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At least 1,423 records · Page 79

An Empirical Orthogonal Function-Based Algorithm for Estimating Terrestrial Latent Heat Flux from Eddy Covariance, Meteorological and Satellite Observations

Accurate estimation of latent heat flux (LE) based on remote sensing data is critical in characterizing terrestrial ecosystems and modeling land surface processes. Many LE products were released during the past few decades, but their quality might not meet the requirements in terms of data consistency and estimation accuracy. Merging multiple algorithms could be an effective way to improve the quality of existing LE products. In this paper, we present a data integration method based on modified empirical orthogonal function (EOF) analysis to integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) LE product (MOD16) and the Priestley-Taylor LE algorithm of Jet Propulsion Laboratory (PT-JPL) estimate. Twenty-two eddy covariance (EC) sites with LE observation were chosen to evaluate our algorithm, showing that the proposed EOF fusion method was capable of integrating the two satellite data sets with improved consistency and reduced uncertainties. Further efforts were needed to evaluate and improve the proposed algorithm at larger spatial scales and time periods, and over different land cover types.

54 ENVIRONMENTAL SCIENCES↗

Process optimization of caustic scrubber and iodine-129 immobilization in sodalite-based waste forms

Caustic scrubbers are proposed to remove vaporized iodine from nuclear fuel reprocessing plants. Resulting caustic slurries of radioactive iodine ( 129 I) and other anions can be captured and immobilized into the cage structures of sodalite-type minerals. Here, mixed anion sodalites were hydrothermally synthesized from a simulated caustic scrubber solution containing hydroxide/water, carbonate, chlorine, bromine, iodine, nitrate, and nitrite ions with added kaolinite. Experiments were conducted with twenty-five different sets of process conditions. Resulting powders were characterized by quantitative X-ray diffraction (XRD) and multi-functional thermal analysis, including gravimetry, calorimetry, and mass spectrometry. Using statistical analysis, process variables were tailored to maximize conversion of kaolinite into cage silicates, immobilize caustic scrubber anions, and minimize amorphous content. Further, chemical analysis showed the incorporation of all the targeted ions into the solids. Detailed investigation of a batch characterized after washing (creating secondary waste) and one without washing but subsequent calcination is given. This work contributes to defining the constraints required for subsequent consolidation process steps of the waste form to avoid volatilization.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Scoping Analysis of Source Term and Functional Containment Attenuation Factors

In order to meet future regulatory requirements, the Next Generation Nuclear Plant (NGNP) Project must fully establish and validate the mechanistic modular high temperature gas-cooled reactor (HTGR) source term. This is not possible at this stage in the project, as significant uncertainties in the final design remain unresolved. In the interim, however, there is a need to establish an approximate characterization of the source term. The NGNP team developed a simplified parametric model to establish mechanistic source term estimates for a set of proposed HTGR configurations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Scoping Analysis of Source Term and Functional Containment Attenuation Factors (Revision 1)

In order to meet future regulatory requirements, the Next Generation Nuclear Plant (NGNP) Project must fully establish and validate the mechanistic modular high temperature gas-cooled reactor (HTGR) source term. This is not possible at this stage in the project, as significant uncertainties in the final design remain unresolved. In the interim, however, there is a need to establish an approximate characterization of the source term. The NGNP team developed a simplified parametric model to establish mechanistic source term estimates for a set of proposed HTGR configurations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Analysis of PV Advanced Inverter Functions and Setpoints under Time Series Simulation.

Utilities are increasingly concerned about the potential negative impacts distributed PV may have on the operational integrity of their distribution feeders. Some have proposed novel methods for controlling a PV system's grid - tie inverter to mitigate poten tial PV - induced problems. This report investigates the effectiveness of several of these PV advanced inverter controls on improving distribution feeder operational metrics. The controls are simulated on a large PV system interconnected at several locations within two realistic distribution feeder models. Due to the time - domain nature of the advanced inverter controls, quasi - static time series simulations are performed under one week of representative variable irradiance and load data for each feeder. A para metric study is performed on each control type to determine how well certain measurable network metrics improve as a function of the control parameters. This methodology is used to determine appropriate advanced inverter settings for each location on the f eeder and overall for any interconnection location on the feeder.

