Search NASA⌕ Search

SEARCH · Search NASA

Results for “dataset shift”

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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Robertson, F. R.↗
DOE OSTI2024

Parallax-corrected VISST-derived pixel-level products from satellite GOES-16

The NASA Langley group led by William Smith produced GOES-16 satellite cloud retrievals over an approximate 10 by 10 degree region over the CACTI field campaign location. These retrievals are described here: https://www.arm.gov/capabilities/vaps/visst and are available for download here . They use algorithms historically called VISST that are now referred to as SatCORPS. More information can be found in Trepte et al. (2019), Minnis et al. (2021), and Yost et al. (2021). If using this dataset, please cite these references, the CACTI VISST dataset DOI found at the download link above, and this dataset’s DOI. The CACTI VISST pixel-level retrievals are on a 2 km spatial grid and available every 15 minutes (every 10 minutes late in the campaign), producing 21,765 files for the entire field campaign between October 2018 and April 2019. They are not corrected for parallax error, which is an offset in the actual geographical location of a cloud above the surface due to the satellite viewing the cloud partly from the side off nadir. This dataset applies a correction for parallax using the location relative to the satellite and the retrieved cloud top height above the surface, which allows the dataset to be geo-located with surface-based observations. The parallax correction for each location depends on the longitude, latitude and cloud top height above ground level (AGL) for that longitude and latitude in the original VISST files. The cloud top height AGL requires first computing the surface elevation at each VISST grid point. Data from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) Global Digital Elevation Map Version 3 at 30-m resolution is projected onto the VISST grid using conservative coarsening (conserving surface elevation) in the xESMF Python package. The surface elevation is then subtracted from the VISST-retrieved cloud top height above mean sea level. These cloud top heights AGL are then combined with longitude and latitude to estimate the latitude and longitude corrections. Due to variability in cloud top height, the parallax shifts produce an irregular grid of values since higher cloud tops are shifted further than lower cloud tops. A ball tree-based neighbor search with Haversine distance is performed using the Python-based scikit-learn library to find the nearest VISST grid point to each parallax correction-shifted point. The data value of the shifted point is then assigned to that VISST grid point. In this manner, the irregular geographical shifts to correct for parallax are projected back to the rectilinear VISST grid. Because relatively higher clouds should obscure lower clouds, the variable values for the highest cloud top are preferentially chosen if two or more values are assigned to a grid point. The parallax correction should be viewed as an improved but still imperfect estimation of the cloud top locations, largely because the cloud top height is an imperfect retrieval. Please see the attached README document for further information. Users are encouraged to contact the authors with any additional questions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

The Global Precipitation Patterns Associated with Short-Term Extratropical Climate Fluctuations

Two globally-complete, observation-only precipitation datasets have recently been developed for the Global Precipitation Climatology Project (GPCP). Both depend heavily on a variety of satellite input, as well as gauge data over land. The first, Version 2x79, provides monthly estimates on a 2.5 deg. x 2.5 deg. lat/long grid for the period 1979 through late 1999 (by the time of the conference). The second, the One-Degree Daily (1DD), provides daily estimates on a 1 deg. x l deg. grid for the period 1997 through late 1999 (by the time of the conference). Both are in beta test preparatory to release as official GPCP products. These datasets provide a unique perspective on the hydrological effects of the various atmospheric flow anomalies that have been identified by meteorologists. In this paper we discuss the regional precipitation effects that result from persistent extratropical flow anomalies. We will focus on the Pacific-North America (PNA) and North Atlantic Oscillation (NAO) patterns. Each characteristically becomes established on synoptic time scales, but then persists for periods that can exceed a month. The onset phase of each appears to have systematic mobile features, while the mature phase tend to be more stationary. Accordingly, composites of monthly data for outstanding positive and negative events (separately) contained in the 20-year record reveal the climatological structure of the precipitation during the mature phase. The climatological anomalies of the positive, negative, and (positive-negative) composites show the expected storm-track-related shifts in precipitation, and provide the advantage of putting the known precipitation effects over land in the context of the total pattern over land and ocean. As well, this global perspective points out some unexpected areas of correlation. Day-by-day composites of daily data anchored to the onset date demonstrate the systematic features during the onset. Although the 1DD has a fairly short record, some preliminary results are shown and compared to previous work with numerical weather prediction models.

