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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Magnetic field mapping of the UCNTau magneto-gravitational trap: design study

The beta decay lifetime of the free neutron is an important input to the Standard Model of particle physics, but values measured using different methods have exhibited substantial disagreement. The UCN r experiment in development at Los Alamos National Laboratory (LANL) plans to explore better methods of measuring the neutron lifetime using ultracold neutrons (UCNs). In this experiment, UCNs are confined in a magneto-gravitational trap formed by a curved, asymmetric Halbach array placed inside a vacuum vessel and surrounded by holding field coils. If any defects present in the Halbach array are sufficient to reduce the local field near the surface below that needed to repel the desired energy level UCNs, loss by material interaction can occur at a rate similar to the loss by beta decay. A map of the magnetic field near the surface of the array is necessary to identify any such defects, but the array's curved geometry and placement in a vacuum vessel make conventional field mapping methods difficult. A system consisting of computer vision-based tracking and a rover holding a Hall probe has been designed to map the field near the surface of the array, and construction of an initial prototype has begun at LANL. The design of the system and initial results will be described here.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Mapping the Energy-Water Nexus around the Pacific Rim

The energy-water nexus has been mapped for almost 12,000 watersheds distributed across the 21-economies comprising the Asia-Pacific Economic Cooperation. Water consumption for energy production was estimated for 9 different sectors including thermoelectric and hydroelectric power; energy extraction including coal, oil, natural gas, uranium and unconventional oil/gas; and, energy processing including oil and biofuels. Conversely, the energy consumed providing water services was mapped for three sectors, drinking water, waste water and seawater desalination. These measures of resource use were put in context by drawing comparison with published measures of water risk. The objective of the mapping was to quantify the energy-water nexus and its variability at the subnational level, pinpoint potential vulnerabilities, and identify opportunities for international collaboration.

13 HYDRO ENERGY↗
DOE OSTI2016

Deciphering Natural Allelic Variation in Switchgrass for Biomass Yield and Quality Using a Nested Association Mapping Population

Switchgrass (Panicum virgatum L.) is a C4 grass with high biomass yield potential and a model species for bioenergy feedstock development. Understanding the genetic basis of quantitative traits is essential to facilitate genome-enabled breeding programs. The nested association mapping (NAM) analysis combines the best features of both bi-parental and association analyses and can provide high power and high resolution in QTL detection and will ensure significant improvements in biomass yield and quality. To develop a NAM population of switchgrass, 15 highly diverse genotypes with specific characteristics were selected from a diversity panel and crossed to a recurrent parent, AP13, a genotype selected for whole genome sequencing and parent of a mapping population. Ten genotypes from each of the 15 F1 families were then chain crossed. Progenies form each family were randomly selected to develop the NAM population. The switchgrass NAM population consists of a total of 2000 genotypes from 15 families. All the progenies, founder parents, F1 parents (n=2350) were evaluated in replicated field trials at Ardmore, OK and Knoxville, TN. Phenotypic data on plant height, tillering ability, regrowth, flowering time, and biomass yield were collected. Dried biomass samples were also analyzed using prediction equations of NIRS at the Noble Foundation and for lignin content, S/G ratio, and sugar release characteristics at the NREL. Genomic shotgun sequencing of 15 switchgrass NAM founder parental genomes at JGI produced 28-66 Gb high-quality sequence data. Alignment of these sequences with the reference genome, AP13 (v3.0), revealed that up to 99% of the genomic sequences mapped to the reference genome. A total of 2,149 individuals from NAM populations were sequenced by exome capture and two sets of 15 SNP matrices (one for each family) were generated. QTL associated with important traits have been identified and verified in breeding populations. The QTL detected and their associated markers can be used in molecular breeding programs to facilitate development of improved switchgrass cultivars for biofuel production.

09 BIOMASS FUELS↗
DOE OSTI2017

GeoCF - Smart Power Maps - Final Technical Report

GeoCF has greatly enhanced the utility-scale solar siting platform, Smart Power Maps, through the help of the DOE Solar Energy Technologies Office. It is now available for the entire country and includes an improved user interface and additional layers such as topology, soils, comprehensive floodplains, parcels, imagery, wells, pipelines, and more. As well, users can now draw and save maps and perform drastically improved and more relevant hydrological, transmission, and financial analyzes. Smart Power Maps has played a pivotal role in supporting the development of otherwise unknown or hard to locate ideal locations for large solar farms in the United States.

