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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 1,729 records · Page 96

Assessment of RELAP5-3D Code with Molten Salt Heat Transfer Experiments

The accurate thermal-hydraulic assessment of thermal storage systems is crucial for addressing the integrity and performance of the storage system design. This is particularly important for thermal storage systems using molten salts as a heat transport and storage medium, as the chemical corrosion and erosion by the high-temperature molten salts can cause serious damage to the structural components of the storage system. To understand these effects for TerraPower’s Natrium® Demonstration Reactor design, the system thermal-hydraulic analysis code, RELAP5-3D, is utilized to analyze the thermal storage system. This study evaluates two heat transfer correlations implemented in the RELAP5-3D code—the Dittus-Boelter and Gnielinski correlations—using selected benchmark cases from two molten salt heat transfer experiments conducted at Xi’an Jiao Tong University and the German Aerospace Center. The Nusselt numbers calculated using the Gnielinski correlation agree with the experimental data within ±5% of the relative deviations at 300°C and 400°C. With the increasing Reynolds numbers, the Dittus-Boelter correlation underestimates the Nusselt numbers by up to 22% compared to the Gnielinski correlation. Comparison of the RELAP5-3D calculation results with experimental data at a high temperature of 550°C revealed that the thermo-chemical characteristics of solar salt at high temperatures surpassing the decomposition temperatures of nitrate salts reduce the accuracy of heat transfer model of the RELAP5-3D code. Specifically, it has been observed that the temperatures of the wall surface and liquid near the wall can surpass the decomposition temperatures, even though the bulk temperature of molten salts remains significantly lower than these decomposition temperatures. In summary, this study recommends the use of the Gnielinski correlation for the heat transfer analysis of molten salt, rather than the Dittus-Boelter correlation.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Impact of graph structures for QAOA on MaxCut

The quantum approximate optimization algorithm (QAOA) is a promising method of solving combinatorial optimization problems using quantum computing. QAOA on the MaxCut problem has been studied extensively on graphs with specific structure; however, little is known about the general performance of the algorithm on arbitrary graphs. Here, we investigate how different graph characteristics correlate with QAOA performance at depths at most three on the MaxCut problem for all connected non-isomorphic graphs with at most eight vertices. Some good predictors of QAOA success relate to graph symmetries, odd cycles, and density. For example, on eight vertex graphs, the average probability for selecting an optimal solution for graphs that contain no odd cycles after three iterations of QAOA is 60.6% compared to 48.2% for those that do. The data generated from these studies are shared in a publicly accessible database to serve as a benchmark for QAOA calculations and experiments. Knowing the relationship between structure and performance can be used to identify classes of combinatorial problems that are likely to exhibit a quantum advantage.

97 MATHEMATICS AND COMPUTING↗

Stress-induced microcrack density evolution in β-eucryptite ceramics: Experimental observations and possible route to strain hardening

In order to investigate their microcracking behaviour, the microstructures of several β-eucryptite ceramics, obtained from glass precursor and cerammed to yield different grain sizes and microcrack densities, were characterized by laboratory and synchrotron x-ray refraction and tomography. Here, results were compared with those obtained from scanning electron microscopy (SEM). In SEM images, the characterized materials appeared fully dense but computed tomography showed the presence of pore clusters. Uniaxial tensile testing was performed on specimens while strain maps were recorded and analyzed by Digital Image Correlation (DIC). X-ray refraction techniques were applied on specimens before and after tensile testing to measure the amount of the internal specific surface (i.e., area per unit volume). X-ray refraction revealed that (a) the small grain size (SGS) material contained a large specific surface, originating from the grain boundaries and the interfaces of TiO 2 precipitates; (b) the medium (MGS) and large grain size (LGS) materials possessed higher amounts of specific surface compared to SGS material due to microcracks, which decreased after tensile loading; (c) the precursor glass had negligible internal surface. The unexpected decrease in the internal surface of MGS and LGS after tensile testing is explained by the presence of compressive regions in the DIC strain maps and further by theoretical arguments. It is suggested that while some microcracks merge via propagation, more close mechanically, thereby explaining the observed X-ray refraction results. Lastly, the mechanisms proposed would allow the development of a strain hardening route in ceramics.

