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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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226 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Multi-Kernel Adaptive Support Vector Machine for Scalable Predictive Maintenance

Application of data-driven solutions across an industry is challenging, since the data are often stored locally, and increasing privacy and security concerns restrict access to the data. In addition, it is highly unlikely that all potential data patterns are captured in a single data source. Because it is highly unlikely that all potential data patterns are captured in a single data source, machine learning (ML) models developed from a single source cannot be robust enough. An alternative is to train the ML model at each source and develop a distributed knowledge discovery and aggregation approach to build global knowledge. In this paper, we develop and demonstrate a distributed ML model, federated transfer learning (FTL), using a multi-kernel-based adaptive support vector machine (MK-A-SVM). For federated learning (FL), the multi-kernel (MK) approach enables feature-specific model aggregation under data heterogeneity; whereas for transfer learning (TL) the adaptive model enables utilization of an aggregated model from a different task. The proposed approach is validated using nuclear power plant (NPP) vertical motor-driven pump data to predict the health condition of vertical motor-driven pumps as an anomaly detection. The efficiency of the proposed approach is also quantified and compared with neural network.

42 ENGINEERING↗
DOE OSTI2021

Magnetic field-induced non-trivial electronic topology in Fe3− x GeTe2

The anomalous Hall, Nernst, and thermal Hall coefficients of the itinerant ferromagnet Fe3−xGeTe2 display anomalies upon cooling that are consistent with a topological transition that could induce deviations with respect to the Wiedemann–Franz (WF) law. This law has not yet been validated for the anomalous transport variables, with recent experimental studies yielding material-dependent results. Nevertheless, the anomalous Hall and thermal Hall coefficients of Fe3−xGeTe2 are found, within our experimental accuracy, to satisfy the WF law for magnetic fields μ0H applied along its c axis. Remarkably, large anomalous transport is also observed for μ0H||a axis with the field aligned along the gradient of the chemical potential generated by thermal gradients or electrical currents, a configuration that should not lead to their observation. These anomalous planar quantities are found to not scale with the component of the planar magnetization (M||), showing instead a sharp decrease beyond μ0H||= 4 T or the field required to align the magnetic moments along μ0H||. We argue that chiral spin structures associated with Bloch domain walls lead to a field-dependent spin chirality that produces a novel type of topological transport in the absence of interaction between the magnetic field and electrical or thermal currents. Locally chiral spin structures are captured by our Monte Carlo simulations incorporating small Dzyaloshinskii–Moriya and biquadratic exchange interactions. These observations reveal not only a new way to detect and expose topological excitations, but also a new configuration for heat conversion that expands the current technological horizon for thermoelectric energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Deficient precipitation sensitivity to Sahel land surface forcings among CMIP5 models

Abstract The overall performance of the simulated seasonal precipitation response to local terrestrial forcings, namely vegetation abundance and soil moisture, in the Sahel among the Coupled Model Intercomparison Project Phase Five (CMIP5) Earth System Models (ESMs) is systematically investigated and compared with its observational counterpart using a multivariate statistical method. The observed seasonal precipitation response is evaluated against a large ensemble of observational, reanalysis, and satellite data sets to provide quantification of uncertainties. The behaviour of models with and without a Dynamic Global Vegetation Model (DGVM) component is also explored, along with the mechanisms responsible for terrestrial feedback on rainfall. In general, the CMIP5 models can reasonably capture the seasonal evolution of Sahel precipitation and soil moisture, albeit with wet biases during the pre‐monsoon period and dry biases during the peak monsoon period. The non‐DGVM ESMs simulate comparable leaf area indices (LAIs) with observations, while DGVM‐enabled ESMs simulate too much year‐round LAI. The variance of precipitation that is attributed to oceanic forcings in CMIP5 is comparable with observations; however, the variance of precipitation that is attributed to terrestrial forcings is smaller in CMIP5 models than observed, especially for non‐DGVM ESMs. CMIP5 models, especially those without DGVMs, undervalue precipitation's observed response strength to soil moisture anomalies. In both observations and CMIP5 models, none of the atmospheric variables show significant responses to direct vegetation forcing, except for the response in transpiration. Although vegetation has minimal direct effect on the atmospheric state, it can affect the atmosphere by modifying soil moisture and transpiration rate indirectly, which helps explain the more realistic simulation of rainfall in DGVM‐enabled ESMs than non‐DGVM ESMs. Coupling of an ESM to a DGVM is critical in generating reasonable land–atmosphere feedback and examining future ecological and climatic changes over the Sahel.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Climatology of Severe Local Storm Environments and Synoptic-Scale Features over North America in ERA5 Reanalysis and CAM6 Simulation