14 SOLAR ENERGY↗
DOE OSTI2017

Application of photoluminescence imaging and laser-beam-induced-current mapping in thin film solar cell characterization

My research projects are focused on application of photonics, optics and micro- fabrication technology in energy related fields. Photonic crystal fabrication research has the potential to help us generate and use light more efficiently. In order to fabricate active 3D woodpile photonic structure devices, a woodpile template is needed to enable the crystal growth process. We developed a silica woodpile template fabrication process based on two polymer transfer molding technique. A silica woodpile template is demonstrated to work with temperature up to 900 C. It provides a more economical way to explore making better 3D active woodpile photonic devices like 3D photonic light emitting diodes (LED). Optical research on solar cell testing has the potential to make our energy generation more e cient and greener. PL imaging and LBIC mapping are used to measure CdTe solar cells with different back contacts. A strong correlation between PL image defects and LBIC map defects is observed. This opens up potential application for PL imaging in fast solar cell inspection. 2D laser IV scan shows its usage in 2D parameter mapping. We show its ability to generate important information about solar cell performance locally around PL image defects.

14 SOLAR ENERGY↗
DOE OSTI2017

Mapping of orthogonal 2D flux coordinates for two nearby magnetic X-points to logically rectangular domains

The behavior of plasmas in configurations with magnetic null points is of potential interest for a number of systems. Such nulls, sometimes referred to as X-points, a name strictly valid only for wellseparated nulls where magnetic separatrices cross at a right angle, may occur in only one component of the magnetic field, such as the poloidal field in a tokamak. Numerical simulations are often used to study and predict turbulence and transport in such systems. For cases with strong magnetic field such that the ion and electron gyro-frequencies are much larger that particle collision frequencies, there is a strong anisotropy in the plasma transport along the magnetic field compared to across the field. Because of the strong anisotropy, it is often advantageous for simulations to use a coordinate system based on magnetic flux surfaces together with a coordinate orthogonal to the flux surfaces. This report presents the topological considerations needed to construct the mapping on an orthogonal flux-surface mesh onto a logically rectangular domain often used in simulation codes of the divertor region of tokamaks having two nearby X-points, thus extending the mapping now common single-null or well-separated double nullpoint cases with one null located at the top and bottom of the device. This extension is especially relevant to study the capability of snowflake divertors in tokamaks for reducing the peak heat flux of exhaust plasma on the target plates [1-3]. The analysis presented here follows the analytic description of the poloidal magnetic field, B pol , near two closely-spaced X-points given by Ryutov [1-3]. This analysis is applicable to experimental devices where the two X-points are generated by distributed poloidal field coils and the plasma core current. This analytic description is used to identify topological features of an orthogonal mesh. A key parameter that specifies the various topology changes is the poloidal angle between the primary X-point and the second X-point, and the changes are associated with a set of critical angles. Understanding these changes leads to the final step in the mesh construction by identifying the locations of various regions or patches in configuration space and in a corresponding logically rectangular index space. UEDGE [4] and other 2-D fluid plasma simulation codes [5-7] describe the edge plasma of toroidally symmetric tokamak configurations with one or more X-points in a divertor region. The 2-D spatial mesh is usually based on a magnetic configuration produced by an MHD equilibrium code such as EFIT and written out as one or more “eqdsk” files. As illustrated in Fig. 1, the domain of the simulated plasma consists of several flux tubes bounded by poloidal magnetic flux surfaces. The number and spacing of the flux surfaces defines the “radial” resolution of the mesh. The “radial” direction is locally orthogonal to flux surfaces; the “poloidal” direction is locally parallel to flux surfaces. The “poloidal” resolution of the mesh is defined by the number of cells in the poloidal direction between adjacent flux surfaces. For boundary plasma transport codes used for tokamak configurations such as UEDGE it is convenient, though not necessary, to assume that all flux tubes have the same number of poloidal cells so the mesh is logically rectangular in index space, but does possess internal boundaries linking different sub-rectangles in the computational domain. The following sections of this report describe indexing schemes that map tokamak magnetic configurations with one or more x-points in the divertor region(s) onto a rectangular index space. Simulation results from the UEDGE code illustrate the schemes for a few configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Model Authorized Product Realization (MAP-R) Analysis

The Model Authorized Product Realization (MAP-R) project was a collaboration between Sandia National Laboratories (SNL) and Kansas City National Security Campus (KCNSC) to advance the Nuclear Security Enterprise's (NSE) ability to quantify the differences between the current drawing centric/drawing-based process and a part centric/model-based process. In short, MAP-R identified the key business benefits of the part centric model-based process using quantifiable data. MAP-R builds upon the past, but leverages current advances in technology, processes/standards, and the motivation of our current workforce to use a part-centric/model- based design and manufacturing method.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