Huffman, George J.↗
NASA NTRS1999

A Global Precipitation Perspective on Persistent Extratropical Flow Anomalies

Two globally-complete, observation-only precipitation datasets have recently been developed for the Global Precipitation Climatology Project (GPCP). Both depend heavily on a variety of satellite input, as well as gauge data over land. The first, Version 2 x 79, provides monthly estimates on a 2.5 deg x 2.5 deg lat/long grid for the period 1979 through late 1999 (by the time of the conference). The second, the One-Degree Daily (1DD), provides daily estimates on a 1 deg x 1 deg grid for the period 1997 through late 1999 (by the time of the conference). Both are in beta test preparatory to release as official GPCP products. These datasets provide a unique perspective on the hydrological effects of the various atmospheric flow anomalies that have been identified by meteorologists. In this paper we discuss the regional precipitation effects that result from persistent extratropical flow anomalies. We will focus on the Pacific-North America (PNA) and North Atlantic Oscillation (NAO) patterns. Each characteristically becomes established on synoptic time scales, but then persists for periods that can exceed a month. The onset phase of each appears to have systematic mobile features, while the mature phase tend to be more stationary. Accordingly, composites of monthly data for outstanding positive and negative events (separately) contained in the 20-year record reveal the climatological structure of the precipitation during the mature phase. The climatological anomalies of the positive, negative, and (positive-negative) composites show the expected storm-track-related shifts in precipitation, and provide the advantage of putting the known precipitation effects over land in the context of the total pattern over land and ocean. As well, this global perspective points out some unexpected areas of correlation. Day-by-day composites of daily data anchored to the onset date demonstrate the systematic features during the onset. Although the 1DD has a fairly short record, some preliminary results are shown and compared to previous work with numerical weather prediction models.

Huffman, George J.↗
NASA NTRS2007

Interannual Variability of Boreal Summer Rainfall in the Equatorial Atlantic

Tropical Atlantic rainfall patterns and variation during boreal summer [June-July-August (JJA)] are quantified by means of a 28-year (1979-2006) monthly precipitation dataset from the Global Precipitation Climatology Project (GPCP). Rainfall variability during boreal spring [March-April-May (MAM)] is also examined for comparison in that the most intense interannual variability is usually observed during this season. Comparable variabilities in the Intertropical Convergence Zone (ITCZ) strength and the basin-mean rainfall are found during both seasons. Interannual variations in the ITCZ's latitudinal location during JJA however are generally negligible, in contrasting to intense year-to-year fluctuations during MAM. Sea surface temperature (SST) oscillations along the equatorial region (usually called the Atlantic Nino events) and in the tropical north Atlantic (TNA) are shown to be the two major local factors modulating the tropical Atlantic climate during both seasons. During MAM, both SST modes tend to contribute to the formation of an evident interhemispheric SST gradient, thus inducing anomalous shifting of the ITCZ and then forcing a dipolar structure of rainfall anomalies across the equator primarily in the western basin. During JJA the impacts however are primarily on the ITCZ strength likely due to negligible changes in the ITCZ latitudinal location. The Atlantic Nino reaches its peak in JJA, while much weaker SST anomalies appear north of the equator in JJA than in MAM, showing decaying of the interhemispheric SST mode. SST anomalies in the tropical central-eastern Pacific (the El Nino events) have a strong impact on tropical Atlantic including both the tropical north Atlantic and the equatorial-southern Atlantic. However, anomalous warming in the tropical north Atlantic following positive SST anomalies in the tropical Pacific disappears during JJA because of seasonal changes in the large-scale circulation cutting off the ENSO influence passing through the mid-latitudes. Hence the anomalies associated with the tropical Pacific during JJA are forced through an anomalous Walker circulation primarily working on the western basin, and likely a lagged oceanic response in the equatorial region.

