energy deuterium ion irradiation. This holds for both tungsten thin films, bulk tungsten, and single-crystal silicon. Meanwhile, argon irradiation did not produce this same effect. The surface morphology of the exposed samples was virtually identical regardless of gas species. There were, however, some surface chemistry differences between argon-exposed and deuterium-exposed samples, mainly concerning the oxide states of the W4f XPS signal. The changes in surface chemistry could be due to hydrogen dynamics on the tungsten surfaces, though further investigation will be required with in-situ irradiation and analysis. The changes in surface stress could also not be explained by temperature alone, as the temperature reached during the ion irradiations was too low to induce non-elastic strain. With this in mind, deuterium retention in the materials could change the surface curvature and stress. To confirm this, further work will be needed to quantify the change in curvature and relate it to ion flux, fluence, and deuterium retention. Unfortunately, when this work was conducted, the experimental setup for thermal desorption spectroscopy was not operating correctly, and that work could not be included in this dissertation. Despite experimental difficulties, this work shows the first results of a promising technique to study deuterium dynamics in tungsten-based reconstituted thin films.

36 MATERIALS SCIENCE↗

Recent progress in the development of liquid metal plasma facing components for magnetic fusion devices

One of the most critical challenges for future fusion reactors is to develop longevity plasma-facing components (PFCs) exposed to extremely high heat and neutron loads. As opposed to those employing solid metals, PFCs with flowing liquid metals (LM) have shown self-healing, heat removal and good impurity control capabilities, all essential to fusion devices. Recently, significant progress in LM-PFC development has been reported globally, with data from several magnetic fusion devices. These studies reveal that LM-PFCs can endure extreme heat fluxes while maintaining plasma compatibility. New design concepts have been proposed and numerically analyzed, advancing models for liquid PFCs in future reactors. Despite existing technical challenges, these developments suggest that LM-PFCs hold promise for future fusion applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Deep convolutional neural networks for multi-scale time-series classification and application to disruption prediction in fusion devices

The multi-scale, mutli-physics nature of fusion plasmas makes predicting plasma events challenging. Recent advances in deep convolutional neural network architectures (CNN) utilizing dilated convolutions enable accurate predictions on sequences which have long-range, multi-scale characteristics, such as the time-series generated by diagnostic instruments observing fusion plasmas. Here we apply this neural network architecture to the popular problem of disruption prediction in fusion tokamaks, utilizing raw data from a single diagnostic, the Electron Cyclotron Emission imaging (ECEi) diagnostic from the DIII-D tokamak. ECEi measures a fundamental plasma quantity (electron temperature) with high temporal resolution over the entire plasma discharge, making it sensitive to a number of potential pre-disruptions markers with different temporal and spatial scales. Promising, initial disruption prediction results are obtained training a deep CNN with large receptive field ({$\sim$}30k), achieving an $F_1$-score of {$\sim$}91\% on individual time-slices using only the ECEi data.

convolutional neural networks↗

Leaf traits and canopy structure together explain canopy functional diversity: an airborne remote sensing approach

Plant functional diversity is strongly connected to photosynthetic carbon assimilation in terrestrial ecosystems. However, many of the plant functional traits that regulate photosynthetic capacity, including foliar nitrogen concentration and leaf mass per area, vary significantly between and within plant functional types and vertically through forest canopies, resulting in considerable landscape-scale heterogeneity in three dimensions. Hyperspectral imagery has been used extensively to quantify functional traits across a range of ecosystems but is generally limited to providing information for top-of-canopy leaves only. On the other hand, lidar data can be used to retrieve the vertical structure of forest canopies. Because these data are rarely collected at the same time, there are unanswered questions about the effect of forest structure on the 3-D spatial patterns of functional traits across ecosystems. In the United States, the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) provides an opportunity to address this structure-function relationship by collecting lidar and hyperspectral data together across a variety of ecoregions. With a fusion of hyperspectral and lidar data from the NEON AOP and field-collected foliar trait data, we assessed the impacts of forest structure on spatial patterns of N. In addition, we examine the influence of abiotic gradients and management regimes on top of canopy %N and total canopy N (i.e. the total amount of N (g/m 2 ) within a forest canopy) at a NEON site consisting of a mosaic of open longleaf pine and dense broadleaf deciduous forests. Here, our resulting maps suggest that in contrast with top-of-canopy values, total canopy N variation is dampened across this landscape resulting in relatively homogeneous spatial patterns. At the same time, we found that leaf functional diversity and canopy structural diversity showed distinct dendritic patterns related to the spatial distribution of plant functional types.

54 ENVIRONMENTAL SCIENCES↗

Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016

A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5~m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. This data was developed using the fusion of hyperspectral, multispectral, and terrain datasets. The current data is located in the Kougarok watershed but we plan to expand this over the Seward Peninsula. Additional metadata and vegetation maps included as two *.pdf, one *.txt, one *.nc, and three *.tif files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Potential model for nuclear astrophysical fusion reactions with a square-well potential

The potential model for nuclear astrophysical reactions requires a considerably shallow nuclear potential when a square-well potential is employed to fit experimental data. Here, we discuss the origin of this apparently different behavior from that obtained with a smooth Woods-Saxon potential, for which a deep potential is often employed. We argue that due to the sharp change of the potential at the boundary the radius parameter tends to be large in the square-well model, which results in a large absorption radius. The wave function then needs to be suppressed in the absorption region, which can eventually be achieved by using a shallow potential. We thus clarify the reason why the square-well potential has been able to reproduce a large amount of fusion data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Thermonuclear Fusion Verification of Staged Z-Pinch Fusion on a 0.5 MA LTD Pulsed Power Generator (Final Report)

LLNL fielded neutron detectors at UCSD’s CESZAR facility during the experimental campaigns investigating the staged Z-pinch concept. This concept uses high current to compress a cylindrical plasma composed a high atomic number gas, such as argon, surrounding fusion fuel. LLNL analyzed data from the diagnostics and improved the diagnostic setup specific to the experiment. This work helps to advance the mission creating a fusion energy source, which is a benefit to the economy and for energy security.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