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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Effective Storage of Electrons in Water by the Formation of Highly Reduced Polyoxometalate Clusters

Aqueous solutions of polyoxometalates (POMs) have been shown to have potential as high-capacity energy storage materials due to their potential for multi-electron redox processes, yet the mechanism of reduction and practical limits are currently unknown. Herein, we explore the mechanism of multi-electron redox processes that allow the highly reduced POM clusters of the form {MO 3 } y to absorb y electrons in aqueous solution, focusing mechanistically on the Wells-Dawson structure X 6 [P 2 W 18 O 62 ], which comprises 18 metal centers and can uptake up to 18 electrons reversibly (y = 18) per cluster in aqueous solution when the countercations are lithium. This unconventional redox activity is rationalized by density functional theory, molecular dynamics simulations, UV-vis, electron paramagnetic resonance spectroscopy, and small-angle X-ray scattering spectra. These data point to a new phenomenon showing that cluster protonation and aggregation allow the formation of highly electron-rich meta-stable systems in aqueous solution, which produce H 2 when the solution is diluted. Finally, we show that this understanding is transferrable to other salts of [P 5 W 30 O 110 ] 15- and [P 8 W 48 O 184 ] 40- anions, which can be charged to 23 and 27 electrons per cluster, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Ionic conductivity and dielectric permittivity of PEO-LiClO{sub 4} solid polymer electrolyte plasticized with propylene carbonate

We have studied ionic conductivity and dielectric permittivity of PEO-LiClO{sub 4} solid polymer electrolyte plasticized with propylene carbonate. Differential scanning calorimetry and X-ray diffraction studies confirm minimum volume fraction of crystalline phase for the polymer electrolyte with 40 wt. % propylene carbonate. The ionic conductivity exhibits a maximum for the same composition. The temperature dependence of the ionic conductivity has been well interpreted using Vogel-Tamman-Fulcher equation. Ion-ion interactions in the polymer electrolytes have been studied using Raman spectra and the concentrations of free ions, ion-pairs and ion-aggregates have been determined. The ionic conductivity increases due to the increase of free ions with the increase of propylene carbonate content. But for higher content of propylene carbonate, the ionic conductivity decreases due to the increase of concentrations of ion-pairs and ion-aggregates. To get further insights into the ion dynamics, the experimental data for the complex dielectric permittivity have been studied using Havriliak–Negami function. The variation of relaxation time with temperature obtained from this formalism follows Vogel-Tamman-Fulcher equation similar to the ionic conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2025

NERSC_Lightweight Distributed Metric Service (NERSC_LDMS) v4.4.2

Miscellany This LDMS Loftsman/Helm Chart horizontally scales LDMS daemons in order to achieve a 1Hz sample rate from over 5,000 nodes, collecting 38k metrics per minute on Perlmutter. This LMDS Configuration relies on already running `ldmsd` producers running on nodes, which produce metrics via sampler plugins. The Helm chart distributes the collection of metrics from producer acrross many aggregator and storage `ldmsd` daemons, ensuring no damon is overloaded and data loss is avoided.

Stile, John [Lawrence Berkeley National Laboratory↗
DOE OSTI2016

Quantification of massive seasonal aggregations of blacktip sharks ( Carcharhinus limbatus ) in Southeast Florida

Southeast Florida witnesses an enormous seasonal influx of upper trophic level marine predators each year as massive aggregations of migrating blacktip sharks ( Carcharhinus limbatus ) overwinter in nearshore waters. The narrow shelf and close proximity of the Gulf Stream current to the Palm Beach County shoreline drive tens of thousands of sharks to the shallow, coastal environment. This natural bottleneck provides a unique opportunity to estimate relative abundance. Over a four year period from 2011–2014, an aerial survey was flown approximately biweekly along the length of Palm Beach County. A high definition video camera and digital still camera mounted out of the airplane window provided a continuous record of the belt transect which extended 200 m seaward from the shoreline between Boca Raton Inlet and Jupiter Inlet. The number of sharks within the survey transect was directly counted from the video. Shark abundance peaked in the winter (January-March) with a maximum in 2011 of 12,128 individuals counted within the 75.6 km -2 belt transect. This resulted in a maximum density of 803.2 sharks km -2 . By the late spring (April-May), shark abundance had sharply declined to 1.1% of its peak, where it remained until spiking again in January of the following year. Shark abundance was inversely correlated with water temperature and large numbers of sharks were found only when water temperatures were less than 25°C. Shark abundance was also correlated with day of the year but not with barometric pressure. Although shark abundance was not correlated with photoperiod, the departure of the sharks from southeast Florida occurred around the vernal equinox. The shark migration along the United States eastern seaboard corresponds spatially and temporally with the spawning aggregations of various baitfish species. As a result, these baseline abundance data can be compared to future studies to determine if shark population size is changing and if sharks are restricting their southward migration as global water temperatures increase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Characterization of PTO and Idle Behavior for Utility Vehicles