The Integration and Mapping of an Open-Source National Well Resource to Inform Geologic Carbon Storage Site Selection and Risk Prevention: The CO2-Locate Database

Geologic carbon storage (GCS) offers a way to capture and permanently store CO₂ from fossil fuel operations in underground geologic structures, aiding in the transition to a carbon-neutral energy economy. However, CO₂ injection sites can experience gas leakage through existing wells that penetrate storage reservoirs, making knowledge of well locations and characteristics crucial for permitting, infrastructure reusability, and risk assessment in GCS. Currently, public wellbore data from state, federal, and tribal entities are inconsistent and fragmented, with gaps and redundancies. To address this, the National Energy Technology Laboratory (NETL) developed CO2-Locate, an open-source, geospatial database and online application. CO2-Locate integrates over 50 data sources from federal, state, and tribal entities, creating a standardized national well database. Funded by the Bipartisan Infrastructure Law, the database is publicly available through the Energy Data eXchange (EDX) and viewable via the CO2-Locate web mapping application. This tool allows users to query, filter, and visualize well data to support GCS planning, permitting, and risk assessments. This presentation covers the methods used to create CO2-Locate, including data acquisition, processing, attribute mapping, and integration, much of which is automated for future updates. The web mapping application and its role in GCS site selection will also be discussed.

Tetteh, Daniel A.↗
DOE OSTI2024

Community Microgrid Assistance Partnership (C-MAP) [Slides]

This informational webinar, held on Nov. 11, 2024, covered the structure, technical focus, and eligibility criteria for the first Request for Proposals (RFP) released by the Community Microgrid Assistance Partnership (C-MAP). Eligible communities are invited to propose a community-based microgrid development or improvement project for funding and/or technical assistance. C-MAP is a program led by the U.S. Department of Energy Office of Electricity with management and coordination by the National Renewable Energy Laboratory. C-MAP will bring together many of the organizations that are working to understand, improve, and implement advanced microgrid energy systems in underserved and Indigenous communities in remote areas, facilitating a new forum for engagement and collaboration. Wraparound services from regional organizations will support the participating communities in microgrid operations as it relates to advancing their energy goals.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Smart Meter Data: A Gateway for Reducing Solar Soft Costs with Model-Free Hosting Capacity Maps

Public-facing solar hosting capacity (HC) maps, which show the maximum amount of solar energy that can be installed at a location without adverse effects, have proven to be a key driver of solar soft cost reductions through a variety of pathways (e.g., streamlining interconnection, siting, and customer acquisition processes). However, current methods for generating HC maps require detailed grid models and time-consuming simulations that limit both their accuracy and scalability—today, only a handful out of almost 2,000 utilities provide these maps. This project developed and validated data-driven algorithms for calculating solar HC using data from AMI without the need of detailed grid models or simulations. The algorithms were validated on utility datasets and incorporated as an application into NRECA’s Open Modeling Framework (OMF.coop) for the over 260 coops and vendors throughout the US to use. The OMF is free and open-source for everyone.

14 SOLAR ENERGY↗
DOE OSTI2025

CESER: wildfire mapping

Multispectral satellite imagery has been demonstrated to accurately detect wildfires over a variety of land cover types at coarse- and medium-resolution (i.e., 1km to 30m), typically by detecting burned area after the fire has caused substantial damage. We developed an algorithm to map active fire (i.e., flame) in 2-meter resolution WorldView time-series imagery and monitor fire trajectory over time. Our results depict robust mapping across scenes collected from different fires over grassy and forested land cover, identifying fires as small as 4m 2 throughout the image. Operational deployment at scale may provide valuable near-real time maps of active fire for responders to leverage for timely, targeted mitigation efforts. This white paper describes the current capability specifications and indicates requirements for scaling.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Magnetic In-Vacuum Field Mapping System for the Muon g-2 Experiment

The Muon g-2 experiment at Fermilab will measure the anomalous magnetic moment of the muon, $a^{}_\mu$ with a precision of 140ppb, a four-fold improvement over the former BNL E821 result. If the current discrepancy of about 3.5$\sigma$ between the Standard Model value for $a^{}_\mu$ and the former experiments was real, then the new experiment would verify the deviation with >7$\sigma$ significance. The experiment uses muons with the magic momentum of 3.09GeV/c stored in a very homogeneous magnetic field of a 45m long storage ring. The determination of $a^{}_\mu$ requires the precise knowledge of both the muon spin precession, $\omega^{}_a$, and the magnetic field, $\omega^{}_p$, expressed in terms of the free-proton Larmor frequency. The field measurement uses the high precision tool of pulsed proton Nuclear Magnetic Resonance and requires cross-calibrating a set of probes: a very accurate NMR probe calibrates the 17 probes on the in-vacuum field mapping system (the so-called trolley). This trolley in turn is used to map the field over the full azimuth of the storage ring. The trolley measurement also provides the calibration of the 378 fixed probes around the ring that constantly monitor the field drift. The trolley is particularly important as it measures the relevant field that is seen by the stored muons and this article presents the details of this field mapping system. This work was supported in part by the US DOE, Fermilab and US DOE OHEP under contract No. KA2201020.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Completely Positive Map for Noisy Driven Quantum Systems Derived by Keldysh Expansion

