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At least 991 records · Page 55

Effects of Defects Analysis and Sizing Framework for Efficient Design of Composite Structures

Design of large composite structures requires striking a balance between permitted flaw size,strength margins, weight, and production rate. Stringent requirements manufacturing flaws can result in a lightweight structure because the strength properties are assumed to be closer to pristine. However, these stringent requirements can lead to production delays due to increased inspection and rework needed during the layup and rejection of parts after cure. Conversely, permitting larger flaws can reduce production delays, but will likely result in a heavier structure due to increased conservatism needed to maintain acceptable structural margins. The tradeoff between these criteria can vary between different structures and material systems, so the balance between manufacturing and design requirements is always a moving target. Assessment of this tradeoff requires having the ability to quickly evaluate the impact of flaw size on strength margin across an entire structure for a large number of load cases. The approach taken in this work is to implement an effects of defects analysis and sizing framework within HyperX. HyperX performs optimization of composite structures; this capability has been enhanced to include structural flaw data in the margin of safety calculations performed during optimization. Both the flaw import process and analysis of flaws have been generalized such that any flaw type from any source can be considered. The resulting tool enables rapid assessment of the impact of defects both at a vehicle and part level.

Effects of defects↗

On the uncertainties in helium generation predictions for fission and fusion alloys

With ongoing advances in fusion and advanced fission reactors, quantifying irradiation effects in materials is critical. Transmutation-induced helium in cladding and structural materials can drive swelling and embrittlement, thereby reducing these components’ lifespans. Yet most studies ignore the considerable uncertainties in predicting helium generation rates. In this work, we created a code wrapper, F-SCATTER, that automatically performs simulations in FISPACT-II. We used this tool to investigate potential variance in helium generation rate, or He/dpa, calculations based on deviations in alloy composition, irradiating neutron flux spectrum, computational methodology, and nuclear data sources. We used 12 wt% Cr HT9 steel as the reference case and observed a 6.5%–98.3% He/dpa spread based on compositional variation within a single chemical specification, a 1.8%–11.5% He/dpa variation upon the incorporation of a 15% artificial uncertainty in flux at each energy, and a He/dpa difference as high as 231% when using ENDF/B-VIII.0 versus TENDL-2021 data libraries. Similar results were found for other prominent iron-based alloys, including Grade 91, castable nano-structured alloy, and 316H—where additional variations exist based on reactor type (e.g. thermal, fast, or fusion) and alloying elements such as carbon, nitrogen, and nickel. Based on the simulated results, we conclude that a significant part of the heat-to-heat variability in swelling responses of Fe-based alloys can be driven by impurity content in alloy compositions, and, therefore, chemical control should be a key element in supply chain design for advanced nuclear energy systems. Furthermore, we provide critical recommendations on best practices for evaluating and reporting helium production and lattice damage rates when computing predictions with multiphysics programs such as FISPACT-II.

FISPACT-II↗

Mars brine formation experiment

The presence of water-soluble cations and anions in the Martian regolith has been the subject of speculation for some time. Viking lander data provided evidence for salt-cemented crusts on the Martian surface. If the crusts observed at the two Viking landing sites are, in fact, cemented by salts, and these crusts are globally widespread, as IRTM-derived thermal inertia studies of the Martian surface seem to suggest, then evaporite deposits, probably at least in part derived from brines, are a major component of the Martian regolith. The composition of liquid brines in the subsurface, which not only may be major agents of physical weathering but may also presently constitute a major deep subsurface liquid reservoir, is currently unconstrained by experimental work. A knowledge of the chemical identity and rate of production of Martian brines is a critical first-order step toward understanding the nature of both these fluids and their precipitated evaporites. Laboratory experiments are being conducted to determine the identity and production rate of water-soluble ions that form in initially pure liquid water in contact with Mars-mixture gases and unaltered Mars-analog minerals.