Severe local storm (SLS) activity is known to occur within specific thermodynamic and kinematic environments. These environments are commonly associated with key synoptic-scale features—including southerly Great Plains low-level jets, drylines, elevated mixed layers, and extratropical cyclones—that link the large-scale climate to SLS environments. This work analyzes spatiotemporal distributions of both extreme values of SLS environmental parameters and synoptic-scale features in the ERA5 reanalysis and in the Community Atmosphere Model, version 6 (CAM6), historical simulation during 1980–2014 over North America. Compared to radiosondes, ERA5 successfully reproduces SLS environments, with strong spatiotemporal correlations and low biases, especially over the Great Plains. Both ERA5 and CAM6 reproduce the climatology of SLS environments over the central United States as well as its strong seasonal and diurnal cycles. ERA5 and CAM6 also reproduce the climatological occurrence of the synoptic-scale features, with the distribution pattern similar to that of SLS environments. Compared to ERA5, CAM6 exhibits a high bias in convective available potential energy over the eastern United States primarily due to a high bias in surface moisture and, to a lesser extent, storm-relative helicity due to enhanced low-level winds. Additionally, composite analysis indicates consistent synoptic anomaly patterns favorable for significant SLS environments over much of the eastern half of the United States in both ERA5 and CAM6, though the pattern differs for the southeastern United States. Overall, our results indicate that both ERA5 and CAM6 are capable of reproducing SLS environments as well as the synoptic-scale features and transient events that generate them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Distinctive Pattern of Global Warming in Ocean Heat Content

Abstract Huge heat anomalies in the atmosphere and ocean in recent years are not yet explained. Strong characteristic patterns in temperatures for upper layers of the ocean occurred from 2000 to 2023 in the presence of global warming from increasing atmospheric greenhouse gases. Here, we show that the deep tropics are warming, although sharply modulated by El Niño–Southern Oscillation events, with strong heating in the extratropics near 40°N and 40°–45°S but little heating near 20°N and 25°–30°S. The heating is most clearly manifested in zonal-mean ocean heat content and is evident in sea surface temperatures. The strongest heating is in the Southern Hemisphere, where aerosol effects are small. Estimates are made of the contributions to heating of top-of-atmosphere (TOA) radiation, atmospheric energy transports, surface fluxes of energy, and redistribution of energy by surface winds and ocean currents. The patterns of change are not directly related to TOA radiation but are evident in net surface energy fluxes and inferred ocean heat transports, underscoring their coupled origin. Changes in the atmospheric circulation through a poleward shift in ocean jet streams and storm tracks are reflected in surface wind-driven ocean Ekman transports. As well as human-induced climate change, internal natural variability is likely in play. Hence, the atmosphere and ocean currents are systematically redistributing heat from global warming, profoundly affecting local climates. Significance Statement As the climate changes, it has been difficult to discern meaningful patterns. Distinctive patterns of change have occurred in the ocean when examined as zonal averages around latitude bands. Most excess heat from global warming resides in the ocean and, since 2005, has become focused into bands near 40°N and 40°S, with little net warming in the subtropics. The strongest warming is in the Southern Hemisphere, although sea surface temperatures have increased more in the Northern Hemisphere. Changes in the atmospheric circulation through a poleward shift in the jet stream and storm tracks are primarily responsible along with corresponding changes in ocean currents. These changes are linked through surface exchanges of energy via heat, moisture, and wind stress.

Trenberth, Kevin E. [National Center for Atmospher↗
DOE OSTI2022

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↗
DOE OSTI2023

Extended Bandwidth Spread Spectrum Time Domain Reflectometry Cable Test for Thermal Aging, Low Resistance Fault, and Water Detection

In 2022, researchers at Pacific Northwest National Laboratory (PNNL) used the Accelerated and Real-Time Environmental Nodal Assessment (ARENA) cable and motor test bed to characterize spread spectrum time domain reflectometry (SSTDR) and compare the responses of an SSTDR instrument to those of a frequency domain reflectometry (FDR) instrument. Results showed both techniques could detect and locate cable anomalies such as phase-to-phase low resistance and shorts, thermal insulation damage, mechanical insulation damage, and the presence or absence of water in some conditions. The SSTDR tests used a commercial instrument provided by LiveWire Innovations Inc. This commercial instrument performed tests at 6, 12, 24, and 48 MHz bandwidth. The results of these tests were compared to FDR tests where bandwidths could be extended up to 1.3 GHz, although the best responses for cable tests were from 100 to 500 MHz. Lower bandwidth signals can propagate better along the cable while higher bandwidths have higher resolution for impedance change reflections allowing more precise indication of location and separation of anomalies. The 2022 research found that FDR responses were clearer than SSTDR and speculated that a higher bandwidth SSTDR could more successfully detect and locate cable anomalies. One advantage of the SSTDR system investigated was that it was designed for energized online use up to 1,000 volts, which may be a significant advantage for nuclear power plant use. The LiveWire SSTDR instrument is an established product in the rail and aircraft industry and updating the SSTDR hardware parameters is difficult to justify without more conclusive testing. Therefore, a software adjustable laboratory SSTDR instrument was developed by PNNL and was used to test extended bandwidth SSTDR cable tests. Within the ARENA test bed, 42 cable conditions were tested with the PNNL SSTDR, FDR, and the LiveWire SSTDR—each operating at four different bandwidths. Observations and conclusions regarding the relative performance of the three instruments over different bandwidths are note below. Responses of the PNNL SSTDR (at 50 MHz) and the LiveWire SSTDR (at 48 MHz) were similar. The PNNL SSTDR higher frequency bandwidths behaved as expected showing sharper peaks and higher noise. This validated the PNNL SSTDR as a reasonable implementation of the SSTDR technology. Lower bandwidth SSTDR responses (particularly 6 and 12 MHz) may have increased value for use within longer cables but were not particularly effective at identifying anomalous cable behavior in the 100 ft cables tested here. The higher bandwidths of the PNNL SSTDR (50, 100, 200, and 400 MHz) did not provide substantially clearer cable reflectometry responses, but having the higher frequency responses available did add to the cable test evaluation. Strong responses to shorts and low impedance faults between phases were particularly evident in the higher bandwidth PNNL SSTDR and the FDR data. Measurements were repeatable, with similar responses obtained from a thermally aged cable for tests taken a month apart. Signal noise was affected in the unshielded cable by the local in-tray cable arrangement including proximity to metal edges and rungs of the cable tray. Foam isolation of the cable from the tray metal reduced in both FDR and SSTDR responses. Cable condition monitoring in nuclear power plants will likely benefit from both more informative off-line testing methods and from the development of on-line methods for continuous monitoring of cables in use. The LWRS-funded ARENA test bed was a valuable resource for this development and direct comparison of nuclear electrical cable condition monitoring technologies. Test results are targeted to guide industry advancement of testing and monitoring tools for cable aging management.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