14 SOLAR ENERGY↗

Uncertainty Quantification and Comparison of Weld Residual Stress Measurements and Predictions.

In pressurized water reactors, the prevention, detection, and repair of cracks within dissimilar metal welds is essential to ensure proper plant functionality and safety. Weld residual stresses, which are difficult to model and cannot be directly measured, contribute to the formation and growth of cracks due to primary water stress corrosion cracking. Additionally, the uncertainty in weld residual stress measurements and modeling predictions is not well understood, further complicating the prediction of crack evolution. The purpose of this document is to develop methodology to quantify the uncertainty associated with weld residual stress that can be applied to modeling predictions and experimental measurements. Ultimately, the results can be used to assess the current state of uncertainty and to build confidence in both modeling and experimental procedures. The methodology consists of statistically modeling the variation in the weld residual stress profiles using functional data analysis techniques. Uncertainty is quantified using statistical bounds (e.g. confidence and tolerance bounds) constructed with a semi-parametric bootstrap procedure. Such bounds describe the range in which quantities of interest, such as means, are expected to lie as evidenced by the data. The methodology is extended to provide direct comparisons between experimental measurements and modeling predictions by constructing statistical confidence bounds for the average difference between the two quantities. The statistical bounds on the average difference can be used to assess the level of agreement between measurements and predictions. The methodology is applied to experimental measurements of residual stress obtained using two strain relief measurement methods and predictions from seven finite element models developed by different organizations during a round robin study.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Subcontract Report: Diffusion Mechanisms and Bond Dynamics in Solid Electrolyte Ion-Conductors

We employ first-principles molecular dynamics simulations and Maximally Localized Wannier Function (MLWF) analysis to explore how halide substitution and nano-phase microstructures affect diffusivity, through the activation energy barrier - E a and D 0 , in the solid electrolyte Li 3 InBr 6-x Cl x . We find that nano-phase microstructures with x=3 (50-50 Br-Cl) mixed composition have a higher diffusivity compared to x=2 and x=3 solid solutions. There is a positive linear relationship between ln(D 0 .) and E a , which suggests that for superionic conductivity optimizing both the activation energy and the D 0 is important. Bond frustration due to mismatch in crystal geometry and ideal coordination number leads to especially high diffusivity through a high D 0 in the x=3 composition.