Moore, Jeffrey M.↗

Mechanisms and functions of membrane lipid remodeling in plants

Lipid remodeling, defined herein as post-synthetic structural modifications of membrane lipids, play crucial roles in regulating the physicochemical properties of cellular membranes and hence their many functions. Processes affected by lipid remodeling include lipid metabolism, membrane repair, cellular homeostasis, fatty acid trafficking, cellular signaling and stress tolerance. Glycerolipids are the major structural components of cellular membranes and their composition can be adjusted by modifying their head groups, their acyl chain lengths and the number and position of double bonds. This focused review summarizes recent advances in our understanding of mechanisms of membrane lipid remodeling with emphasis on the lipases and acyltransferases involved in the modification of phosphatidylcholine and monogalactosyldiacylglycerol, the major membrane lipids of extraplastidic and photosynthetic membranes, respectively. We also discuss the role of triacylglycerol metabolism in membrane acyl chain remodeling. Finally, we discuss emerging data concerning the functional roles of glycerolipid remodeling in plant stress responses. Illustrating the molecular basis of lipid remodeling may lead to novel strategies for crop improvement and other biotechnological applications such as bioenergy production.

59 BASIC BIOLOGICAL SCIENCES↗

Data for Rapid and High-Throughput Determination of Sorghum ( Sorghum bicolor ) Biomass Composition using Near Infrared Spectroscopy and Chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum ( Sorghum bicolor ) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

Biomass Analytics↗

Quaoar: New, Longitudinaly Resolved, Spectroscopic Characterization of Its Surface

(50000) Quaoar, one of the largest Trans-neptunian objects, is comparable in size to Pluto's moon Charon. However, while Charon's surface is rich almost exclusively in H2O ice, Quaoar's surface characterized by ices of CH4, N2, as well as C2H6, a product of irradiation of CH4 (Dalle Ore et al. 2009). Because of its distance from the Sun, Quaoar is expected to have preserved, to a degree, its original composition, however, its relatively small size did not make it a prime candidate for presence of volatile ices in the study by Schaller and Brown (2007). Furthermore, based on the Brown et al. (2011) study (Brown, Schaller, & Fraser, 2011. A Hypothesis for the Color Diversity of the Kuiper Belt. ApJL, 739, L60) its red coloration points to CH3OH as the ice which, when irradiated, might have produced the red material. We present new visible to near-infrared (0.3-2.48 micrometers) spectro-photometric data obtained with the XSHOOTER (Vernet et al. 2011, A&A, 536A, 105 ) instrument at the VLT-ESO facility at four different longitudes on the surface of Quaoar. The data are complemented by previously published photometric observations obtained in the near-infrared (3.6, 4.5 micrometers) with the Spitzer Space Telescope, which provide an extra set of constraints in the model calculation process in spite of the different observing times that preclude establishing the spatial consistency between the two sets. For each of the four spectra we perform spectral modeling of the entire wavelength range -from 0.3 to 4.5 micrometers- by means of a code based on the Shkuratov radiative transfer formulation of the slab model. We obtain spatially resolved compositional information for the surface of Quaoar supporting the presence of CH4 and C2H6, as previously reported, along with evidence for N2 and NH3OH. The albedo at the two Spitzer bands indicates the likely presence of CO and CO2. CH3OH, predicted on the basis of Quaoar's coloration (Brown et al. 2011), is not found at any of the four longitudes, implying that the presence of this ice is a sufficient, but not necessary condition for reddening of TNO surfaces. Other ices, in particular CH4 (Brunetto et al. 2006), have been shown to be plausible precursors for reddening of TNO surfaces.