Gu, Guojun↗
DOE OSTI2025

Metagenome-assembled genomes from topsoils along a hillslope water gradient across early snowmelt to late summer in East River, CO

Drought is changing the American Mountain West at unprecedented rates with unknown consequences to soil microbiome composition and function. As a part of LBNL Watershed Science Focus Area (SFA), we investigated shifts in microbial community and transcriptional activity on a subalpine conifer-meadow transition zone throughout the summer of 2023 as soil dried down. This work took place in Crested Butte, CO on Snodgrass mountain, using a proxy for drought conditions.Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal community at 0-10cm from three sites along a hillslope water gradient across five timepoints from early snowmelt to late summer. 42 metagenomes were sequenced at Joint Genome Institute (JGI) and can be found under the JGI GOLD (Genomes Online Database) sequencing project Gs0166660. Metagenomes were assembled through an inhouse pipeline (see methods), binned using four autobinners (concoct, maxbin2, metabat2, and vamb) and consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>70%) and contamination (<10%), and dereplicated at 95% ANI using drep. This dataset (1) a zip file of 157 MAGs (as fasta files, Gs0166660_bins_tar.gz), (2) sample metadata file with sample IGSNs (International Generic Sample Numbers) (samples.csv), (3) bounding box coordinates for the sampled locations (Gs0166660.kml), (4) metagenome assembly and coassembly metadata file listing IMG/M (Integrated Microbial Genomes/Metagenomes) metagenome accessions linking samples to metagenomes (EastRiver_Drought_ESSDive_Metadata.csv), (5) location metadata file (locations.csv), (6) file-level metadata file (flmd.csv) and (7) data dictionary (dd.csv) file.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessment of Machine Learning for Ultrasonic Nondestructive Evaluation of Alkali–Silica Reaction in Concrete

Alkali–silica reaction (ASR) is a type of material degradation in concrete structures that leads to concrete cracking and rebar corrosion, thereby reducing the material’s structural integrity and the overall structure’s lifetime and raising safety concerns. Ultrasonic nondestructive evaluation (NDE) has been proven to be a valuable technique for assessing concrete properties and monitoring ASR progression in concrete. However, the deployment and analysis of ultrasonic NDE and its data requires specialized expertise, often relying on the engineer’s subjective interpretation. With the surge in computational power, artificial intelligence (AI) and machine learning (ML) algorithms have become popular in automating NDE data analysis. Various industrial sectors are increasingly adopting ML algorithms for NDE data analysis with a growing emphasis on AI–assisted automation. Regulatory agencies are also preparing for this technological shift, anticipating corresponding revisions in standards. Thus, there is an urgent need to identify the capabilities and limitations of current ML technologies for the evaluation of concrete material properties and damage status. Furthermore, the effects of various factors on ML model performance must be thoroughly investigated. The study summarized herein evaluated the effectiveness of two ML models (i.e., support vector regression (SVR) and deep neural network (DNN)) in predicting concrete material damage induced by ASR based on the long-term ultrasonic monitoring data. Four distinct concrete specimens were cast with artificially induced ASR, and over a period exceeding 500 days, ultrasonic signals and expansion data were continuously collected. For the SVR model, wave velocity and 12 other wave features were extracted from the ultrasonic signals, with 6 out of 13 features selected as input for the model. Different combinations of training and testing datasets were designed to explore factors influencing prediction performance, including the range of data within training and testing sets, in addition to various signal preprocessing methodologies. These findings suggest the importance of using a training dataset with a broader data range compared with testing datasets for improved model performance alongside consistent signal preprocessing across datasets.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Irrigation Induced Surface Cooling in the Context of Modern and Increased Greenhouse Gas Forcing