36 MATERIALS SCIENCE↗

Harvest legacies and climate change interact to shape forest structure and biomass through time

Forest structural change driven by climate trends has been observed worldwide and is expected to increase in the future. Management of forest structure has been an important tool for mitigating the impacts of climate change but forest structure may shift independently of management goals as it interacts with climate change. Here, we investigated the long-term impacts of harvest-based management strategies on structure and resistance to climate-induced biomass loss using a process-based ecosystem model for a midwestern USA hardwood forest. We identified aboveground biomass loss events and compared the cumulative number of these events following a five-year period of active management under four management strategies and two climate change scenarios. Management legacy had the clearest impact on climate-driven biomass loss over the mid-term (∼25 years) with the shelterwood scenario experiencing no loss events during this period. However, by the end of the century legacy effects faded and climate change severity became the driver of differences as greater warming scenarios experienced twice the loss events, and end-of-century loss events were 3–10 times more frequent than mid-century events. We found that while structure was distinct among harvest scenarios through the mid-century, differences were negligible by the end-of-century; identical to when management correlated with loss event frequency. Here, we found that loss events were preceded by a drop in precipitation two years prior, while no specific forest structure preceded a loss event. However, the structures preceding a biomass loss event were distinct across different legacies, implying additional influences of past management.

54 ENVIRONMENTAL SCIENCES↗

Implications of point defect accumulation on UO 2 thermal conductivity and fission gas release under accelerated fuel irradiation

Evaluation of thermal properties is a crucial factor for nuclear fuel performance. During reactor operation, the accumulation of fission products and irradiation-induced lattice defects are responsible for degradation in thermal conductivity. Consequently, it affects fuel temperature and fission gas release (FGR) among other Multiphysics processes important for economics and safety analysis. We analyze the implications of point defects (PD) accumulation described using a rate theory (RT) Model on lattice thermal conductivity of UO 2 . Here, we demonstrate that fission rate-dependent point defect concentrations have the largest impact on in-pile thermal conductivity in the periphery of light water reactor fuels below a temperature threshold governed by the migration barrier of defects. Our analysis provides a mechanistic description of this phenomena which current fuel performance codes treat empirically. The reduction of thermal conductivity in the low -temperature rim region acts as additional thermal resistance and leads to a temperature notably larger than suggested by Lucuta thermal conductivity correlation. These effects are anticipated to have notable impacts when fuels are exposed to accelerated radiation. The impact of such point defect-informed treatment of thermal conductivity on fuel performance is evaluated by a detailed analysis of fission gas behavior and its release. We consider several models capturing different stages of fission gas bubble evolution and fission gas release (FGR). Finally, a new fission rate-dependent correction to the Lucuta correlation is proposed. The results show a significant reduction in thermal conductivity at the fuels’ periphery and an increase in fuel centerline temperature specifically at low burnups. Ultimately a modified LC shows a higher FGR compared to the original LC, while the acceleration process results in a reduction in overall FGR.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DYRK1A is required for maintenance of cancer stemness, contributing to tumorigenic potential in oral/oropharyngeal squamous cell carcinoma

Highlights: • DYRK1A is essential to maintain cancer stemness in OSCC. • DYRK1A regulates cancer stemness via FGF2 expression. • Levels of DYRK1A and FGF2 expression are positively correlated in OSCC cells. • DYRK1A-FGF2 is a novel molecular axis regulating cancer stemness in OSCC. DYRK1A, one of the dual-specificity tyrosine phosphorylation-regulated kinases (DYRKs), plays an important role in various biological processes by regulating downstream targets via kinase-dependent and independent mechanisms. Here, we report a novel role of DYRK1A in maintaining tumor growth and stemness of oral/oropharyngeal squamous cell carcinoma (OSCC) cells. Deletion of DYRK1A from OSCC cells abrogated their in vivo tumorigenicity and self-renewal capacity, the key features of cancer stem-like cells (CSCs; also referred to as tumor-initiating cells). The DYRK1A deletion also induced the suppression of CSC populations and properties, such as migration ability and chemoresistance. Conversely, ectopic expression of DYRK1A in OSCC cells augmented their CSC phenotype. Among five DYRK members (DYRK1A, 1B, 2, 3, and 4), DYRK1A is the most dominantly expressed kinase, and its expression is upregulated in OSCC compared to normal oral epithelial cells. More importantly, DYRK1A was highly enriched in various CSC-enriched OSCC populations compared to their corresponding non-CSC populations, indicating its pivotal role in cancer progression and stemness. Further, our study revealed that fibroblast growth factor 2 (FGF2) is a key regulator in the DYRK1A-mediated CSC regulation. Functional studies demonstrated that the loss of DYRK1A inhibits CSC phenotype via reduction of FGF2. Overexpression of DYRK1A promotes CSC phenotype via upregulation of FGF2. Our study delineates a novel mechanism of cancer stemness regulation by DYRK1A-FGF2 axis in OSCC. Thus, inhibition of DYRK1A would lead to a potential novel therapeutic option for targeting CSCs in OSCC.

