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At least 523 records · Page 29

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NASA NTRS2016

Meteoritic Amino Acids: Diversity in Compositions Reflects Parent Body Histories

The analysis of amino acids in meteorites dates back over 50 years; however, it is only in recent years that research has expanded beyond investigations of a narrow set of meteorite groups (exemplied by the Murchison meteorite) into meteorites of other types and classes. These new studies have shown a wide diversity in the abundance and distribution of amino acids across carbonaceous chondrite groups, highlighting the role of parent body processes and composition in the creation, preservation, or alteration of amino acids. Although most chiral amino acids are racemic in meteorites, the enantiomeric distribution of some amino acids, particularly of the nonprotein amino acid isovaline, has also been shown to vary both within certain meteorites and across carbonaceous meteorite groups. Large -enantiomeric excesses of some extraterrestrial protein amino acids (up to 60) have also been observed in rare cases and point to nonbiological enantiomeric enrichment processes prior to the emergence of life. In this Outlook, we review these recent meteoritic analyses, focusing on variations in abundance, structural distributions, and enantiomeric distributions of amino acids and discussing possible explanations for these observations and the potential for future work.

carbonaceous chondrite groups↗

DOE OSTI2023

PhytoOracle: Scalable, modular phenomics data processing pipelines

As phenomics data volume and dimensionality increase due to advancements in sensor technology, there is an urgent need to develop and implement scalable data processing pipelines. Current phenomics data processing pipelines lack modularity, extensibility, and processing distribution across sensor modalities and phenotyping platforms. To address these challenges, we developed PhytoOracle (PO), a suite of modular, scalable pipelines for processing large volumes of field phenomics RGB, thermal, PSII chlorophyll fluorescence 2D images, and 3D point clouds. PhytoOracle aims to ( i ) improve data processing efficiency; ( ii ) provide an extensible, reproducible computing framework; and ( iii ) enable data fusion of multi-modal phenomics data. PhytoOracle integrates open-source distributed computing frameworks for parallel processing on high-performance computing, cloud, and local computing environments. Each pipeline component is available as a standalone container, providing transferability, extensibility, and reproducibility. The PO pipeline extracts and associates individual plant traits across sensor modalities and collection time points, representing a unique multi-system approach to addressing the genotype-phenotype gap. To date, PO supports lettuce and sorghum phenotypic trait extraction, with a goal of widening the range of supported species in the future. At the maximum number of cores tested in this study (1,024 cores), PO processing times were: 235 minutes for 9,270 RGB images (140.7 GB), 235 minutes for 9,270 thermal images (5.4 GB), and 13 minutes for 39,678 PSII images (86.2 GB). These processing times represent end-to-end processing, from raw data to fully processed numerical phenotypic trait data. Repeatability values of 0.39-0.95 (bounding area), 0.81-0.95 (axis-aligned bounding volume), 0.79-0.94 (oriented bounding volume), 0.83-0.95 (plant height), and 0.81-0.95 (number of points) were observed in Field Scanalyzer data. We also show the ability of PO to process drone data with a repeatability of 0.55-0.95 (bounding area).

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

AbBERT: Learning Antibody Humanness via Masked Language Modeling

Understanding the degree of humanness of antibody sequences is critical to the therapeutic antibody development process to reduce the risk of failure modes like immunogenicity or poor manufacturability. We introduce AbBERT, a transformer-based language model trained on up to 20 million unpaired heavy/light chain sequences from the Observed Antibody Space database. We first validate AbBERT using a novel “multi-mask” scoring procedure to demonstrate high accuracy in predicting complementary determining regions—including the challenging hypervariable H3 region. We then demonstrate several uses of AbBERT at various points along the antibody design process. AbBERT enhances in silico antibody optimization via deep reinforcement learning by utilizing its learned embeddings as additional observations during optimization. Within a larger computational antibody design platform, AbBERT has been successfully applied as an additional design objective, where it displays strong correlations with computational tools predicting antibody structural stability. Finally, mutant antibody sequences that have been scored as unfavorable by AbBERT have shown corresponding low yields when expressed in cells. These use cases demonstrate the power of language modeling within computational antibody design.