25 ENERGY STORAGE↗

Final Scientific/Technical Report

A variety of calcifying organisms produce a transient or metastable amorphous calcium carbonate (ACC) precursor phase that is assembled and subsequently transformed into a crystalline biomineral, typically calcite or aragonite. The complex shapes, hierarchical structures, and unique physical properties of the biominerals that result from this calcification pathway have stimulated interest in adapting these concepts for the design and creation of bio-inspired functional materials in the laboratory. ACC also forms as a reactive precursor in diverse inorganic systems and is likely to play a much broader role in calcium carbonate formation. Knowledge of the structure, composition, and behavior of this metastable phase is critical for establishing a structural and mechanistic framework for calcium carbonate formation and its role in biogeochemical processes, including carbon cycling. Minor additives, such as magnesium, phosphorus, and organic macromolecules, are known to play important roles in controlling ACC stability, transformation kinetics, and selection of final crystalline polymorph. Molecular water also occurs in many types of ACC and is thought to play a structural role in its stability and transformation behavior. One of the major challenges that remain unresolved is identification of the structural basis for the role of these minor additives and molecular water. The absence of long-range order in ACC, and other amorphous phases, has posed a challenge for study by techniques commonly used for crystalline solids. Preliminary studies in our group show that the combination of two techniques, synchrotron X-ray-based pair distribution function (PDF) analysis and nuclear magnetic resonance (NMR) spectroscopy can provide entirely new insight to structural properties of synthetic ACC over length scales that are most relevant for understanding its transformation properties. Building on preliminary experiments, we propose a systematic study of synthesis, structure, and transformation behavior in abiotic systems. The work will specifically address the influence of phosphate as a minor additive. PDF analysis will utilize total X-ray scattering data collected at synchrotron facilities optimized for this method and will provide direct characterization of the short- and intermediate-range structure of ACC synthesized under controlled conditions. Parallel computational work using reverse Monte Carlo methods will allow structural models to be constructed for a more complete analysis of PDF results. NMR spectroscopy, using a variety of single- and double-resonance techniques, will provide information on H and CO3 components, including dynamical properties, and their relationship to stabilizing additives. PDF and NMR results will be complemented by parallel studies using X-ray absorption and FT-IR spectroscopy to allow direct comparison to previous studies. These techniques will be used to follow the transformation of different ACC samples, with specific additives, to crystalline phases under controlled condition (e.g., relative humidity). This work will provide the structural and mechanistic basis for understanding ACC stability, its transformation behavior, and the factors that govern polymorph selection. This new insight will directly benefit researchers in diverse fields, as well as adding to the framework of knowledge for understanding and controlling calcium carbonate formation in natural and engineered systems.

58 GEOSCIENCES↗

Correlation of Injury Simulation with Clinical Assessment of Traumatic Brain Injury

This report contains a summary of our efforts to correlate head injury simulations predicting intracranial fluid cavitation with clinical assessments of brain injury from blunt impact to the head. Magnetic resonance imaging (MRI) data, collected on traumatic brain injury (TBI) subjects by researchers at the MIND Institute of New Mexico, was acquired for the current work. Specific blunt impact TBI case histories were selected from the TBI data for further study and possible correlation with simulation. Both group and single-subject case histories were examined. We found one single-subject case that was particularly suited for correlation with simulation. Diffusion tensor image (DTI) analysis of the TBI subject identified white matter regions within the brain displaying reductions in fractional anisotropy (FA), an indicator of local damage to the white matter axonal structures. Analysis of functional magnetic resonance image (fMRI) data collected on this individual identified localized regions of the brain displaying hypoactivity, another indicator of brain injury. We conducted high fidelity simulations of head impact experienced by the TBI subject using the Sandia head-neck-torso model and the shock physics computer code CTH. Intracranial fluid cavitation predictions were compared with maps of DTI fractional anisotropy and fMRI hypoactivity to assess whether a possible correlation exists. The ultimate goal of this work is to assess whether one can correlate simulation predictions of intracranial fluid cavitation with the brain injured sites identified by the fMRI and DTI analyses. The outcome of this effort is described in this report.

59 BASIC BIOLOGICAL SCIENCES↗

Efficient Generalizable Deep Learning

Stochastic optimization is a fundamental field of research for machine learning. Stochastic gradient descent (SGD) and related methods provide a feasible means to train complicated prediction models over large datasets. SGD, however, does not explicitly address the problem of overfitting, which can lead to predictions that perform poorly on new data. This difference between loss performance on unseen testing data verses that of training data defines the generalization gap of a model. We introduce a new computational kernel called Stochastic Hessian Projection (SHP) that uses a maximum likelihood framework to simultaneously estimate gradient noise covariance and local curvature of the loss function. Our analysis illustrates that these quantities affect the evolution of parameter uncertainty and therefore generalizability. We show how these computations allow us to predict the generalization gap without requiring holdout data. Explicitly assessing this metric for generalizability during training may improve machine learning predictions when data is scarce and understanding prediction variability is critical.