Ices↗

High Volume Fraction Carbon Nanotube Composites for Aerospace Applications

Reported nanoscale mechanical properties of carbon nanotubes (CNTs) suggest that their use may enable the fabrication of significantly lighter structures for use in space applications. To be useful in the fabrication of large structures, however, their attractive nanoscale properties must be retained as they are scaled up to bulk materials and converted into practically useful forms. Advances in CNT production have significantly increased the quantities available for use in manufacturing processes, but challenges remain with the retention of nanoscale properties in larger assemblies of CNTs. This work summarizes recent progress in producing carbon nanotube composites with tensile properties approaching those of carbon fiber reinforced polymer composites. These advances were achieved in nanocomposites with CNT content of ~70% by weight. The processing methods explored to yield these CNT composite properties will be discussed, as will the characterization and test methods that were developed to provide insight into the factors that contribute to the enhanced tensile properties. Technology maturation was guided by parallel advancements in computational modeling tools that aided in the interpretation of experimental data.

Siochi, Emilie J.↗

Assessing the Behavior of Typically Lithophile Elements Under Highly Reducing Conditions Relevant to the Planet Mercury

With the data returned from the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission, there are now numerous constraints on the physical and chemical properties of Mercury, including its surface composition. The high Sand low FeO contents observed from MESSENGER suggest a low oxygen fugacity of the present materials on the planet's surface. Most of our understanding of elemental partitioning behavior comes from observations made on terrestrial rocks, but Mercury's oxygen fugacity is far outside the conditions of those samples, estimated at approximately 3-7 log units below the Iron-Wtistite (lW) oxygen buffer, several orders of magnitude more reducing than other terrestrial bodies we have data from. With limited oxygen available, lithophile elements may instead exhibit chalcophile, halophile, or siderophile behaviors. Furthermore, very few natural samples of rocks that formed under reducing conditions (e.g., enstatite chondrites, achondrites, aubrites) are available in our collections for examination of this change in geochemical affinity. Our goal is to determine the elemental partitioning behavior of typically lithophile elements at lower oxygen fugacity as a function of temperature and pressure. Experiments were conducted at I GPa in a 13 mm QUICKpress piston cylinder and at 4 GPa in an 880-ton multianvil press, at temperatures up to 1850degC. The composition of starting materials for the experiments were designed so the final run products contained metal, silicate melt, and sulfide melt phases. Oxygen fugacity was controlled in the experiments by adding silicon metal to the samples, in order to utilize the Si-Si02 buffer, which is approximately 5 log units more reducing than the IW buffer at our temperatures of interest. The target silicate melt composition was diopside (CaMgSi206) because measured surface compositions indicate partial melting of a pyroxene-rich mantle. The results of our experiments will aid in our understanding of the fate of elements during the differentiation and thermal evolution of Mercury and other highly reducing planetary bodies.

Rowland, Rick, II↗

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗

Electron microscopy characterization of the fuel-cladding interaction in medium burnup annular fast reactor MOX

In this work, we present electron microscopy data focused on the fuel-cladding interaction layer in annular fast reactor MOX with HT-9 cladding at medium burnup. In agreement with previous literature data, the volatile fission products Cs, Te and I have migrated radially into the extreme fuel periphery and partially interacted with the cladding. The accumulation of Cs has occurred in the outermost rim of the fuel pellet, where grain recrystallization has also been observed. Significant amounts of Pd have been found in the interaction zone, particularly in the sample taken from the upper half of the fissile column where the cladding temperatures are higher. At this axial location, Cr has been enriched at the cladding inner surface and diffused into the fuel. Furthermore, chromium remains mainly in metallic form, but locally formed oxides. The fission products Cs, Te and I are found, with variable composition, in form of nanocrystalline regions dispersed in the metallic Cr-rich layer. The morphology and chemical characteristics of the layer suggest a non-oxidative corrosion mechanism as principal cladding degradation phenomenon occurring in this sample, with local onset of Cr oxidation within the nanocrystalline precipitates.

