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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Institutional Framework of Variable Renewable Energy Forecasting in India

The share of variable renewable energy (VRE) in India is growing rapidly, with a national goal of reaching 50% capacity from non-fossil fuel generation by 2030. One implication of this growth is the need for improved VRE forecasting methods. For this reason, the Ministry of New and Renewable Energy (MNRE) in India commissioned this study with support from the United States Agency for International Development (USAID), the National Renewable Energy Laboratory (NREL) in the United States, and the National Institute of Wind Energy (NIWE) in India. The objective of this study was to review the existing institutional framework and suggest changes needed to support the plans for large-scale VRE integration in the country. To achieve that objective, the authors consulted local stakeholders about the status of VRE forecasting in India, reviewed existing studies, and examined VRE forecasting methods around the world to identify best practices. Based on those best practices, the study presents six potential approaches to improve the VRE forecasting framework in India. Approaches include incentivizing VRE forecast improvement and use of the most accurate VRE forecast, creating an institution that will optimize VRE forecasts while maintaining and ensuring access to necessary data for forecasting, implementing a review and certification process for VRE forecast providers, forecasting closer to dispatch time and allowing for more frequent forecast revisions, increasing the frequency of weather forecasts, and aggregating VRE forecasts at the point of interconnection.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Investigation of metal ion extraction and aggregate formation combining acidic and neutral organophosphorous reagents

In the present study, we investigate how varying mixtures of tri-n-butyl phosphate (TBP) and dibutyl phosphate (HDBP) results in enhanced extraction of lanthanum(III), La{sup 3+}, and dysprosium(III), Dy{sup 3+}. Water and metal ion extraction were carefully monitored as a function of TBP:HDBP mole ratio.In addition to these techniques, EXAFS was used to determine the coordination environment of the metal ion in this system. To produce the necessary signal, a concentration of 1.25*10{sup -3} M La{sup 3+} and Dy{sup 3+} was used. Although previous studies of synergistic extraction of metal cations using combinations of neutral and acidic reagents explain the enhanced extraction by increased dehydration of the metal ion and the formation of mixed extractant complexes, our evidence for the increased water extraction coupled with the aggregate formation suggests a reverse micellar aspect to synergism in the system containing TBP and HDBP. It is quite possible that both of these phenomena contribute to our system behavior. The EXAFS data shows that, based on coordination numbers alone, several possible structures may exist. From this study, we cannot provide a definitive answer as to the nature of extraction in this system or the exact complex formed during extraction.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

Grid Data Access on Widely Distributed Worker Nodes Using Scalla and SRM

Facing the reality of storage economics, NP experiments such as RHIC/STAR have been engaged in a shift of the analysis model, and now heavily rely on using cheap disks attached to processing nodes, as such a model is extremely beneficial over expensive centralized storage. Additionally, exploiting storage aggregates with enhanced distributed computing capabilities such as dynamic space allocation (lifetime of spaces), file management on shared storages (lifetime of files, pinning file), storage policies or a uniform access to heterogeneous storage solutions is not an easy task. The Xrootd/Scalla system allows for storage aggregation. We will present an overview of the largest deployment of Scalla (Structured Cluster Architecture for Low Latency Access) in the world spanning over 1000 CPUs co-sharing the 350 TB Storage Elements and the experience on how to make such a model work in the RHIC/STAR standard analysis framework. We will explain the key features and approach on how to make access to mass storage (HPSS) possible in such a large deployment context. Furthermore, we will give an overview of a fully 'gridified' solution using the plug-and-play features of Scalla architecture, replacing standard storage access with grid middleware SRM (Storage Resource Manager) components designed for space management and will compare the solution with the standard Scalla approach in use in STAR for the past 2 years. Integration details, future plans and status of development will be explained in the area of best transfer strategy between multiple-choice data pools and best placement with respect of load balancing and interoperability with other SRM aware tools or implementations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Forecasting influenza activity using machine-learned mobility map