Bioinformatics↗

NASA NTRS1989

Method of controlling a resin curing process

An analytical technique for controlling the curing process of fiber-reinforced composite materials that are formed using thermosetting resins. The technique is the percent gel method and involves development of a time-to-gel equation as s function of temperature. From this equation a rate-of-gel equation is then determined, and a percent gel is calculated which is the product of the rate-of-gel times time. Percent gel accounting is used to control the proper pressure application point in an autoclave cure process to achieve desired properties in a production composite part.

Charles Neal Webster↗

NASA NTRS1992

Enhancing control of grid distribution in algebraic grid generation

Three techniques are presented to enhance the control of grid-point distribution for a class of algebraic grid generation methods known as the two-, four- and six-boundary methods. First, multidimensional stretching functions are presented, and a technique is devised to construct them based on the desired distribution of grid points along certain boundaries. Second, a normalization procedure is proposed which allows more effective control over orthogonality of grid lines at boundaries and curvature of grid lines near boundaries. And third, interpolating functions based on tension splines are introduced to control curvature of grid lines in the interior of the spatial domain. In addition to these three techniques, consistency conditions are derived which must be satisfied by all user-specified data employed in the grid generation process to control grid-point distribution. The usefulness of the techniques developed in this study was demonstrated by using them in conjunction with the two- and four-boundary methods to generate several grid systems, including a three-dimensional grid system in the coolant passage of a radial turbine blade with serpentine channels and pin fins.

Steinthorsson, E.↗

DOE OSTI2023

Analysis of position-dependent cavity parameters in irradiated metals to obtain insight on fundamental defect migration phenomena

Motion of point defects is a fundamental process that governs microstructure and properties of materials. Here, we examine the near-surface and grain boundary cavity swelling depth profiles in neutron- and ion-irradiated simple metals (Cu, Ni, and Fe-Cr) and investigate diffusional broadening of implanted Ni ions in Fe-Cr alloys. Vacancy migration energies and radiation-enhanced diffusion were experimentally estimated. Cavity denuded zone widths near planar sinks are shown to be dependent on temperature, damage rate, balance of point defects and sinks, and vacancy migration energies. An enhanced cavity swelling zone adjacent to the void-denuded zone was observed in specimens with low to moderate sink strength and interpreted as evidence of 1D gliding interstitial clusters. Radiation-enhanced diffusional broadening of implanted Ni ions (at 400–550 °C) in Fe and Fe-Cr was up to 250 nm toward the surface, which leads to a much broader near-peak-damage region where cavity swelling is suppressed. Diffusional broadening of implanted ions is calculated to be similarly pronounced for self-ion irradiations, particularly near the peak and higher swelling temperature regimes. Adequately high ion energies (~8–15 MeV) are recommended for ion-irradiation studies to provide a sufficiently broad midrange safe analysis region with minimized surface and injected ion effects.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A Novel Dew Point Meter: Application to the Measurement of the Sulfuric Acid Dew Point for Combustion Flue Gas

Accurate knowledge of acid dew point is essential for industrial and applied combustion. Sulfur in the fuel or raw materials is converted to sulfur dioxide (SO2) during combustion, and a portion of the SO2 is oxidized to sulfur trioxide (SO3). The SO3 will react to form H2SO4 vapor when in the presence of water vapor. Even with just trace levels of H2SO4 vapor in the gas phase (1-10 ppm), the dew point can reach 100°C and higher. To avoid acid condensation and the resulting corrosion on heat recovery equipment, plant engineers must ensure that surface temperatures are above the acid dew point, but this decreases the efficiency of the thermal energy recovery. Thus, there is a trade-off between minimizing equipment corrosion and maximizing thermal energy recovery efficiency, and the acid dew point is a key parameter for this optimization. In this work, we analyze and discuss the theory of the sulfuric acid condensation process and develop a novel dew point meter based on this analysis. The meter consists of a novel optical instrument that is designed to monitor the slightest appearance of condensation on a hydrophobic window surface, and the surface temperature of the window is slowly decreased until condensation is first observed, yielding an accurate measurement of the dew point. The basis of the instrument is that a collimated beam from a diode laser generates scattered light when encountering surface condensate, and a sophisticated array detector is used to sensitively monitor the light scattering. The measurement procedures are established to rapidly find the acid dew point, while minimizing error. Further, we propose a calibration system based on a liquid bubbler, which can generate a stable gas flow with known sulfuric acid dew point, to test the dew point meter. Test results show that the dew point meter can accurately measure the acid dew point over a wide range.