42 ENGINEERING↗

Correlation of Injury Simulation with Clinical Assessment of Traumatic Brain Injury

This report contains a summary of our efforts to correlate head injury simulations predicting intracranial fluid cavitation with clinical assessments of brain injury from blunt impact to the head. Magnetic resonance imaging (MRI) data, collected on traumatic brain injury (TBI) subjects by researchers at the MIND Institute of New Mexico, was acquired for the current work. Specific blunt impact TBI case histories were selected from the TBI data for further study and possible correlation with simulation. Both group and single-subject case histories were examined. We found one single-subject case that was particularly suited for correlation with simulation. Diffusion tensor image (DTI) analysis of the TBI subject identified white matter regions within the brain displaying reductions in fractional anisotropy (FA), an indicator of local damage to the white matter axonal structures. Analysis of functional magnetic resonance image (fMRI) data collected on this individual identified localized regions of the brain displaying hypoactivity, another indicator of brain injury. We conducted high fidelity simulations of head impact experienced by the TBI subject using the Sandia head-neck-torso model and the shock physics computer code CTH. Intracranial fluid cavitation predictions were compared with maps of DTI fractional anisotropy and fMRI hypoactivity to assess whether a possible correlation exists. The ultimate goal of this work is to assess whether one can correlate simulation predictions of intracranial fluid cavitation with the brain injured sites identified by the fMRI and DTI analyses. The outcome of this effort is described in this report.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Characterization of Multiple Trichloroethene, cis-Dichloroethene and 1,1-Dichloroethene Degrading Propanotrophic Communities

Aerobic cometabolism offers a viable strategy for the remediation of chlorinated solvent plumes at oxic sites where anaerobic approaches are limited. In this study, propane-enriched mixed cultures (derived from agricultural soils and an impacted site sediment) which previously degraded 1,4-dioxane, were evaluated for their capacity to also degrade trichloroethene (TCE), cis-1,2-dichloroethene (cDCE), and 1,1-dichloroethene (1,1-DCE) over successive transfers. Sustained biodegradation of TCE and cDCE was observed across multiple enrichments, and cultures enriched on one compound generally degraded the other. In contrast, 1,1-DCE biodegradation was restricted to a subset of cultures and removal times increased over transfers. Further, 1,1-DCE removal was absent at elevated concentrations, both trends consistent with inhibitory or toxic effects. Whole genome sequencing analyses revealed pronounced substrate-dependent selection of microbial communities, with cDCE-degrading cultures being dominated by Mycobacterium and Mycolicibacterium, whereas TCE-degrading cultures were dominated by Rhodococcus. Rhodococcus metagenome-assembled genomes (MAGs) in the TCE degrading cultures classified as R. opacus or R. wratislaviensis. 1,1-DCE degrading cultures were dominated by Pseudonocardia, although the associated MAGs contained a truncated propane monooxygenase alpha subunit. Functional gene analysis identified both group 5 (prmABCD) and putative group 6 propane monooxygenases. The following KBase narratives contain the quality controlled reads, MAGs (fasta assemblies) and the prokka annotations for each assembly TCE Site 1A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254918) TCE Soil 2A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254919) TCE Soil T3 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254920) TCE Soil T4 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254921) cDCE Site 1A 1B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254915) cDCE Soils T2 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254927) cDCE Soil T3 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254928) cDCE Soil 4A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254942) 1,1-DCE T2 T3 Propanotrophic MAGs (https://narrative.kbase.us/narrative/254903)