Human mobility is a primary driver of infectious disease spread. However, existing data is limited in availability, coverage, granularity, and timeliness. Data-driven forecasts of disease dynamics are crucial for decision-making by health officials and private citizens alike. In this work, we focus on a machine-learned anonymized mobility map (hereon referred to as AMM) aggregated over hundreds of millions of smartphones and evaluate its utility in forecasting epidemics. We factor AMM into a metapopulation model to retrospectively forecast influenza in the USA and Australia. We show that the AMM model performs on-par with those based on commuter surveys, which are sparsely available and expensive. We also compare it with gravity and radiation based models of mobility, and find that the radiation model’s performance is quite similar to AMM and commuter flows. Additionally, we demonstrate our model’s ability to predict disease spread even across state boundaries. Our work contributes towards developing timely infectious disease forecasting at a global scale using human mobility datasets expanding their applications in the area of infectious disease epidemiology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Considerations and code for partial volume correcting [ 18 F]-AV-1451 tau PET data

[ 18 F]-AV-1451 is a leading tracer used with positron emission tomography (PET) to quantify tau pathology. However, [ 18 F]-AV-1451 shows “off target” or non-specific binding, which we define as binding of the tracer in unexpected areas unlikely to harbor aggregated tau based on autopsy literature. Along with caudate, putamen, pallidum and thalamus nonspecific binding, we have found binding in the superior portion of the cerebellar gray matter, leading us to use inferior cerebellar gray as the reference region. We also addressed binding in the posterior portion of the choroid plexus. PET signal unlikely to be associated with tau also occurs in skull, meninges and soft tissue. We refer to [ 18 F]- AV-1451 binding in the skull and meninges as extra-cortical hotspots (ECH) and find them near lateral and medial orbitofrontal, lateral occipital, inferior and middle temporal, superior and inferior parietal, and inferior cerebellar gray matter. Lastly, the choroid plexus also shows nonspecific binding that bleeds into hippocampus. We are providing the code (http://www.runmycode.org/companion/view/2798) used to create different regions of interest (ROIs) that we then used to perform Partial Volume Correction (PVC) using the Rousset geometric transfer matrix method. This method was used in the companion article, “Comparison of multiple tau-PET measures as biomarkers in aging and Alzheimer's Disease” (DOI 10.1016/j.neuroimage.2017.05.058).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features

Residential electricity load profiles and their diversity have become increasingly important to realize the benefits of Smart or Transactive Energy Networks (TENs). An important element of TENs will be practical, accurate, and implementable residential load forecasting techniques. While there have been many approaches to short-term load forecasting, few have included forecasting for individual households, partly because the high volatility and idiosyncrasies present in individual household load data can pose significant challenges. In this study, we develop a Convolutional Long Short-Term Memory-based neural network with Selected Autoregressive Features (termed a CLSAF model) to improve short-term household electricity load forecasting accuracy by employing three strategies: autoregressive features selection, exogenous features selection, and a “default” state to avoid overfitting at times of high load volatility. We include aggregations of apartments to floor and building level, because utilities may favor transactive approaches that rely on aggregator models, e.g., a cluster of consumers as opposed to an individual. We demonstrate that the CLSAF model, by virtue of its enhanced feature representation and modest computational resources, can accomplish load forecasting in a multi-family residential building across three spatial granularities (individual apartment/household, floor, and building levels), with an accuracy improvement of up to 25% compared to a persistence model. We propose a data screening technique to characterize time-series electricity-load data. This technique is suitable for integration into a TEN ecosystem and allows one to estimate confidence levels of the load forecasts to optimize computational resources and the risks associated with uncertain forecasts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion

The authors built and tested a stochastic simulation to estimate achieved detection probabilities (DPs) on a stratum basis, over a tailorable range of diverted amounts from 0 to 2 significant quantities (SQ), using typical International Atomic Energy Agency (IAEA) inspection data: i.e., SQ in stratum, number of items, number of gross/partial/bias defect measurements conducted, and realistic relative standard deviation (RSD) values for typical IAEA verification measurements. For bulk strata, the model calculates achieved DP at 0.01 SQ diversion increments; for item strata, the model calculates DP using the smallest realistic diversion increment (e.g., a plate, pin, or coupon). After successfully benchmarking against IAEA deterministic models, the simulation was used to test the sensitivity of DP to certain standard assumptions and selected input parameters. First, the equal defect assumption was tested; the results suggest significant complexity in the effectiveness of partial defect measurements. Next, the authors explored the sensitivity of DP to the assumed RSD of attribute tests. Then, the authors compared non-normal models for instrument performance (e.g., logistic, step, or arbitrary functions) to the typical results from a normal distribution (characterized by RSD). This last comparison was supplemented with experimentally derived performance data for an HM-5 gamma spectrometer. The HM-5 was used to make enrichment measurements on both LEU and HEU MTR fuel elements as plates were removed, and the results fit with logistic and step curves and applied in the simulation. These stochastic DP results were compared to DP estimates from a deterministic model assuming a normal curve and typical RSD, yielding insights that could improve effectiveness in the field. These early results illustrate the potential of stochastic models to better understand achieved DP and to improve safeguards effectiveness.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Evaluating the contribution of plant metabolic pathways in the light to the ATP:NADPH demand using a meta-analysis of isotopically non-stationary metabolic flux analyses

Abstract Balancing the ATP: NADPH demand from plant metabolism with supply from photosynthesis is essential for preventing photodamage and operating efficiently, so understanding its drivers is important for integrating metabolism with the light reactions of photosynthesis and for bioengineering efforts that may radically change this demand. It is often assumed that the C3 cycle and photorespiration consume the largest amount of ATP and reductant in illuminated leaves and as a result mostly determine the ATP: NADPH demand. However, the quantitative extent to which other energy consuming metabolic processes contribute in large ways to overall ATP: NADPH demand remains unknown. Here, we used the metabolic flux networks of numerous recently published isotopically non-stationary metabolic flux analyses (INST-MFA) to evaluate flux through the C3 cycle, photorespiration, the oxidative pentose phosphate pathway, the tricarboxylic acid cycle, and starch/sucrose synthesis and characterize broad trends in the demand of energy across different pathways and compartments as well as in the overall ATP:NADPH demand. These data sets include a variety of species including Arabidopsis thaliana , Nicotiana tabacum , and Camelina sativa as well as varying environmental factors including high/low light, day length, and photorespiratory levels. Examining these datasets in aggregate reveals that ultimately the bulk of the energy flux occurred in the C3 cycle and photorespiration, however, the energy demand from these pathways did not determine the ATP: NADPH demand alone. Instead, a notable contribution was revealed from starch and sucrose synthesis which might counterbalance photorespiratory demand and result in fewer adjustments in mechanisms which balance the ATP deficit.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Meso-scale modeling of irradiated concrete in test reactor

In this paper, we detail a numerical model accounting for the effects of neutron irradiation on concrete at the mesoscale. Irradiation experiments in test reactor (Elleuch et al.,1972), i.e., in accelerated conditions, are simulated. Concrete is considered as a two-phase material made of elastic inclusions (aggregate) subjected to thermal and irradiation-induced swelling and embedded in a cementitious matrix subjected to shrinkage and thermal expansion. The role of the hardened cement paste in the post-peak regime (brittle-ductile transition with decreasing loading rate), and creep effects are investigated. Radiation-induced volumetric expansion (RIVE) of the aggregate cause the development and propagation of damage around the aggregate which further develops in bridging cracks across the hardened cement paste between the individual aggregate particles. The development of damage is aggravated when shrinkage occurs simultaneously with RIVE during the irradiation experiment. The post-irradiation expansion derived from the simulation is well correlated with the experimental data and, the obtained damage levels are fully consistent with previous estimations based on a micromechanical interpretation of the experimental post-irradiation elastic properties (Le Pape et al.,2015). In conclusion, the proposed modeling opens new perspectives for the interpretation of test reactor experiments in regards to the actual operation of light water reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Characterization of Aβ Monomers through the Convergence of Ensemble Properties among Simulations with Multiple Force Fields