Cheng, Mao↗

NASA NTRS1994

JPL-ANTOPT antenna structure optimization program

New antenna path-length error and pointing-error structure optimization codes were recently added to the MSC/NASTRAN structural analysis computer program. Path-length and pointing errors are important measured of structure-related antenna performance. The path-length and pointing errors are treated as scalar displacements for statics loading cases. These scalar displacements can be subject to constraint during the optimization process. Path-length and pointing-error calculations supplement the other optimization and sensitivity capabilities of NASTRAN. The analysis and design functions were implemented as 'DMAP ALTERs' to the Design Optimization (SOL 200) Solution Sequence of MSC-NASTRAN, Version 67.5.

Strain, D. M.↗

DOE OSTI2021

Transcription initiation as a control point in plastid gene expression

The extensive processing and protein-assisted stabilization of transcripts have been taken as evidence for a viewpoint that the control of gene expression had shifted entirely in evolution from transcriptional in the bacterial endosymbiont to posttranscriptional in the plastid. This suggestion is however at odds with many observations on plastid gene transcription. Chloroplasts of flowering plants and mosses contain two or more RNA polymerases with distinct promoter preference and division of labor for the coordinated synthesis of plastid RNAs. Plant and algal plastids further possess multiple nonredundant sigma factors that function as transcription initiation factors. The controlled accumulation of plastid sigma factors and modification of their activity by sigma-binding proteins and phosphorylation constitute additional transcriptional regulatory strategies. Plant and algal plastids also contain dedicated one- or two-component transcriptional regulators. Finally, transcription initiation thus continues to form a critical control point at which varied developmental and environmental signals intersect with plastid gene expression.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1974

Engineering studies related to the GEOS-C radar altimeter

Experiment requirements, technical characteristics, and GEOS-C radar altimeter related analyses are discussed along with results of a study on engineering test data requirements. Statistical analyses related to determination of wave height resolution achievable as a function of system characteristics and averaging period are described, in addition to a discussion on the desirability of using computer procedures to compensate for altitude tracker time-jitter. Data processing considerations for the GEOS-C system are examined. An extensive analysis of the spatial filter effect is given and results of a computation of geoidal power spectral density, based on Skylab altimeter data, is displayed and interpreted in terms of projected GEOS-C random errors. This information is then used in deriving minimum-mean-square filter procedures for both geoid undulation and slope data. The characteristics of mean received waveforms as a function of off-nadir angle are used to obtain tracker bias as a function of sea state and pointing angle. The angle estimation process proposed by the GEOS-C hardware contractor is also investigated from a standpoint of achievable angular resolution.

Miller, L. S.↗

DOE OSTI2021

MIGHTEE: total intensity radio continuum imaging and the COSMOS/XMM-LSS Early Science fields

ABSTRACT MIGHTEE is a galaxy evolution survey using simultaneous radio continuum, spectropolarimetry, and spectral line observations from the South African MeerKAT telescope. When complete, the survey will image ∼20 deg2 over the COSMOS, E-CDFS, ELAIS-S1, and XMM-Newton Large Scale Structure field (XMM-LSS) extragalactic deep fields with a central frequency of 1284 MHz. These were selected based on the extensive multiwavelength data sets from numerous existing and forthcoming observational campaigns. Here, we describe and validate the data processing strategy for the total intensity continuum aspect of MIGHTEE, using a single deep pointing in COSMOS (1.6 deg2) and a three-pointing mosaic in XMM-LSS (3.5 deg2). The processing includes the correction of direction-dependent effects, and results in thermal noise levels below 2 $\mathrm{\mu }$Jy beam−1 in both fields, limited in the central regions by classical confusion at ∼8 arcsec angular resolution, and meeting the survey specifications. We also produce images at ∼5 arcsec resolution that are ∼3 times shallower. The resulting image products form the basis of the Early Science continuum data release for MIGHTEE. From these images we extract catalogues containing 9896 and 20 274 radio components in COSMOS and XMM-LSS, respectively. We also process a close-packed mosaic of 14 additional pointings in COSMOS and use these in conjunction with the Early Science pointing to investigate methods for primary beam correction of broad-band radio images, an analysis that is of relevance to all full-band MeerKAT continuum observations, and wide-field interferometric imaging in general. A public release of the MIGHTEE Early Science continuum data products accompanies this article.