36 MATERIALS SCIENCE↗

An infrared spectral database for gas-phase quantitation of volatile per- and polyfluoroalkyl substances (PFAS)

We report the construction of a database of vetted infrared spectra specifically targeting volatile fluorocarbon gases that may be emitted during thermal treatment of per- and polyfluoroalkyl substances (PFAS) to assist understanding of treatment processes and improve quantification. To populate this database, protocols derived from the Pacific Northwest National Laboratory (PNNL) infrared spectral database are used, curtailing the species selection for this data set. Each spectrum in the database is a weighted average derived from 10 or more individual measurements at different partial pressures (static method) or flow rates (dissemination method) to yield good fidelity of both strong and weak infrared signatures, with each composite spectrum ranging from = 6500 cm-1 to = 600 cm-1 with an apodized resolution of 0.112 cm-1. This resolution was chosen to fully resolve all spectral features, recognizing that atmospheric pressure broadening results in nearly all ro-vibrational lines having linewidths = 0.1 cm-1. As an example case, application of the database is demonstrated via identification and quantification of dominant 1H-perfluoroheptane and perfluorohept-1-ene fluorocarbon products resulting from thermal decomposition of perfluorooctanoate (PFOA) below 450 °C.

Infrared, Gas-phase spectra, FTIR, Spectral databa↗

Nodal Capacity Expansion Modeling with ReEDS: A Case Study of the RTS-GMLC Test System

Test systems play an important role in power systems analysis and are used extensively for a wide range of purposes like reliability analysis, production cost modeling, studying the impacts of load shifting, and many more. These test systems have continued to evolve over the years to keep pace with changing system compositions due to technology and policy changes. In this work, we apply the Regional Energy Deployment System (ReEDS) model, a large-scale capacity expansion model (CEM), on the nodal RTS-GMLC system to perform capacity expansion of the bus-level test system. This work both demonstrates that a large-scale CEM can successfully be applied to nodal systems, and that the CEM can allow a test system to be evolved to meet desired criteria. The process allowed the coupling of CEM data not available in the test system (such as capital costs) with test system data to provide plausible system evolutions in line with scenario specifications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

SERDP PFAS 2.0 - An infrared spectral database for gas-phase quantitation of volatile per- and polyfluoroalkyl substances (PFAS)

We report the construction of a database of vetted infrared spectra specifically targeting volatile fluorocarbon gases that may be emitted during thermal treatment of per- and polyfluoroalkyl substances (PFAS) to assist understanding of treatment processes and improve quantification. To populate this database, protocols derived from the Pacific Northwest National Laboratory (PNNL) infrared spectral database are used, curtailing the species selection for this data set. Each spectrum in the database is a weighted average derived from 10 or more individual measurements at different partial pressures (static method) or flow rates (dissemination method) to yield good fidelity of both strong and weak infrared signatures, with each composite spectrum ranging from = 6500 cm-1 to = 600 cm-1 with an apodized resolution of 0.112 cm-1. This resolution was chosen to fully resolve all spectral features, recognizing that atmospheric pressure broadening results in nearly all ro-vibrational lines having linewidths = 0.1 cm-1. As an example case, application of the database is demonstrated via identification and quantification of dominant 1H-perfluoroheptane and perfluorohept-1-ene fluorocarbon products resulting from thermal decomposition of perfluorooctanoate (PFOA) below 450 °C.

Infrared, Gas-phase spectra, FTIR, Spectral databa↗

Robust Multilayer Insulation for Cryogenic Systems

New requirements for thermal insulation include robust Multilayer insulation (MU) systems that work for a range of environments from high vacuum to no vacuum. Improved MLI systems must be simple to install and maintain while meeting the life-cycle cost and thermal performance objectives. Performance of actual MLI systems has been previously shown to be much worse than ideal MLI. Spacecraft that must contain cryogens for both lunar service (high vacuum) and ground launch operations (no vacuum) are planned. Future cryogenic spacecraft for the soft vacuum environment of Mars are also envisioned. Industry products using robust MLI can benefit from improved cost-efficiency and system safety. Novel materials have been developed to operate as excellent thermal insulators at vacuum levels that are much less stringent than the absolute high vacuum requirement of current MLI systems. One such robust system, Layered Composite Insulation (LCI), has been developed by the Cryogenics Test Laboratory at NASA Kennedy Space Center. The experimental testing and development of LCI is the focus of this paper. LCI thermal performance under cryogenic conditions is shown to be six times better than MLI at soft vacuum and similar to MLI at high vacuum. The experimental apparent thermal conductivity (k-value) and heat flux data for LCI systems are compared with other MLI systems.