A Pn magnitude scale m b ( Pn ) for earthquakes along the equatorial Mid-Atlantic Ridge

We developed a short-period Pn magnitude scale m b (Pn) for earthquakes along the equatorial Mid-Atlantic Ridge. Due to low signal-to-noise ratios, teleseismic body wave magnitude and long-period surface wave magnitude cannot be confidently determined for small earthquakes of m b < 4. Local magnitude scales are also not useful for these events because the oceanic environment does not allow the propagation of crustal phases. However, regional high-frequency Pn waves from these small- to moderate-size (m b 3–6) earthquakes are well recorded in the equatorial Atlantic region and can be used to assign magnitudes. We measured over 2041 Pn peak amplitudes on vertical records from about 21 stations in northeastern Brazil and 11 stations in western Africa in the distance range of 700–3700 km. We analysed data from 189 events from the global centroid moment tensor catalogue to tie our m b (Pn) scale to M w so that seismic moments can be readily estimated. Pn arrivals show apparent group velocity between 7.9 km s –1 at short ranges (~1000 km) and up to 9.1 km s –1 at 3500 km. The measured peak amplitudes have a frequency between 0.8 and 3 Hz at 1000–1800 km, but at greater distances, 1800–3700 km, they show a remarkably consistent frequency of about 0.8 Hz. The peak amplitude attenuates at a higher rate at short distances (~0.65 magnitude units between 700 and 2000 km) but attenuates at a lower rate at long distances (~0.35 magnitude units between 2000 and 3700 km). The low rate of amplitude decay with distance and nearly constant frequency content of the peak amplitudes suggest that Pn waves propagate efficiently in the lower part of the upper mantle in the equatorial Atlantic Ocean basins. Furthermore, these are important attributes of oceanic Pn waves that can be used to assign magnitude for small- to moderate-size earthquakes in the equatorial mid-Atlantic region. The estimated station corrections correlate well with upper mantle low-velocity anomalies, especially in Brazil.

58 GEOSCIENCES↗
DOE OSTI2024

Datasets and U-Net Model for "A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma"

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

Artificial Intelligence↗
DOE OSTI2023

Cosmic topology. Part I. Limits on orientable Euclidean manifolds from circle searches

The Einstein field equations of general relativity constrain the local curvature at every point in spacetime, but say nothing about the global topology of the Universe. Cosmic microwave background anisotropies have proven to be the most powerful probe of non-trivial topology since, within ΛCDM, these anisotropies have well-characterized statistical properties, the signal is principally from a thin spherical shell centered on the observer (the last scattering surface), and space-based observations nearly cover the full sky. The most generic signature of cosmic topology in the microwave background is pairs of circles with matching temperature and polarization patterns. No such circle pairs have been seen above noise in the WMAP or Planck temperature data, implying that the shortest non-contractible loop around the Universe through our location is longer than 98.5% of the comoving diameter of the last scattering surface. We translate this generic constraint into limits on the parameters that characterize manifolds with each of the nine possible non-trivial orientable Euclidean topologies, and provide a code which computes these constraints. In all but the simplest cases, the shortest non-contractible loop in the space can avoid us, and be shorter than the diameter of the last scattering surface by a factor ranging from 2 to at least 6. Further, this result implies that a broader range of manifolds is observationally allowed than widely appreciated. Probing these manifolds will require more subtle statistical signatures than matched circles, such as off-diagonal correlations of harmonic coefficients.

79 ASTRONOMY AND ASTROPHYSICS↗