60 APPLIED LIFE SCIENCES↗

Distribution of Copper States, Phases, and Defects across the Depth of a Cu-Doped CdTe Solar Cell

Copper has been used as a p-type dopant in cadmium telluride (CdTe) for decades. However, the density of Cu atoms in the finished device is much higher than that of holes, which means that most Cu atoms are not activated as acceptors during incorporation. Furthermore, studies have demonstrated that the distribution of copper (Cu) atoms across the device is highly inhomogeneous, with reports citing Cu substitution on Cd sites and segregation to grain boundaries. Fast diffusion along these boundaries and Cu accumulation at the CdTe/CdS interface have also been observed and validated computationally. These levels of inhomogeneity make it difficult to accurately characterize and correlate the performance with the nature of the Cu atomic species present. To address this challenge, we utilize X-ray microscopy and, specifically, nanoscale fluorescence-mode X-ray absorption near-edge structure to resolve the atomic Cu environment throughout the depth of the CdTe layer. Our results suggest that the majority of Cu atoms are in the form of Cu x Te phases (or similar local environments) near the ZnTe|CdTe interface, Cu x O phases in the CdTe absorber, and present in various oxidation states, including Cu 1+ and Cu 2+ , near the CdS/CdTe junction. Here this work also provides experimental evidence for the first time of the presence of CuS around the ZnTe|CdTe interface and the hypothesized Cu Cd -Cl i complex in the CdTe absorber.

14 SOLAR ENERGY↗

Fluorescence Color by Data-Driven Design of Genomic Silver Clusters

DNA nucleobase sequence controls the size of DNA-stabilized silver clusters, leading to their well-known yet little understood sequence-tuned colors. The enormous space of possible DNA sequences for templating clusters has challenged the understanding of how sequence selects cluster properties and has limited the design of applications that employ these clusters. Here, we investigate the genomic role of DNA sequence for fluorescent silver clusters using a data-driven approach. Employing rapid parallel silver cluster synthesis and fluorimetry, we determine the fluorescence spectra of silver cluster products stabilized by 1432 distinct DNA oligomers. By applying pattern recognition algorithms to this large experimental data set, we discover certain DNA base patterns, or “motifs,” that correlate to silver clusters with similar fluorescence spectra. These motifs are employed in machine learning classifiers to predictively design DNA template sequences for specific fluorescence color bands. Our method improves selectivity of templates by 330% for silver clusters with peak emission wavelengths beyond 660 nm. The discovered base motifs also provide physical insights into how DNA sequence controls silver cluster size and color. Finally, this predictive design approach for color of DNA-stabilized silver clusters exhibits the potential of machine learning and data mining to increase the precision and efficiency of nanomaterials design, even for a soft-matter-inorganic hybrid system characterized by an extremely large parameter space.

59 BASIC BIOLOGICAL SCIENCES↗

A Multi-Analysis Approach for Estimating Regional Health Impacts from the 2017 Northern California Wildfires

In the evening of October 8 and early hours of October 9, 2017, high winds in Northern California downed trees and power lines, igniting some of the most devastating wildfires the state had seen, and within hours unhealthy air quality impacted millions of people. We simulated these air quality conditions using fire detection information from the MODIS, VIIRS, and GOES-16 ABI satellite instruments, and applying a set of three WRF–CMAQ simulations, one data fusion, and three machine learning methods. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ air quality modeling system. Interestingly, this approach did not necessarily improve results compared to the baseline case, which used a default time profile. However, this approach was key to simulating the initial 12-hr explosive fire activity and smoke impacts. The WRF-CMAQ simulations compared well with observational data for the October 8-15 time period and tended to overestimate concentrations October 16-20. To improve these results, we applied three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across the WRF-CMAQ, data fusion, and machine learning datasets, the best Pearson correlation was 0.5. The data fusion and machine learning results were biased low and WRF-CMAQ results were biased high. Finally, we applied the optimized PM2.5 exposure estimate in a short-term exposure-response function. Total estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to wildland fire smoke.