Accurate modeling of decoherence errors in quantum processors is crucial for analyzing and improving gate fidelities. To increase the accuracy beyond that of the Lindblad dynamical map, several generalizations have been proposed, and the exploration of simpler and more systematic frameworks is still ongoing. In this paper, we introduce a decoherence model based on the Keldysh formalism. This formalism allows us to include non-periodic drives and correlated quantum noise in our model. In addition to its wide range of applications, our method is also numerically simple, and yields a CPTP map. These features allow us to integrate the Keldysh map with quantum-optimal-control techniques. We demonstrate that this strategy generates pulses that mitigate correlated quantum noise in qubit state-transfer and gate operations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Mapping the Spatial Distribution of Fibrillar Polymorphs in Human Brain Tissue

Alzheimer’s disease (AD) is a neurodegenerative disorder defined by the progressive formation and spread of fibrillar aggregates of Aβ peptide and tau protein. Polymorphic forms of these aggregates may contribute to disease in varying ways since different neuropathologies appear to be associated with different sets of fibrillar structures and follow distinct pathological trajectories that elicit characteristic clinical phenotypes. The molecular mechanisms underlying the spread of these aggregates in disease may include nucleation, replication, and migration all of which could vary with polymorphic form, stage of disease, and region of brain. Given the linkage between mechanisms of progression and distribution of polymorphs, mapping the distribution of fibrillar structures in situ has the potential to discriminate between mechanisms of progression. However, the means of carrying out this mapping are limited. Optical microscopy lacks the resolution to discriminate between polymorphs in situ, and higher resolution tools such as ssNMR and cryoEM require the isolation of fibrils from tissue, destroying relevant spatial information. Here, we demonstrate the use of scanning x-ray microdiffraction (XMD) to map the locations of fibrillar polymorphs of Aβ peptides and tau protein in histological thin sections of human brain tissue. Coordinated examination of serial sections by immunohistochemistry was used to aid in the interpretation of scattering patterns and to put the observations in a broader anatomical context. Scattering from lesions in tissue shown to be rich in Aβ fibrils by immunohistochemistry exhibited scattering patterns with a prototypical 4.7 Å cross-β peak, and overall intensity distribution that compared well with that predicted from high resolution structures. Scattering from lesions in tissue with extensive tau pathology also exhibited a 4.7 Å cross-β peak but with intensity distributions that were distinct from those seen in Aβ-rich regions. In summary, these observations demonstrate that XMD is a rich source of information on the distribution of fibrillar polymorphs in diseased human brain tissue. When used in coordination with neuropathological examination it has the potential to provide novel insights into the molecular mechanisms underlying disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Identification of a Fusarium ear rot resistance gene in maize by QTL mapping and RNA sequencing

Fusarium ear rot (FER) caused by Fusarium verticillioides is a prevalent maize disease. To comprehensively characterize the genetic basis of the natural variation in FER resistance, a recombinant inbred line (RIL) population was used to map quantitative trait loci (QTL) for FER resistance. A total of 17 QTL were identified by linkage mapping in eight environments. These QTL were located on six chromosomes and explained 3.88–15.62% of the total phenotypic variation. Moreover, qFER1.03 had the strongest effect and accounted for 4.98–15.62% of the phenotypic variation according to analyses of multiple environments involving best linear unbiased predictions. The chromosome segment substitution lines (CSSLs) derived from a cross between Qi319 (donor parent) and Ye478 (recurrent parent) were used to verify the contribution of qFER1.03 to FER resistance. The line CL171, which harbored an introgressed qFER1.03 , was significantly resistant to FER. Further fine mapping of qFER1.03 revealed that the resistance QTL was linked to insertion/deletion markers InDel 8 and InDel 2, with physical distances of 43.55 Mb and 43.76 Mb, respectively. Additionally, qFER1.03 differed from the previous resistance QTL on chromosome 1. There were three annotated genes in this region. On the basis of the RNA-seq data, which revealed the genes differentially expressed between the FER-resistant Qi319 and susceptible Ye478, GRMZM2G017792 (MPK3) was preliminarily identified as a candidate gene in the qFER1.03 region. The Pr-CMV-VIGS system was used to decrease the GRMZM2G017792 expression level in CL171 by 34–57%, which led to a significant decrease in FER resistance. Using RIL and CSSL populations combined with RNA-seq and Pr-CMV-VIGS, the candidate gene can be dissected effectively, which provided important gene resource for breeding FER-resistant varieties.