There is evidence that expected warming trends from increased greenhouse gas (GHG) forcing have been locally masked by irrigation induced cooling, and it is uncertain how the magnitude of this irrigation masking effect will change in the future. Using an irrigation dataset integrated into a global general circulation model, we investigate the equilibrium magnitude of irrigation induced cooling under modern (Year 2000) and increased (A1B Scenario, Year 2050) GHG forcing, using modern irrigation rates in both scenarios. For the modern scenario, the cooling is largest over North America, India, the Middle East, and East Asia. Under increased GHG forcing, this cooling effect largely disappears over North America, remains relatively unchanged over India, and intensifies over parts of China and the Middle East. For North America, irrigation significantly increases precipitation under modern GHG forcing; this precipitation enhancement largely disappears under A1B forcing, reducing total latent heat fluxes and the overall irrigation cooling effect. Over India, irrigation rates are high enough to keep pace with increased evaporative demand from the increased GHG forcing and the magnitude of the cooling is maintained. Over China, GHG forcing reduces precipitation and shifts the region to a drier evaporative regime, leading to a relatively increased impact of additional water from irrigation on the surface energy balance. Irrigation enhances precipitation in the Middle East under increased GHG forcing, increasing total latent heat fluxes and enhancing the irrigation cooling effect. Ultimately, the extent to which irrigation will continue to compensate for the warming from increased GHG forcing will primarily depend on changes in the background evaporative regime, secondary irrigation effects (e.g. clouds, precipitation), and the ability of societies to maintain (or increase) current irrigation rates.

Cook, Benjamin I.↗
NASA NTRSDate not supplied

Geochemical Insights Into Volcanic and Lithospheric Evolution of Mars

Introduction: The Martian lithosphere plays a pivotal role in volcanic processes, altering surface features, climate shifts, and the planet's early habitability. Crucially, the rigid lithosphere significantly influences Mars' long-term thermal conditions. Studying various geological eons’ volcanic compositions unveils how the lithosphere has evolved, even though understanding the early Noachian volcanic chemistry remains challenging due to weathering and resurfacing. In this study, newly discovered Noachian volcanic terranes[1-2] along with Hesperian and Amazonian volcanic terranes[3] are considered(Figure 1), to infer the evolution of the Martian lithosphere. Figure 1:Mars topographic map derived from MOLA-HRSC data [4] highlights the study regions including the Noachian volcanic terranes, Arabia Terra (AT), Thaumasia Minor (TM), and the Southwest Margin of Icaria Planum (SWIP)[5].Additionally, the Hesperian volcanic terranes such as Syrtis Major (SM), Hesperia Planum (HP), and, the Amazonian volcanic terranes encompass Elysium Mons (EM), Alba Patera (AP), and Olympus Mons (OM) are marked. Methods and Datasets: We use the most recent elemental mass fraction maps derived from gamma spectroscopy data from the Mars Odyssey 2001mission [6]to ascertain the bulk composition of the Martian landscape. Utilizing the updated geochemical provinces dataset of Mars[7], we consider bulk chemistry variations within our study regions. The maps, at a resolution of 50×50, encompass elements like Al, Ca, Fe, Si, K, Th, H2O, Cl, and S, detected through Gamma-Ray Spectroscopy (GRS) with decimeter scale depth sensitivity[6].Additional major and minor elements like Mg, Na, Ti, P, and Mn, using mass balance methods [8]serve as inputs for melting and crystallization simulations. We employ the pMELTS model with FMQ-3to FMQ oxygen fugacity to estimate the Pressure(P)and melting degree(F)in various eons of volcanic terranes. We have also used conventional thermobarometric calculations to determine their formation P-T conditions, using silica activity and olivine-melt Mg-exchange thermometry[9-10]. Results: Chemical Composition of Studied Volcanic Terranes: To assess formation