Heywood, I. (ORCID:0000000168645057)↗

DOE OSTI2025

Slicing Solutions for Wire Arc Additive Manufacturing

Both commercial and research applications of wire arc additive manufacturing (WAAM) have seen considerable growth in the additive manufacturing of metallic components. However, there remains a clear lack of a unified paradigm for toolpath generation when slicing parts for WAAM deposition. Existing toolpath generation options typically lack the appropriate features to account for all complexities of the WAAM process. This manuscript explores the key slicing challenges specific to toolpaths for WAAM geometry and pairs each consideration with multiple solutions to mitigate most negative effects on completed components. These challenges must be addressed to minimize voids, prevent bead collapse, and ensure deposited components accurately approximate the desired geometry. Slicing considerations are grouped into four general categories: geometric, process, thermal, and productivity. Geometric considerations are addressed with overhang compensation, corner-sharpening, and toolpath-smoothing features. Process considerations are addressed with start point configuration and controls for the bead lengths and end points. Thermal and productivity considerations are addressed with island optimization, multi-material printing, and connected insets. Finally, tools for the post-processing of generated G-code are explored. Overall, these solutions represent a critical set of slicing features used to improve generated toolpaths and the quality of the components deposited with those toolpaths.

36 MATERIALS SCIENCE↗

NASA NTRS1977

Apollo-Soyuz pamphlet no. 8: Zero-g technology

The behavior of liquids in zero gravity environments is discussed with emphasis on foams, wetting, and wicks. A multipurpose electric furnace (MA-010) for the high temperature processing of metals and salts in zero-g is described. Experiments discussed include: monolectic and synthetic alloys (MA-041); multiple material melting point (MA-150); zero-g processing of metals (MA-070); surface tension induced convection (MA-041); halide eutectic growth; interface markings in crystals (MA-060); crystal growth from the vapor phase (MA-085); and photography of crystal growth (MA-028).

Page, L. W.↗

NASA NTRS1984

Thematic Mapper geometric correction processing

The Thematic Mapper Image Processing System is described from the point of view of geometric correction. The system performance requirements are discussed, and the Landsat-D flight segment is described. The ground processing and overall geometric system performance is addressed. Those aspects of the Thematic Mapper Image Processing System that differ significantly from those of the MSS System are emphasized.

Beyer, E. P.↗

DOE OSTI2025

Fabrication and Evaluation of Large Alumina Crucibles by Vat Photopolymerization Additive Manufacturing for High-Temperature Actinide Chemistry

Additive manufacturing (AM) offers opportunities to advance the design and function of ceramic tooling in high temperature actinide pyrochemistry. In technical ceramics such as alumina, conventional forming techniques often restrict design flexibility and can limit experimental progress. In this study, we investigate the use of vat photopolymerization (VP) with commercial resins to fabricate large-scale alumina crucibles, reaching dimensions up to 125 mm, which is significantly larger than typically reported for dense VP ceramics. Notably, these additively manufactured components are produced using consumer-grade hardware, which limits process control, but offers significant upside in scalability and accessibility. Using microscopy and X-ray computed tomography, the VP alumina parts have high bulk densities above 95%, but also the prevalence of AM-induced artifacts and surface defects. Mechanical testing showed these defects to significantly reduce flexural strength and compromise part reliability. Electrorefining trials under sustained exposure to molten salts and metals reveal mixed results, with the AM material exhibiting high chemical compatibility, but mechanical failures due to the reduced strength were prevalent. Our findings illustrate both the promise and current limitations of AM ceramics for actinide chemistry, and point toward future improvements in process optimization, design strategies, and part screening to enhance performance and reliability.