59 BASIC BIOLOGICAL SCIENCES↗

Impact of BBDuk metagenomic read trimming and decontamination

Background Investigators using metagenomic sequencing to study their microbiomes are often provided data that has been trimmed and decontaminated or do it themselves without knowing the effect these procedures can have on their downstream analyses. Here we evaluated the impact that JGI trimming and decontamination procedures had on assembly and binning metrics, placement of metagenome assembled genomes into species trees, and functional profiles of metagenome-assembled genomes (MAGs) extracted from twenty three complex rhizosphere metagenomes. We also investigated how more aggressive trimming impacts these binning metrics. Results We found that JGI trimmed and decontamination of input reads had some significant impacts in assembly and binning metrics compared to raw reads, and that differences in placement of MAGs in species trees increased with decreasing completeness and contamination thresholds. More aggressive trimming beyond those used by JGI were found to reduce MAG counts. Conclusions Mild trimming and decontamination of metagenomics reads prior to assembly can change an investigator’s answer to the questions, “Who is there and what are they doing? However, mild trimming and decontamination of metagenomic reads with high quality scores is recommended for those who elect to do so.

59 BASIC BIOLOGICAL SCIENCES↗

Lectin Receptor-Like Kinases: The Sensor and Mediator at the Plant Cell Surface

Lectin receptor-like kinases (LecRLKs), a plant-specific receptor-like kinase (RLK) sub-family, have been recently found to play crucial roles in plant development and responses to abiotic and biotic stresses. In this review, we first describe the classification and structures of Lectin RLKs. Then we focus on the analysis of functions of LecRLKs in various biological processes and discuss the status of LecRLKs from the ligands they recognize, substrate they target, signaling pathways they are involved in, to the overall regulation of growth-defense tradeoffs. LecRLKs and the signaling components they interact with constitute recognition and protection systems at the plant cell surface contributing to the detection of environmental changes monitoring plant fitness.

59 BASIC BIOLOGICAL SCIENCES↗

Morpho-physiological and transcriptomic responses of field pennycress to waterlogging

Field pennycress (Thlaspi arvense) is a new biofuel winter annual crop with extreme cold hardiness and a short life cycle, enabling off-season integration into corn and soybean rotations across the U.S. Midwest. Pennycress fields are susceptible to winter snow melt and spring rainfall, leading to waterlogged soils. The objective of this research was to determine the extent to which waterlogging during the reproductive stage affected gene expression, morphology, physiology, recovery, and yield between two pennycress lines (SP32-10 and MN106). In a controlled environment, total pod number, shoot/root dry weight, and total seed count/weight were significantly reduced in SP32-10 in response to waterlogging, whereas primary branch number, shoot dry weight, and single seed weight were significantly reduced in MN106. This indicated waterlogging had a greater negative impact on seed yield in SP32-10 than MN106. We compared the transcriptomic response of SP32-10 and MN106 to determine the gene expression patterns underlying these different responses to seven days of waterlogging. The number of differentially expressed genes (DEGs) between waterlogged and control roots were doubled in MN106 (3,424) compared to SP32-10 (1,767). Functional enrichment analysis of upregulated DEGs revealed Gene Ontology (GO) terms associated with hypoxia and decreased oxygen, with genes in these categories encoding proteins involved in alcoholic fermentation and glycolysis. Additionally, downregulated DEGs revealed GO terms associated with cell wall biogenesis and suberin biosynthesis, indicating suppressed growth and energy conservation. Interestingly, MN106 waterlogged roots exhibited significant stronger regulation of these genes than SP32-10, displaying a more robust transcriptomic response overall. Together, these results reveal the reconfiguration of cellular and metabolic processes in response to the severe energy crisis invoked by waterlogging in pennycress.

ERF-VII↗

Out-of-Plane Sulfur Distortions in the Bi4O4S3 Superconductor

The local atomic structure of the non-magnetic layered superconductor Bi4O4S3 was investigated using neutron diffraction and pair density function (PDF) analysis. Although on average, the crystal structure is well ordered, evidence for local, out–of–plane sulfur distortions is provided, which may act as a conduit for charge transfer from the SO4 blocks into the superconducting BiS2 planes. In contrast with LaO1−xFxBiS2, no sulfur distortions were detected in the planes, which indicates that charge density wave fluctuations are not supported in Bi4O4S3.

Philip, Sharon S. (ORCID:000000031055718X)↗