conditions, we have investigated if GRS-measured compositions signify primary igneous processes by evaluating weathering through the Chemical Index of Alteration (CIA), K/Th ratios, and ternary plots for aqueous alteration. Consistent K/Th ratios and low CIA (<50) across volcanic regions suggest minimal large-scale weathering, affirming well-preserved igneous material extending at decimeter depths. In addition, the calculated bulk compositions align with Martian mantle equilibrium, confirming studied volcanic terranes-Arabia Terra, Thaumasia Minor, and SWIP -as primary or less altered compositions, reinforcing their representativeness at a regional GRS scale on Mars. We have also estimated the bulk compositions of Hesperian and Amazonian volcanic terranes shown in Figure 1. All volcanic terranes represent the primary or minimally altered composition. Temporal Evolution of Martian Volcanic Terranes: Our results show P-T conditions ranging from 1.3-1.6 GPa and 1350-1390°C for Noachian terranes, while Hesperian volcanic terranes vary from 1.6-1.7 GPa and 1370-1395°C, and Amazonian volcanic terranes range between 1.9-2.8 GPa and 1380-1415°C. Our analyses correspond to lithospheric thicknesses/ depth of melting for Noachian which ranges from110-135 km, 120-235 km for Hesperian terranes, and 160-235 km for Amazonian terranes. Partial melting percentages (F) range from 8-12% for Noachian, 10-11% for Hesperian, and 10-12% for Amazonian. We have also calculated mantle potential temperatures (Tp) to show variations across epochs(Figure 2). Heat flux estimation shows variations from 51-65 mW/m2 for Noachian, 38-45 mW/m2for Hesperian, and 27-39 mW/m2for Amazonian terranes, implying temporal changes in lithospheric thickness and heat flow. Comparison of Noachian volcanic terranes with Hesperian and Amazonian reveals variations in lithospheric thickness and heat flux, indicating potential implications for Martian surface conditions, including volcanic activity, climate evolution, and early habitability. Figure 2: P-T diagram displays formation conditions of studied Martian volcanic regions using GRS data, alongside Noachian-age surface basalt samples from Gusev, Gale, and Jezero. Dashed lines represent Martian mantle potential temperatures, calculated by adding the latent heat of fusion to the equilibrium temperature at which melt and solid mantle coexist and subtracting the Martian adiabatic gradient corresponding to the depth of melt. The solid line shows the Martian mantle solidus [11].Discussion& Implication: The study explores Martian volcanic activity across eons. Uniform lithospheric thickness from the Noachian to Hesperian eons suggests persistent weak plumes until Hesperian, influencing heat flow variations. Noachian's high heat flux, likely due to concentrated radioactive elements, shows spatial heterogeneity, indicating early Mars' differentiated mantle. Volcanic outgassing plays avital role in the formation of the Martian climate, likely sustained water on the surface, influencing warm-wet or cold-dry conditions. Hesperian's favorable lithospheric heat flow (45 mW/m2) supports extended water existence, resembling Earth's conditions. Whereas, Amazonian's diminished heat flux (25 mW/m2) corresponds to water loss and arid climate. Hesperian's similar lithospheric thickness to mid-Noachian implies prolonged water retention, influencing climate and potential for astrobiological research, expanding perspectives for future Martian missions. Future work: As volcanism was active throughout its history. The emergence of Mars' extensive volcanic regions, known as large igneous provinces, which are linked to intermittent volcanic activity driven by mantle plumes, poses challenges to understanding the scale and persistence of these phenomena in Martian convection models. Therefore, understanding the regional-scale changes in eruptive processes within Martian volcanic provinces over time remains unclear and crucial for deciphering the evolution of the Martian interior without Earth-like plate tectonics. We will continue this work with petrological and thermoelastic analyses to study the compositional and spatiotemporal evolution of the Elysium Volcanic Province.