We found that amyloid β (Aβ) monomers represent a base state in the pathways of aggregation that result in the fibrils and oligomers implicated in the pathogenesis of Alzheimer’s disease (AD). The structural properties of these intrinsically disordered peptides remain unclear despite extensive experimental and computational investigations. Further, there are mutations within Aβ that change the way the peptide aggregates and are known to cause familial AD (FAD). Here, we analyze the ensembles of different isoforms (Aβ42 and Aβ40) and mutants (E22Δ, D23N, E22K, E22G, and A2T in Aβ40) of Aβ generated with all-atom replica exchange molecular dynamics (REMD) simulations on the μs/replica time scale. These were run using three different force field/water model combinations: OPLS-AA/L and TIP3P (“OPLS”), AMBER99sb-ILDN and TIP4P-Ew (“ILDN”), as well as CHARMM22* and TIP3SP (“CHARMM”). Despite fundamental changes in simulation parameters, we find that the resulting ensembles demonstrate a strong convergence in structural properties. In particular, antiparallel contacts between L17–A21 and A30–L34 are prevalent in ensembles of Aβ40, directly forming β sheets in the OPLS and ILDN combinations. A21–A30 commonly forms an interceding region that rarely interacts with the rest of the peptide. Further, Aβ42 contributes new β hairpin motifs involving V40–I41 in both OPLS and ILDN. However, the structural flexibility of the central region and the electrostatic interactions that characterize it are notably different between the different conditions. Further, for OPLS, each of the FAD mutations disrupts central bend character and increases the polymorphism of antiparallel contacts across the central region. However, the studied mutations in the ILDN set primarily encourage more global contacts involving the N-terminus and the central region, and promote the formation of new β topologies that may seed different aggregates involved in disease phenotypes. Furthermore, these differences aside, the large degree of agreement between simulation sets across multiple force fields provides a generalizable characterization of Aβ that is also consistent with experimental data and models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Characterization of the structural forces governing the reversibility of the thermal unfolding of the human acidic fibroblast growth factor

Human acidic fibroblast growth factor (hFGF1) is an all beta-sheet protein that is involved in the regulation of key cellular processes including cell proliferation and wound healing. hFGF1 is known to aggregate when subjected to thermal unfolding. In this study, we investigate the equilibrium unfolding of hFGF1 using a wide array of biophysical and biochemical techniques. Systematic analyses of the thermal and chemical denaturation data on hFGF1 variants (Q54P, K126N, R136E, K126N/R136E, Q54P/K126N, Q54P/R136E, and Q54P/K126N/R136E) indicate that nullification of charges in the heparin-binding pocket can significantly increase the stability of wtFGF1. Triple variant (Q54P/K126N/R136E) was found to be the most stable of all the hFGF1 variants studied. With the exception of triple variant, thermal unfolding of wtFGF1 and the other variants is irreversible. Thermally unfolded triple variant refolds completely to its biologically native conformation. Microsecond-level molecular dynamic simulations reveal that a network of hydrogen bonds and salt bridges linked to Q54P, K126N, and R136E mutations, are responsible for the high stability and reversibility of thermal unfolding of the triple variant. In our opinion, the findings of the study provide valuable clues for the rational design of a stable hFGF1 variant that exhibits potent wound healing properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Zero-deadtime processing in beta spectroscopy for measurement of the non-zero neutrino mass

The Project 8 collaboration seeks to measure, or more tightly bound, the mass of the electron antineutrino by applying a novel spectroscopy technique to precisely measure the tritium beta-decay spectrum. The current system produces a single analog signal, which is digitized and processed in several stages before being saved to local disk storage. Online processing includes two stages, an FPGA connected to the analog to digital converter reduces the data down to the region of interest before shipping over the local network for further processing and storage. A normal CPU-based processing stage applies triggering logic to only save data at times when a signal is present, further reducing the total volume of data which needs to be written to disk or transferred for long-term storage. The next stage of the project will need to process many input channels and will integrate a necessary aggregation and combination step prior to applying the event search and triggering logic. We present the online processing system which has successfully been deployed for the current, singlechannel, phase. We also present the status and design for a many-channel platform.