This report presents the results of analyses performed on utility vehicle data composed primarily of aerial lift bucket trucks sampled from the National Renewable Energy Laboratory's Fleet DNA database to characterize power takeoff (PTO) and idle operating behavior for utility trucks. Two major data sources were examined in this study: a 75-vehicle sample of Odyne electric PTO (ePTO)-equipped vehicles drawn from multiple fleets spread across the United States and 10 conventional PTO-equipped Pacific Gas and Electric fleet vehicles operating in California. Novel data mining approaches were developed to identify PTO and idle operating states for each of the datasets using telematics and controller area network/onboard diagnostics data channels. These methods were applied to the individual datasets and aggregated to develop utilization curves and distributions describing PTO and idle behavior in both absolute and relative operating terms. This report also includes background information on the source vehicles, development of the analysis methodology, and conclusions regarding the study's findings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Nailing the Peak: City-Scale, Building-Specific Load Factor and Contribution to a Utility’s Hour of Critical Generation

Maintaining electrical generation assets to meet peak demand increases the cost of providing electricity to a country’s buildings and insufficient assets can result in power outages. In order to keep reliable electricity costs low for consumers and demand charges low for utilities, there exist markets and financial incentives for limiting consumption during peak demand.The team has partnered with an electrical distributor servicing a 1,390 km2 area and 178,368 buildings with the aim of using urban-scale building energy modelling to inform business decisions necessary for the operation of their electric grid. A suite of software has been developed that allows the scalable creation of a “digital twin” for all buildings in the utility’s service area. This virtual utility area is analysed for targeted deployment of new technologies or policies to assess building-specific savings, effects on critically-loaded grid infrastructure (e.g. feeders, substations), and aggregated impact to utility-scale operations.This work leverages 15-minute data from each building to compare actual and simulated monthly peak-hour demand and assessment of the load factor for each building. Findings include market characterization via clustering of relative energy use profiles for ~180,000 buildings as well as simulation-informed savings opportunities indicating residential load factors of 0.17, commercial load factors of 0.2-0.4 depending on year of construction, and general load factors of 0.16-0.5 depending on building type.

New, Joshua↗
DOE OSTI2023

A General Method for Estimating Zonal Transmission Interface Limits from Nodal Network Data: Preprint

Capacity expansion models for the electric power system often employ zonal (rather than nodal) resolution, necessitating estimates of aggregate power transfer limits across the interfaces between model zones. Interface limits between planning areas are sometimes published, but they are not generalizable to arbitrary zone shapes. There is thus a need for a reproducible method for estimating interface transfer limits (ITLs) between user-defined zones directly from nodal transmission system data. Here, we present a simple method for estimating ITLs using a DC power flow approximation via the power transfer distribution factor (PTDF) matrix. Linear optimization is performed to identify the distribution of power flows that maximizes the total flow on interface-crossing lines, subject to individual line ratings, limits on bus injection/withdrawal, and the relationships among flows, injections, and withdrawals imposed by the PTDF matrix. We demonstrate the application of the method on a 134-zone ~65000-bus system, and we explore the influence of flow direction, contingency level, and zone size on the estimated ITLs. There is significant heterogeneity in the ratio of the ITL to the sum of interface-crossing line ratings, which highlights the importance of accounting for the physical constraints on power flows imposed by Kirchhoff's laws when estimating zonal ITLs.