A Rani↗
DOE OSTI2021

An Integrated View of Hydraulic Induced Fracture Geometry in Hydraulic Fracture Test Site 2

Until relatively recently, most of our understanding about the geometry of hydraulically induced fractures in unconventional reservoirs has been inferred by patterns observed via microseismic monitoring. Important information, such as fracture-azimuth, fracture-length, height-growth and other geometric data has been determined from microseismic “event clouds”, which in turn has been used to interpret a stimulated reservoir volume (SRV). It is important to note that relatively limited microseismic results have been acquired in conjunction with other diagnostics and validated in a consistent manner. The Hydraulic Fracture Test Site 2 (HFTS2) in the Permian Delaware Basin provides a unique opportunity to compare the frac geometry interpretations derived from multiple frac diagnostic tools and at multiple scales. The integrated view that emerges from all the frac diagnostic tools is that in HFTS2 the geometries of hydraulically induced fractures are not random and with a highly complex branching architecture. In fact, the fracs are mostly vertical, parallel plana domains, and both vertically and horizontally asymmetrical. The hydraulically induced fractures have a very consistent azimuth with a strike that matches SHmax. At the distance corresponding to the spacing between nearby wells in HFTS2, ~ 660 ft, the pattern of strain interceptions observed from Low Frequency Distributed Acoustic Sensing (LF-DAS) shows far-field dimensions that are consistent with the stage length dimensions at the stimulated well. In general, larger stages with higher number of clusters create larger number of interceptions and wider stimulated intervals than that of shorter stages with the same cluster to cluster spacing and fewer clusters. The hydraulically induced fractures also show a clear tendency to preferentially grow upwards as shown by the microseismic data, by the relative lower number of LF-DAS interceptions in nearby deeper wells and finally by the observed LF-DAS strain patterns in the vertical observation well. In the near field, the geometries of the fracture domains are also consistent. As shown by the distributed strain measurements obtained during production via the monitoring of Rayleigh Frequency Shift (RFS), each cluster has a separate, non-overlapping, frac-zone-domain that are generally centered around the locations of each perforation cluster. Overall, the hydraulically induced fractures in HFTS2 are interpreted as occurring in swarms associated with individual clusters, each with its own unique geometry but with similar predictable geometric and propagation tendencies. The comprehensive frac diagnostic program in HFTS2, the well-pad layout that permits the investigation of the Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S018R003/2477511/urtec-2021-5396-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5396 2 impact that nearby producing wells has on frac geometry, together with an innovative Design of Experiment (DofE) that includes sequential-fracing, consistent cluster-to-cluster distances and few single-perforation cluster stages, has allowed us to gain a unique perspective about the geometry of the induced hydraulic fractures on this pad. Finally, the HFTS2 dataset has also provided us with a better understanding of the applicability and limitations of the different diagnostic tools.

58 GEOSCIENCES↗
DOE OSTI2022

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants (4th Annual Report)

Nuclear plant sites collect and store large volumes of data collected from various equipment and systems. These datasets typically include plant process parameters, maintenance records, technical logs, online monitoring data, and equipment failure data. The collection of such data affords an opportunity to leverage data-driven machine learning and artificial intelligence technologies to provide diagnostic and prognostic capabilities within the nuclear power industry to reduce operating and maintenance costs. In this way, nuclear energy can become more economically competitive with other energy sources, and premature closures can be avoided. From a maintenance standpoint, savings can be achieved by leveraging machine learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose and predict potential faults within the system. Improved model accuracy can lead to reductions in unnecessary maintenance and more efficient planning of future maintenance, thus lowering the costs associated with parts, labor, and unnecessary planned, forced, or extended outages. From an operations perspective, cost savings can be generated by shifting from route-based monitoring to wireless technologies for online monitoring, and by transitioning from onsite- to cloud-based computing and storage services. Wireless monitoring would reduce the operator manhours required for taking routine measurements, while cloud computing services would generate cost savings by reducing the amount of hardware needing to be purchased and maintained—all while scaling to both computational and storage demands. This report summarizes this project’s effort to shift from costly, labor-intensive preventative maintenance to cheaper predictive maintenance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2017

Variability and Quasi-Decadal Changes in the Methane Budget over the Period 2000-2012

Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000- 2012, we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000-2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000-2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008-2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16-32] Tg CH4 yr(exp -1) higher methane emissions over the period 2008-2012 compared to 2002-2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002-2006 and 2008-2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