Project 8 Collaboration↗
DOE OSTI2024

Impact of Floating PV (FPV) System on Water Evaporation: Case Study of an Open Loop Reservoir in North Carolina

Fresh water scarcity is becoming one of the important concerns worldwide. This situation of water scarcity is further exacerbated by the increase in water evaporation due to climate change. This manuscript will address this concern by considering the impact of floating photovoltaics (FPVs) systems on water evaporation. The installation of PV modules on the water bodies can help reduce the water evaporation rate from reservoirs by reducing the evaporating area of the water surface. This work evaluates the effect of FPV on water evaporation rates in the TuckerTown reservoir located in North Carolina state of United States. Meteorological data, such as mean temperature and dew-point, are used to calculate the rate of the water evaporation by Linacre method. The simulation results for the TuckerTown case study showed that the aggregated avoided evaporated volume for one year is 9 million gallons.

14 SOLAR ENERGY↗
DOE OSTI2017

The strain-dependent spatial evolution of garnet in a high- P ductile shear zone from the Western Gneiss Region (Norway): a synchrotron X-ray microtomography study

Reaction and deformation microfabrics provide key information to understand the thermodynamic and kinetic controls of tectono-metamorphic processes, however they are usually analysed in two dimensions, omitting important information regarding the third spatial dimension. We applied synchrotron-based X-ray microtomography to document the evolution of a pristine olivine gabbro into a deformed omphacite-garnet eclogite in four dimensions, where the 4th dimension is represented by the degree of strain. In the investigated samples, which cover a strain gradient into a shear zone from the Western Gneiss Region (Norway), we focused on the spatial transformation of garnet coronas into elongated clusters of garnets with increasing strain. Our microtomographic data allowed quantification of garnet volume, shape and spatial arrangement evolution with increasing strain. We combined microtomographic observations with light microscope- and backscatter electron images as well as electron microprobe- (EMPA) and electron backscatter diffraction (EBSD) analysis to correlate mineral composition and orientation data with the X-ray absorption signal of the same mineral grains. With increasing deformation, the garnet volume almost triples. In the low strain domain, garnets form a well interconnected large garnet aggregate that develops throughout the entire Page 1 of 52 sample. We also observed that garnet coronas in the gabbros never completely encapsulate olivine grains. In the most highly deformed eclogites, the oblate shapes of garnet clusters reflect a deformational origin of the microfabrics. We interpret the aligned garnet aggregates to direct synkinematic fluid flow and consequently influence the transport of dissolved chemical components. EBSD analyses reveal that garnet show a near-random crystal preferred orientation that testifies no evidence for crystal plasticity. There is, however evidence for minor fracturing, neo-nucleation and overgrowth. Microprobe chemical analysis revealed that garnet compositions progressively equilibrate to eclogite facies, becoming more almandine-rich. We interpret these observations as pointing to a mechanical disintegration of the garnet coronas during strain localisation, and their rearrangement into individual garnet clusters through a combination of garnet coalescence and overgrowth while the rock was deforming.

garnet↗
DOE OSTI2025

CEC Quest: Long Duration Energy Storage Impact Analysis Tool

SAND2025-14389O CEC Quest is a Python tool with a user interface designed to analyze the greenhouse gas impacts of long-duration energy storage projects in California. The tool automates data collection from public sources and uses an Application Programming Interface (API) to enable users to download photovoltaic resource availability, marginal operating emissions rate, and utility rate data. It guides users in inputting parameters for a battery energy storage model and uploading site electrical load data, while also prompting for relevant analysis parameters like timestep and grid limits. CEC Quest performs monthly optimization of one year of data to assess impacts on the site’s electrical bill and the grid’s greenhouse gas emissions. Finally, it conducts a lifecycle analysis to evaluate changes over a defined quantification period, with results aggregated through automated report generation. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Rosewater, David [Sandia National Lab. (SNL-CA), L↗
DOE OSTI2024