17 WIND ENERGY↗
DOE OSTI2018

The F-t-Pj-RG method: An adjacent-rolling-windows based steady-state detection technique for application to kinetic Monte Carlo simulations

A window-based steady-state detection algorithm has been developed for application to kinetic Monte Carlo simulation data. The algorithm, termed F-t-Pj-RG sequentially applies an F-test, a t-test, and a projection test on adjacent windows of the data while rolling (or shifting) and growing the windows when any of the tests fail. In aggregate, the algorithm is able to (a) automatically reject the warm-up period as not being at steady-state, as well as (b) determine an appropriate window size for converged statistics when sampling the data, which is necessary for detection of steady-state, and (c) detect steady-state within a particular tolerance. The last step, the projection test, is actually an oscillating-slope projection test, and is performed on j sequential data windows (i.e., more than two adjacent windows). It requires more than simply being within the user defined tolerance: the oscillating-slope projection test includes a condition that the slope must oscillate around zero when 2, which is an additional indication of steady-state. When all three tests are passed, the F-t-Pj test is passed, indicating that the prerequisites of steady-state detection have been met and also that conditions consistent with the definition of steady-state have been realized. This algorithm is applied to a variety of data sets that correspond to the diverse type of data trends that can be produced by kinetic Monte Carlo simulations. The algorithm is shown to be robust in its ability to handle differing functional forms, and is able to detect steady-state with low computational cost. Finally, the low computational cost of this method and its robustness towards varied data trends make it suitable for on-the-fly use in kinetic Monte Carlo simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Development and Evaluation of Algorithms to Improve Small- and Medium-Size Commercial Building Operations

Small- and medium-sized (<100,000 sf) commercial buildings (SMBs) represent over 95% of the U.S. commercial building stock and consume over 60% of total site energy consumption. Many of these buildings use rudimentary controls that are mostly manual, with limited scheduling capability, no monitoring or failure management. Therefore, many of these buildings are operated inefficiently and consume excess energy. SMBs typically utilize packaged rooftop units (RTUs) that are controlled by an individual thermostat. There is increased urgency to improve the operating efficiency of existing commercial building stock in the U.S. for many reasons, chief among them is to mitigate the climate change impacts. Studies have shown that managing set points and schedules of the RTUs will result in up to 20% energy and cost savings. Another problem associated with RTUs is short-cycling, where an RTU goes through ON and OFF cycles too frequently. Excessive cycling can lead to excessive wear and lead to premature failure of the compressor or its components. The short cycling can result in a significantly decreased average efficiency (up to 10%), even if there are no physical failures in the equipment. Also, SMBs use a time-of-day scheduling is to start the RTUs before the building will be occupied and shut it off when unoccupied. Ensuring correct use of the zone set points and eliminating frequent cycling of RTUs thereby leading to persistent building operations can significantly increase the operational efficiency of the SMBs. A growing trend is to use low-cost control infrastructure that can enable scalable and cost-effective intelligent building operations. The work reported in this report describes three algorithms for detecting the zone set point temperature, RTU cycling rate and occupancy schedule detection that can be deployed on the low-cost infrastructure. These algorithms only require the zone temperature data for detection. The algorithms have been tested and validated using field data from a number of RTUs from six buildings in different climate locations. Overall, the algorithms were successful in detecting the set points and ON/OFF cycles accurately using the peak detection technique and occupancy schedule using symbolic aggregate approximation technique. The report describes the three algorithms, results from testing the algorithms using field data, how the algorithms can be used to improve SMBs efficiency, and presents related conclusions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

High-resolution imaging of Hg/Se aggregates in the brain of small Indian mongoose, a wild terrestrial species: insights into intracellular Hg detoxification

Human activities result in the emission of 2000 metric tons of mercury compounds annually. Mercury (Hg) biomagnification has been characterized in marine mammals and predatory fish; however, little is known about mercury accumulation in brains of wild terrestrial species. Elevated Hg content, of 1.27 μg/g wet wt.—found in the brain of wild small Indian mongoose, prompted us to use synchrotron X-ray fluorescence imaging for simultaneous, quantitative mapping of biologically relevant and neurotoxic elements with high spatial resolution. X-ray fluorescence combined with immunohistochemistry revealed ~0.5–1.9 micron Hg-rich aggregates in cells of the choroid plexus and astrocytes of the subventricular wall in the mongoose brain. Hg content within aggregates correlated with selenium. Hg aggregates did not co-localize with lysosomes. The low Hg density inside aggregates indicated diffuse Hg binding to a Se-containing biomolecule, rather than much denser HgSe nanoparticles proposed to form in other species. Our data show the susceptibility of the small Indian mongoose population to Hg pollution and highlight the vulnerability of the brain as an organ targeted by mercury. Data also provide evidence on the adaptation in the form of a Se-based detoxification mechanism sequestering Hg into intracellular aggregates.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Electromagnetic Transient Modeling of Large Data Centers for Grid-Level Studies