O'Neill, Susan↗

Technical Note: Method to correlate whole-specimen histopathology of radical prostatectomy with diagnostic MR imaging

Purpose: Validation of MRI-guided tumor boundary delineation for targeted prostate cancer therapy is achieved via correlation with gold-standard histopathology of radical prostatectomy specimens. Challenges to accurate correlation include matching the pathology sectioning plane with the in vivo imaging slice plane and correction for the deformation that occurs between in vivo imaging and histology. A methodology is presented for matching of the histological sectioning angle and position to the in vivo imaging slices. Methods: Patients (n = 4) with biochemical failure following external beam radiotherapy underwent diagnostic MRI to confirm localized recurrence of prostate cancer, followed by salvage radical prostatectomy. High-resolution 3-D MRI of the ex vivo specimens was acquired to determine the pathology sectioning angle that best matched the in vivo imaging slice plane, using matching anatomical features and implanted fiducials. A novel sectioning device was developed to guide sectioning at the correct angle, and to assist the insertion of reference dye marks to aid in histopathology reconstruction. Results: The percentage difference in the positioning of the urethra in the ex vivo pathology sections compared to the positioning in in vivo images was reduced from 34% to 7% through slicing at the best match angle. Reference dye marks were generated, which were visible in ex vivo imaging, in the tissue sections before and after processing, and in histology sections. Conclusions: The method achieved an almost fivefold reduction in the slice-matching error and is readily implementable in combination with standard MRI technology. The technique will be employed to generate datasets for correlation of whole-specimen prostate histopathology with in vivo diagnostic MRI using 3-D deformable registration, allowing assessment of the sensitivity and specificity of MRI parameters for prostate cancer. Although developed specifically for prostate, the method is readily adaptable to other types of whole tissue specimen, such as mastectomy or liver resection.

61 RADIATION PROTECTION AND DOSIMETRY↗

PlasmidHostFinder: Prediction of Plasmid Hosts Using Random Forest

Plasmids play a major role facilitating the spread of antimicrobial resistance between bacteria. Understanding the host range and dissemination trajectories of plasmids is critical for surveillance and prevention of antimicrobial resistance. Identification of plasmid host ranges could be improved using automated pattern detection methods compared to homology-based methods due to the diversity and genetic plasticity of plasmids. In this study, we developed a method for predicting the host range of plasmids using machine learning—specifically, random forests. We trained the models with 8,519 plasmids from 359 different bacterial species per taxonomic level; the models achieved Matthews correlation coefficients of 0.662 and 0.867 at the species and order levels, respectively. Our results suggest that despite the diverse nature and genetic plasticity of plasmids, our random forest model can accurately distinguish between plasmid hosts. This tool is available online through the Center for Genomic Epidemiology (https://cge.cbs.dtu.dk/services/PlasmidHostFinder/).

59 BASIC BIOLOGICAL SCIENCES↗

Extra Large G-Protein Interactome Reveals Multiple Stress Response Function and Partner-Dependent XLG Subcellular Localization

The three-member family of Arabidopsis extra-large G proteins (XLG1-3) defines the prototype of an atypical Ga subunit in the heterotrimeric G protein complex. Some recent evidence indicate that XLG subunits operate along with its Gbg dimer in root morphology, stress responsiveness, and cytokinin induced development, however downstream targets of activated XLG proteins in the stress pathways are rarely known. In order to assemble a set of candidate XLG-targeted proteins, a yeast two-hybrid complementation-based screen was performed using XLG protein baits to query interactions between XLG and partner protein found in glucose-treated seedlings, roots, and Arabidopsis cells in culture. Seventy two interactors were identified and >60% of a test set displayed in vivo interaction with XLG proteins. Gene co-expression analysis shows that >70% of the interactors are positively correlated with the corresponding XLG partners. Gene Ontology enrichment for all the candidates indicates stress responses and posits a molecular mechanism involving a specific set of transcription factor partners to XLG. Genes encoding two of these transcription factors, SZF1 and 2, require XLG proteins for full NaCl-induced expression. Furthermore, the subcellular localization of the XLG proteins in the nucleus, endosome, and plasma membrane is dependent on the specific interacting partner.