Saunois, Marielle↗
NASA NTRSDate not supplied

Insights into Long-Term Global Precipitation from IMERG and GPCP

Multiple satellite-based datasets provide estimates of the long-term record of global precipitation. Each necessarily includes both the real atmospheric behavior and a collection of artifacts driven by the input data sources and design choices in the retrievals and dataset construction. For this presentation, the Integrated Multi-satellitE Retrievals for GPM (IMERG) products from the Global Precipitation Measurement (GPM) mission’s U.S. Science Team are designed as a modern High-Resolution Precipitation Product (HRPP), while the Global Precipitation Climatology Project’s (GPCP) products are designed as a modern Climate Data Record (CDR). Although they share some common input data sources, the computational process for each is rather different. Comparing the precipitation estimates from each algorithm gives us insights into likely artifacts and the natural variations that are common to both. The goal of an HRPP is to give the best estimate of precipitation at each time step in the dataset, generally meaning that “all possible available” data are used. In contrast, the CDR is intended to provide a precipitation record that has relatively homogeneous statistics, necessary for climate analysis. Each analysis strives for both goals, of course, but this means that the HRPP uses the disparate collection of satellites whose statistics don’t quite match the ideal record, while the CDR is computed from fewer satellites that provide a relatively homogeneous set of precipitation statistics. This presentation employs the current versions of the IMERG and GPCP products, V07B and V3.2, respectively. A variety of analyses have demonstrated that IMERG has more artifacts, as expected, which tend to result from changes in the source of intercalibration for the various input satellites, namely the Combined Radar-Radiometer Algorithm using TMI and PR during the TRMM era and using GMI and DPR-Ku during the GPM era. As well, a shift occurs when the altitudes of the TRMM and GPM satellites change as a result of orbit boosts. For the most part the mean precipitation shows good continuity across these boundaries, but there are noticeable changes in the respective histograms. The latter has taken on more importance in recent years due to increased scrutiny on extremes which implicitly focus on the upper end of the precipitation histograms. The GPCP product is more homogeneous, with only one major change in calibrator, transitioning from the SSMI series of satellites to the SSMIS series of satellites in 2009. The GPCP analysis does a good job of minimizing artifacts in the means at this boundary, while the histograms show a smaller, but still noticeable shift in the histograms, a result that is similar to data boundaries in IMERG. The GPCP Daily, which is a month-by-month rescaling of the daily accumulated IMERG Final product, shows more consistency than the equivalent daily IMERG, but inherits the histogram shifts from IMERG. Given this overlay of artifacts, there is enough consistency between the products to illustrate some important long-term variations, including interannual variations, not all of which are easily attributable to ENSO events, and trends that are large regionally, but comparatively small when averaged across the globe.

precipitation↗
DOE OSTI2024

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Viability Assessment of Wind and Solar Renewable Energy Generation in Support of Nationwide Vehicle Electrification

In 2022, the U.S. transportation sector was the largest source of greenhouse gas emissions in the country, with the combination of passenger and commercial vehicles contributing 80% of these emissions. As adoption of passenger electric vehicles continues to climb, sights are being set on the electrification of heavy-duty commercial vehicle (HDCV) fleets. The sustainability of these shifts relies in part on the addition of significant renewable energy generation resources to both bolster the grid in the face of increased demand, and to prevent a shift in the source of greenhouse gas (GHG) emissions to the grid, as opposed to a true net reduction. Additionally, it is necessary to quantify the variations in economic viability across the country for these technologies as it pertains to their productive capabilities. Doing so will encourage investment and ensure that the transition to electrified HDCV fleets is commercially viable, as well as sustainable. In an effort to meet these goals, multiple computational frameworks are used to locate suitable land for renewable infrastructure development, and to quantify spatiotemporal variations in the potential energy generation and financial viability of development sites across the Unites States. First, the Oak Ridge Siting Analysis for power Generation Expansion tool (OR-SAGE) is used to assess the suitability of land for potential wind and solar energy development across the contiguous U.S. From there, resource data from the National Solar Radiation Database (NSRDB) and the Wind Integration National Dataset (WIND) are used in concert with the National Renewable Energy Laboratory (NREL) Renewable Energy Potential (ReV) model to calculate the variation in potential generation capacity for each resource. Additionally, the capital and operational expenditures are calculated for an example configuration of each renewable technology. These measures are then used to calculate the levelized cost of energy (LCOE) of potential sites. All of these results are then processed and analyzed to determine where in the U.S. solar and wind energy are most viable. This viability is based on available generation potential, consistency and stability of energy generation over time, and economic viability with respect to LCOE.