Prospective Seal Name Catalog for U.S. Sedimentary Basins V1.0

The Prospective Seal Name Catalog for U.S. Sedimentary Basins V1.0 is an aggregation of prospective seal units for prospective storage resources within the USA for geologic carbon storage in both onshore and offshore basins. The catalog is intended to guide users to available literature and data resources. Prospective seal names are displayed with respect to the associated prospective storage resource target, for which the specified prospective seal may act as a confining layer for CO2 storage. A prospective seal unit’s lithology, position with respect to the reservoir (Primary, Secondary, Intraformational, etc.), and age (Geologic Period) are included when stated in the original literature or data resource. The information source for each record in the catalog includes the published citation, year of publication, resource type (Journal Article, Event Proceedings, etc.) and additional record notes.

Basin↗
DOE OSTI2021

Harnessing Condorcet Methods to Improve Decision-making Based on Ranked Data

Decision-makers must often choose between multiple alternatives based on their relative merits across a variety of criteria. These multiple-criteria decision-making (MCDM) problems must be approached in an objective, measurable, and transparent fashion to obtain well-supported outcomes. The challenge of using sets of ranked data to identify the optimal choice is not unlike the challenge of using ranked ballots to identify the winner of an election in a preference voting system. As such, the methods of rank aggregation used in elections can be applied to help resolve MCDM problems. Previous research into the design of elections and ballots has yielded many algorithms with well-understood properties. A subset of these, called Condorcet methods, reliably identify the “Condorcet winner,” if it exists, giving the result that would defeat any other in a pairwise comparison. That, in addition to several other desirable qualities, makes Condorcet methods like the Schulze method, Ranked Pairs, and Copeland’s method, effective and scalable means for tackling MCDM problems. These rank aggregation methods have been implemented in JavaScript functions for incorporation into a web-based MCDM decision tool. These algorithms can be applied in a wide variety of contexts (for example, determining the “best” environmental remediation method or selecting a subcontractor) to facilitate effective decision-making. The performance of the JavaScript Condorcet prototype tool was compared across the implemented algorithms and with both a non-Condorcet rank aggregation method as well as an implementation of the Simple Multi-Attribute Rating Technique (SMART) algorithm.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

ENDF/B-VIII.0 Testing With AMPX and SCALE

As the new ENDF/B-VIII.0 data has continued development from its initial beta release into the final release version, it has subsequently undergone processing and testing at Oak Ridge National Laboratory with AMPX and SCALE. Each of the beta releases has been processed with AMPX to create both multigroup (MG) and continuous-energy (CE) libraries. The MG libraries were all processed using the SCALE 252-group structure. These libraries were then used with the VALID suite for benchmarking the new data library’s performance against the currently distributed ENDF/B-VII.1 (VII.1)-based SCALE libraries. Here, we compare the MG and CE VALID results for the two current ENDF releases, versions VII.1 and the most recent beta release of ENDF/B-VIII.0 as of this writing (VIII.0.β4). Generally, both the MG and CE VALID aggregate results for VIII.0.β4 compare reasonably well with their VII.1-derived counterparts. As can be expected of any new ENDF release, some of the individual cases have substantially different computed neutron multiplicity (k eff ) values between the two releases, although typically the differences are less than 100 percent-milli (pcm). However, changes to the plutonium cross sections have induced much larger changes in the ratio of the computed k eff to the experimental value (C/E) for thermal spectrum plutonium solution critical systems. This paper details the comparative performance of the VII.1 and VIII.0.β4 data for the broad range of test cases covered by the VALID suite. A companion paper at this conference provides details of the baseline validation of SCALE 6.2, including the first release of the VII.1 data.

97 MATHEMATICS AND COMPUTING↗