The magnitude and complexity of electricity usage patterns from large data centers are having significant impacts on the operation and dynamics of the power grid; grid operators and planners require a range of specialized data center models to properly evaluate these impacts and specify technical solutions as needed. Towards addressing this need, Pacific Northwest National Laboratory (PNNL) has developed a library of electromagnetic transient (EMT) models for grid-level studies of data centers called the data center model library (DML). This report describes how the DML was created and how it may properly be used. The models present in the DML are generic models; subject matter expertise and additional technical data are needed to modify these models before they can represent any real data center. However, they will significantly reduce the level of effort required to develop site-specific models and can serve as a common starting point to guide industry towards a more refined consensus. Most of the models within DML are dedicated to representing the power electronics interfaces commonly used in modern data centers, such as double-conversion uninterruptible power supplies and single-phase power factor correction converters. These models are intended for use in grid-level studies and are a simplified aggregation of many small components. That said, background material on the physical and electrical design of large data centers is provided as companion material so that users can be aware of many of the details which have been omitted or streamlined as a matter of practical necessity. Additionally, guidance on the application of EMT analysis for data center interconnection studies is provided, which aids users in identifying when the DML is necessary and what sort of additional model development may be necessary for conducting real-world studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Electromagnetic Transient Modeling of Large Data Centers for Grid-Level Studies: Beta Release

The magnitude and complexity of electricity usage patterns from large data centers are having significant impacts on the operation and dynamics of the power grid; grid operators and planners require a range of specialized data center models to properly evaluate these impacts and specify technical solutions as needed. Towards addressing this need, Pacific Northwest National Laboratory (PNNL) has developed a library of electromagnetic transient (EMT) models for grid-level studies of data centers called the data center model library (DML). This report describes how the DML was created and how it may properly be used. This report details the DML’s beta release, completed in July 2026. This is a revision and expansion of the alpha release, which was made available in January 2026 The models present in the DML are generic models; subject matter expertise and additional technical data are needed to modify these models before they can represent any real data center. However, they will significantly reduce the level of effort required to develop site-specific models and can serve as a common starting point to guide industry towards a more refined consensus. Most of the models within DML are dedicated to representing the power electronics interfaces commonly used in modern data centers, such as double-conversion uninterruptible power supplies and single-phase power factor correction converters. These models are intended for use in grid-level studies and are a simplified aggregation of many small components. That said, background material on the physical and electrical design of large data centers is provided as companion material so that users can be aware of many of the details which have been omitted or streamlined as a matter of practical necessity. Additionally, guidance on the application of EMT analysis for data center interconnection studies is provided, which aids users in identifying when the DML is necessary and what sort of additional model development may be necessary for conducting real-world studies.

electromagnetic transients↗
DOE OSTI2019

A Community EcoHealth Index from EnviroAtlas Ecosystem Services Metrics

Human health is inextricably tied to ecosystem services (ES), including those associated with greenspace in urban communities. EnviroAtlas provides close to 100 maps of ES metrics based on high-resolution land cover data in featured communities across the contiguous United States. Using selected EnviroAtlas ES metrics, a Community EcoHealth Index (CEHI) was created based on an ecohealth framework including health promotion and hazard buffering domains. Aggregation of eight selected ES metrics in these domains entailed a weighted distance measure, where objective, data-driven weights were generated. CEHI was calculated by Census Block Group (CBG) at both the local level and the national level for 22 EnviroAtlas communities. Results were mapped to show one- to five-star CBGs or neighborhoods within and across all 22 featured communities. At the national level, CEHI favors communities in forested ecoregions. The local version of CEHI is more appropriate to inform social, economic, and environmental decision-making for improving community ES associated with human health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling

Existing estimates of methane (CH 4 ) fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these differences, this study uses atmospheric CH 4 observations from the US and Canada to analyze seven different bottom-up, wetland CH 4 estimates reported in a recent model comparison project. We first use synthetic data to explore whether wetland CH 4 fluxes are detectable at atmospheric observation sites. We find that the observation network can detect aggregate wetland fluxes from both eastern and western Canada but generally not from the US. Based upon these results, we then use real data and inverse modeling results to analyze the magnitude, seasonality, and spatial distribution of each model estimate. The magnitude of Canadian fluxes in many models is larger than indicated by atmospheric observations. Many models predict a seasonality that is narrower than implied by inverse modeling results, possibly indicating an oversensitivity to air or soil temperatures. The LPJ-Bern and SDGVM models have a geographic distribution that is most consistent with atmospheric observations, depending upon the region and season. Lastly, these models utilize land cover maps or dynamic modeling to estimate wetland coverage while most other models rely primarily on remote sensing inundation data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Aggregate Load Controllers and Associated Methods

Aggregate load controllers and associated methods are described. According to one aspect, a method of operating an aggregate load controller includes using an aggregate load controller having an initial state, applying a stimulus to a plurality of thermostatic controllers which are configured to control a plurality of respective thermostatic loads which receive electrical energy from an electrical utility to operate in a plurality of different operational modes, accessing data regarding a response of the thermostatic loads as a result of the applied stimulus, using the data regarding the response, determining a value of at least one design parameter of the aggregate load controller, and using the determined value of the at least one design parameter, configuring the aggregate load controller to control amounts of the electrical energy which are utilized by the thermostatic loads.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Electronic structure study of screw dislocation core energetics in Aluminum and core energetics informed forces in a dislocation aggregate

Here we use a real-space formulation of orbital-free DFT to study the core energetics and core structure of an isolated screw dislocation in Aluminum. Using a direct energetics based approach, we estimate the core size of a perfect screw dislocation to be ≈ 7 |b|, which is considerably larger than previous estimates of 1–3 |b| based on displacement fields. The perfect screw upon structural relaxation dissociates into two Shockley partials with partial separation distances of 8.2 Å and 6.6 Å measured from the screw and edge component differential displacement plots, respectively. Similar to a previous electronic structure study on edge dislocation, we find that the core energy of the relaxed screw dislocation is not a constant, but strongly dependent on macroscopic deformations. Next, we use the edge and screw dislocation core energetics data with physically reasonable assumptions to develop a continuum energetics model for an aggregate of dislocations that accounts for the core energy dependence on macroscopic deformations. Further, we use this energetics model in a discrete dislocation network, and from the variations of the core energy with respect to the nodal positions of the network, we obtain the nodal core force which can directly be incorporated into discrete dislocation dynamics frameworks. We analyze and classify the nodal core force into three different contributions based on their decay behavior. Two of these contributions to the core force, both arising from the core energy dependence on macroscopic deformations, are not accounted for in currently used discrete dislocation dynamics models which assume the core energy to be a constant excepting for its dependence on the dislocation line orientation. Using case studies involving simple dislocation structures, we demonstrate that the contribution to the core force from the core energy dependence on macroscopic deformations can be significant in comparison to the elastic Peach–Koehler force even up to distances of 10–15 nm between dislocation structures. Thus, these core effects, whose origins are in the electronic structure of the dislocation core, can play an important role in influencing dislocation-dislocation interactions to much larger distances than considered heretofore.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Strong Lens Discoveries in DESI Legacy Imaging Surveys DR10 with Two Deep Learning Architectures

Abstract We have conducted a search for strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 10 (DR10). This paper is the fourth in a series of searches. This is the first catalog of lens candidates covering nearly the entirety of the extragalactic sky south of declination δ ≈ +32 ∘ , all observed by DECam, covering ∼14,000 deg 2 . We impose a z -band magnitude cut of <20 in AB magnitude. We deploy a residual neural network and EfficientNet as an ensemble trained on a compilation of known lensing systems and high-grade candidates as well as nonlenses in the same footprint. The predictions from these two base models are aggregated using a meta-learner. After applying our ensemble to the survey data, we exclude known candidates and systems, and use our own visual inspection portal to rank images in the top 0.01 percentile of all neural network recommendations. We have found 811 lens candidates, five of which are confirmed through Euclid Quick Data Release (Q1). These include 484 new candidates in the Legacy Surveys DR9 footprint, all parts of which have been searched for strong lenses at least once before, either by our group or others. Combining the discoveries from this work with those from the first three papers in this series (335, 1210, and 1512), we have discovered a total of 3868 new candidates in the DESI Legacy Surveys.

Inchausti, Jose Carlos [University of San Francisc↗