Xia, Yusheng↗
DOE OSTI2020

Spatial Mapping of Riverbed Grain-Size Distribution Using Machine Learning

Recent alluvial sediments in riverbeds play a significant role in controlling hydrologic exchange flows (HEFs) in river systems. The alluvial layer is usually associated with strong heterogeneity in physical properties (e.g., permeability and hydraulic conductivity), which affects local HEFs and therefore biogeochemical processes. The spatial distribution of these physical properties needs to be determined to inform the numerical models used to reveal the realistic hydro-biogeochemical behaviors. Such information can be obtained based on the intrinsic link between sediment grain-size distribution and hydraulic properties where sediment texture information is available. However, grain-size measurements are usually spatially sparse and do not have adequate coverage and resolution, particularly for a relatively large domain such as the Hanford Reach of the Columbia River. In this paper, we adopted machine learning (ML) approaches for categorizing and mapping the spatial distributions of riverbed substrate grain size and filling in missing areas of substrate data using the ML models along the reach. Such ML models for substrate size mapping were trained at 13,372 locations using measured substrate sizes along with observed and simulated attributes, including bathymetric attributes (e.g., elevation, slope, and aspect ratio) from LIDAR and bathymetric surveys, and hydrodynamic properties (e.g., water depth, velocity, shear stress, and their statistical moments). An ensemble bagging-based ML technique, Random Forest, was adopted to identify the most influential factors as predictors to develop the predictive models with over-fitting issues addressed. The models were evaluated with respect to each individual substrate size class and the lumped group, and then used to generate the final substrate size maps covering all the grid cells in the numerical modeling domain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Rapid Spaceborne Mapping of Wildfire Retardant Drops for Active Wildfire Management

Aerial application of fire retardant is a critical tool for managing wildland fire spread. Retardant applications are carefully planned to maximize fire line effectiveness, improve firefighter safety, protect high-value resources and assets, and limit environmental impact. However, topography, wind, visibility, and aircraft orientation can lead to differences between planned drop locations and the actual placement of the retardant. Information on the precise placement and areal extent of the dropped retardant can provide wildland fire managers with key information to (1) adaptively manage event resources, (2) assess the effectiveness of retardant slowing or stopping fire spread, (3) document location in relation to ecologically sensitive areas; and perform or validate cost-accounting for drop services. This study uses Sentinel-2 satellite data and commonly used machine learning classifiers to test an automated approach for detecting and mapping retardant application. We show that a multiclass model (retardant, burned, unburned, and cloud artifact classes) outperforms a single-class retardant model and that image differencing (post-application minus pre-application) outperforms single-image models. Compared to the random forest and support vector machine, the gradient boosting model performed the best with an overall accuracy of 0.88 and an F1 Score of 0.76 for fire retardant, though results were comparable for all three models. Our approach maps the full areal extent of the dropped retardant within minutes of image availability, rather than linear representations currently mapped by aerial GPS surveys. The development of this capability allows for the rapid assessment of retardant effectiveness and documentation of placement in relation to sensitive environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Direct AFM-based nanoscale mapping and tomography of open-circuit voltages for photovoltaics

The nanoscale optoelectronic properties of materials can be especially important for polycrystalline photovoltaics including many sensor and solar cell designs. For thin film solar cells such as CdTe, the open-circuit voltage and short-circuit current are especially critical performance indicators, often varying between and even within individual grains. A new method for directly mapping the open-circuit voltage leverages photo-conducting AFM, along with an additional proportional-integral-derivative feedback loop configured to maintain open-circuit conditions while scanning. Alternating with short-circuit current mapping efficiently provides complementary insight into the highly microstructurally sensitive local and ensemble photovoltaic performance. Furthermore, direct open-circuit voltage mapping is compatible with tomographic AFM, which additionally leverages gradual nanoscale milling by the AFM probe essentially for serial sectioning. The two-dimensional and three-dimensional results for CdTe solar cells during in situ illumination reveal local to mesoscale contributions to PV performance based on the order of magnitude variations in photovoltaic properties with distinct grains, at grain boundaries, and for sub-granular planar defects.

77 NANOSCIENCE AND NANOTECHNOLOGY↗