Miller, Brandon [ORNL] (ORCID:0009000300169201)↗
NASA NTRS2014

Irrigation as an Historical Climate Forcing

Irrigation is the single largest anthropogenic water use, a modification of the land surface that significantly affects surface energy budgets, the water cycle, and climate. Irrigation, however, is typically not included in standard historical general circulation model (GCM) simulations along with other anthropogenic and natural forcings. To investigate the importance of irrigation as an anthropogenic climate forcing, we conduct two 5-member ensemble GCM experiments. Both are setup identical to the historical forced (anthropogenic plus natural) scenario used in version 5 of the Coupled Model Intercomparison Project, but in one experiment we also add water to the land surface using a dataset of historically estimated irrigation rates. Irrigation has a negligible effect on the global average radiative balance at the top of the atmosphere, but causes significant cooling of global average surface air temperatures over land and dampens regional warming trends. This cooling is regionally focused and is especially strong in Western North America, the Mediterranean, the Middle East, and Asia. Irrigation enhances cloud cover and precipitation in these same regions, except for summer in parts of Monsoon Asia, where irrigation causes a reduction in monsoon season precipitation. Irrigation cools the surface, reducing upward fluxes of longwave radiation (increasing net longwave), and increases cloud cover, enhancing shortwave reflection (reducing net shortwave). The relative magnitude of these two processes causes regional increases (northern India) or decreases (Central Asia, China) in energy availability at the surface and top of the atmosphere. Despite these changes in net radiation, however, climate responses are due primarily to larger magnitude shifts in the Bowen ratio from sensible to latent heating. Irrigation impacts on temperature, precipitation, and other climate variables are regionally significant, even while other anthropogenic forcings (anthropogenic aerosols, greenhouse gases, etc.) dominate the long term climate evolution in the simulations. To better constrain the magnitude and uncertainties of irrigation-forced climate anomalies, irrigation should therefore be considered as another important anthropogenic climate forcing in the next generation of historical climate simulations and multimodel assessments.

simulation↗
DOE OSTI2023

Spatio-temporal and weather characterization of road loads of electrified heavy-duty commercial vehicles across U.S. interstate roads

Adoption of battery electric vehicles (BEV) in heavy duty (HD) commercial freight transportation is difficult due to technological and economic hurdles. Beyond safety and compliance, fleet and operational logistics necessitate both high uptime and parity with diesel system productivity/Total Cost of Ownership to support widespread deployment of electric powertrains. However, relatively high energy storage costs, along with the higher weight of BEV systems, limit the viability of HD commercial freight transport to shorter-range applications where smaller batteries will serve for mission energy requirements (single operational shift). Knowing the energy consumption and operating variations of these commercial vehicle systems is crucial for effectively sizing the energy storage systems. This paper is the first in a series of studies to understand the regional specific operating design domain variations of commercial Class 8 HD trucks and the associated impact to their energy requirements. In particular, the local weather conditions are shown to influence the total vehicle energy usage. Further, the impact of temperature, pressure, and humidity changes are shown to impact the local air density. This is needed to calculate aerodynamic drag on vehicles and has been found to play a significant role in the overall performance of a vehicle. Although the methodology of calculating air density varies only slightly throughout the literature, the application to transportation has still been limited. This study provides a means by which air density can be estimated for the contiguous U.S. using the NOAA MADIS dataset. These air density estimates were then used to determine vehicle performance in varying regions of the country to highlight the importance of consideration of weather variables when monitoring vehicle performance, but also to provide recommendations based on these locales upon fleet conversion to BEVs.

Moore, Amy↗
DOE OSTI2021

Modeling iterative reconstruction and displacement field in the large scale structure

The next generation of galaxy surveys like the Dark Energy Spectroscopic Instrument and Euclid will provide datasets orders of magnitude larger than anything available to date. Our ability to model nonlinear effects in late time matter perturbations will be a key to unlock the full potential of these datasets, and the area of initial condition reconstruction is attracting growing attention. Iterative reconstruction developed by Marcel Schmittfull et al. is a technique designed to reconstruct the displacement field from the observed galaxy distribution. The nonlinear displacement field and initial linear density field are highly correlated. Therefore, reconstructing the nonlinear displacement field enables us to extract the primordial cosmological information better than from the late time density field at the level of the two-point statistics. This paper will test to what extent the iterative reconstruction can recover the true displacement field and construct a perturbation theory model for the postreconstructed field. We model the iterative reconstruction process with Lagrangian perturbation theory (LPT) up to third order for dark matter in real space and compare it with N-body simulations. Here we find that the simulated iterative reconstruction does not converge to the nonlinear displacement field, and the discrepancy mainly appears in the shift term, i.e., the term correlated directly with the linear density field. On the contrary, our 3LPT model predicts that the iterative reconstruction should converge to the nonlinear displacement field. We discuss the sources of discrepancy, including numerical noise/artifacts on small scales, and present an ad hoc phenomenological model that improves the agreement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