Materials science↗

DOE OSTI2022

Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps

Abstract An accurate characterization of the water content of snowpack, or snow water equivalent (SWE), is necessary to quantify water availability and constrain hydrologic and land surface models. Recently, airborne observations (e.g., lidar) have emerged as a promising method to accurately quantify SWE at high resolutions (scales of ∼100 m and finer). However, the frequency of these observations is very low, typically once or twice per season in the Rocky Mountains of Colorado. Here, we present a machine learning framework that is based on random forests to model temporally sparse lidar-derived SWE, enabling estimation of SWE at unmapped time points. We approximated the physical processes governing snow accumulation and melt as well as snow characteristics by obtaining 15 different variables from gridded estimates of precipitation, temperature, surface reflectance, elevation, and canopy. Results showed that, in the Rocky Mountains of Colorado, our framework is capable of modeling SWE with a higher accuracy when compared with estimates generated by the Snow Data Assimilation System (SNODAS). The mean value of the coefficient of determination R 2 using our approach was 0.57, and the root-mean-square error (RMSE) was 13 cm, which was a significant improvement over SNODAS (mean R 2 = 0.13; RMSE = 20 cm). We explored the relative importance of the input variables and observed that, at the spatial resolution of 800 m, meteorological variables are more important drivers of predictive accuracy than surface variables that characterize the properties of snow on the ground. This research provides a framework to expand the applicability of lidar-derived SWE to unmapped time points. Significance Statement Snowpack is the main source of freshwater for close to 2 billion people globally and needs to be estimated accurately. Mountainous snowpack is highly variable and is challenging to quantify. Recently, lidar technology has been employed to observe snow in great detail, but it is costly and can only be used sparingly. To counter that, we use machine learning to estimate snowpack when lidar data are not available. We approximate the processes that govern snowpack by incorporating meteorological and satellite data. We found that variables associated with precipitation and temperature have more predictive power than variables that characterize snowpack properties. Our work helps to improve snowpack estimation, which is critical for sustainable management of water resources.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Advances in Resin Management Using 3R-Scan - 20154

The most important factor underlying optimal waste management is developing a clear picture of the radioactivity content of the waste and its impact on waste disposal cost. For over 35 years since the publishing of 10CFR61, waste characterization has relied on sampling the final waste product after formation. In the days following 10CFR61, the cost of final disposal was marginal with only a small impact on the overall costs. Constraints were added by provisions of the Low Level Waste Policy Act of 1985 leading to increasingly limited access to those disposal sites that remained available. In addition, Nuclear Regulatory Commission (NRC) pressure promoting waste volume reduction led to disposal costs inevitably rising. Despite this, characterization practices in monitoring of waste generation for activity content still center on the same dated processes. This results in a disposal classification on the basis of endpoint sampling without consideration of the homogeneity of the waste mixture. It can also disregard consideration of the representativeness of the single or small sample base. As a minimum effort, a formalized sampling program of a fixed grouping of waste streams can be implemented that could account for more than 95% of all of the activity carried in solid waste products. The sample results for each radionuclide could then be trended as time passes to develop reasonable scaling factors for difficult to measure radionuclides. This process, identified in NRC guidance, has been rigorously followed by a relatively small number of facilities. The trended scaling factors serve to improve accuracy by identifying anomalous results that could otherwise go undetected. Direct monitoring of the accumulation of activity in process streams generating solid radwaste, including demineralizers and filter streams, is a more precise approach. Nearly all of these streams are monitored by plant chemistry on a regular schedule to maintain water quality. This paper discusses viable options for developing the basis for characterization through process monitoring of the accumulation of activity at the point of generation. Special focus is on resin bed tracking and how process knowledge of these streams can be brought together to form a consistent and precise solid waste radioactivity inventory. Some of the specific points covered in this paper include the merger of the fission product release computer program, 3R-STAT, with the radwaste sample analysis computer program, SCAN4 to create 3R-SCAN, the importance of individual waste stream influences on the overall source term, and the use of historic sample data to develop scaling factors using an automated process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1995

Solar wind: Internal parameters driven by external source

A new concept interpreting solar wind parameters is suggested. The process of increasing twofold of a moving volume in the solar wind (with energy transfer across its surface which is comparable with its whole internal energy) is a more rapid process than the relaxation for the pressure. Thus, the solar wind is unique from the point of view of thermodynamics of irreversible processes. The presumptive source of the solar wind creation - the induction electric field of the solar origin - has very low entropy. The state of interplanetary plasma must be very far from the thermodynamic equilibrium. Plasma internal energy is contained mainly in non-degenerate forms (plasma waves, resonant plasma oscillations, electric currents). Microscopic oscillating electric fields in the solar wind plasma should be about 1 V/m. It allows one to describe the solar wind by simple dissipative MHD equations with small effective mean free path (required for hydrodynamical description), low value of electrical conductivity combined with very big apparent thermal conductivity (required for observed solar wind acceleration). These internal parameters are interrelated only due to their origin: they are externally driven. Their relation can change during the interaction of solar wind plasma with an obstacle (planet, spacecraft). The concept proposed can be verified by the special electric field measurements, not ruining the primordial plasma state.

Chertkov, A. D.↗