59 BASIC BIOLOGICAL SCIENCES↗

Editorial: Plant-microbe omics

Omics-based studies have evolved over the past two decades to provide rich datasets from which deeper system-level understanding can be unraveled. Omics technologies (e.g., genomics, transcriptomics, proteomics, and metabolomics) can provide specific molecular insights into plant and microbe fitness, disease states, stress, cell signaling/cell-cell communication, and nutrient exchange, and these molecular observations can be correlated with system phenotype and function. The overall health of plant-microbe systems and their surrounding environments can be assessed, and a greater understanding of processes related to nutrient exchange/cycling, plant disease, and ecosystem homeostasis can now be achieved via the latest approaches to plant-microbe omics analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Advanced Geomechanical Model to Predict the Impact of CO2-Induced Microstructural Alterations on the Cohesive-Frictional Behavior of Mt. Simon Sandstone

We investigated the influence of CO2-induced geochemical reactions on the cohesive-frictional properties of host rock within the context of CO2 storage in a saline aquifer and focused on the Mt. Simon sandstone. The research objective was to model geo-mechanical changes due to host rock exposure to CO2-saturated brine while accounting for heterogeneity, double-scale porosity, and granular structure. We formulated a three-level multi-scale model for host rocks. We conducted scanning electron microscopy analyses to probe the microstructure and grid nanoindentation to measure the mechanical response. We derived new nonlinear strength upscaling solutions to correlate the effective strength characteristics and the macroscopic yield surface to the micro-structure at the nano-, micro-, and meso-scales. Specifically, our theoretical model links CO2-induced microstructural alterations to a reduction in the size of the yield surface, and a drop in the value of the friction coefficient. In turn, regarding the Illinois Basin Decatur Project, the CO2-induced drop in friction coefficient is linked to an increase in the risk of fault slip and a higher probability of induced microseismicity during and after the end of CO2 underground injection operations. The theoretical model presented is essential for the geo-mechanical modeling of CO2 underground injection operations at multiple length-scales.

58 GEOSCIENCES↗

Geology of Utah and Nevada by ERTS imagery

The author has identified the following significant results. Imagery for a portion of the study area was received, catalogued for in-house availability, and examined for relevant data. Topographic, geologic, aeromagnetic, and gravity maps were gathered to form a basis of comparison. Overlay drawings were prepared indicating significant features for further study and eventual field checking. The number of significant observations appears to be very great, and it is apparent that methods of handling the acquired information for easy access, for planning field checks, and for final presentation, must be improved. The tracing of lithologic variations and contacts is readily noted on many of the images. Some of the features vary from what is shown on geological maps but the correlation, or lack of same, is still to be studied in the field and by comparison of ground truth geological maps with the specific images. Numerous lineaments, based on tonal differences, are noted in the districts, some of which extend for tens of kilometers. Several positive and negative magnetic anomalies are noted with the suggestion that the sources of the mineralizing fluids were derived from hidden intrusives.

Jensen, M. L.↗

Quantitative observation of light flash sensations experiment MA-106

Light flashes caused by the interaction of cosmic particles with the visual apparatus have been observed by astronauts on all space missions since Apollo 11. This Apollo Soyuz Test Project experiment compared measurements of the observer's visual sensitivity with measurements of the ambient radiation environment and with the frequency and character of the flashes observed. The data obtained reveal a latitude dependence of the frequency of observed flashes. This distribution of flashes is correlated with the distribution of cosmic particles with stopping power greater than 15 keV/ micrometers in the eye. The interaction of dark adaptation, specific ionization, and range of particles in the retina as factors in the visualization of particle passage is discussed.

Budinger, T. F.↗

Correlation tracking study for meter-class solar telescope on space shuttle

The theory and expected performance level of correlation trackers used to control the pointing of a solar telescope in space using white light granulation as a target were studied. Three specific trackers were modeled and their performance levels predicted for telescopes of various apertures. The performance of the computer model trackers on computer enhanced granulation photographs was evaluated. Parametric equations for predicting tracker performance are presented.

Smithson, R. C.↗