Fesmire, J. E.↗

Airborne High Spectral Resolution Lidar Measurements of Aerosol Distributions and Properties During the NASA CAMP2Ex Mission

The NASA Clouds, Aerosols and Monsoon Processes-Philippines Experiment (CAMP2Ex) occurred during August-October, 2019,primarily over the ocean near the Philippines, including the ocean west of Luzon. CAMP2Ex attempts to characterize the role of anthropogenic and natural aerosol particles in modulating warm and mixed-phase precipitation in the maritime continent during the Southwest Monsoon. This mission is also examining relationships between spatial heterogeneity in the aerosol and cloud fields and radiative heating rates and studying the effects of aerosol concentration and composition on the microphysical properties of shallow cumulus and cumulus congestus clouds. Critical to the successful investigation of these objectives is profiling of aerosol, cloud and meteorological properties throughout the atmospheric column. For the CAMP2Ex experiment, we deployed the second generation NASA Langley airborne High Spectral Resolution Lidar (HSRL-2) on the NASA P-3 aircraft to obtain profile measurements of aerosol and thin cloud extinction and optical thickness via the HSRL technique at 355 and 532 nm, and of backscatter and depolarization at 355, 532, and 1064 nm. The HSRL technique allows for the independent measurement of extinction and backscatter without the need to assume modeled lidar ratios. Additional HSRL-2 data products include aerosol type, mixed layer depth, and range-resolved aerosol microphysical parameters. The HSRL measurements reveal the temporal, spatial, and vertical variability of aerosol optical properties over these locations. The HSRL-2 measured these backscatter, extinction, and depolarization profiles during all nineteen science flights and the transit flights to and from the aircraft operations base at Clark International Airport.In this presentation, we use these HSRL-2 measurements to show the horizontal and vertical distributions of aerosols in the CAMP2Ex operational area as well as provide insight into the optical and physical characteristics of these aerosols. We also discuss how these aerosols are distributed within and above the mixed layer.

aerosol↗

The SPARC-Reanalysis Intercomparison Project: Summary of Phase 1 and Plans for Phase 2 (S-RIP2): Chemical Reanalyses & Air Quality, Tropospheric Circulation, Extreme Events, and More

Reanalysis datasets are widely used to understand numerous atmospheric processes. Different reanalyses may give very different results for the same diagnostics. The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP, https://s-rip.github.io/) is a coordinated activity to compare key diagnostics among available reanalyses, identify differences among reanalyses and their underlying causes, provide guidance on appropriate usage of reanalyses in scientific studies, and contribute to future improvements in the reanalysis products via collaborations with reanalysis centers and data users. S-RIP Phase 1 (completed in early 2022) focused primarily on the upper troposphere through the middle atmosphere and processes linking these regions to the troposphere and surface. We look forward to broadening our efforts in Phase 2 (S-RIP2), with new foci including studies of tropospheric circulation, extreme weather events, and their links to the stratosphere, and focusing on evaluation of chemical reanalyses, both those with a stratosphere / upper troposphere focus and those that focus on air quality applications. This presentation will provide a summary of Phase 1 results and discussion of future directions for S-RIP2, emphasizing applications to composition and chemistry studies as well as fostering capacity building for Early Career Scientists.

Jonathan S Wright↗

Broadening Systematic Reanalysis lntercomparisons in the SPARC-Reanalysis lntercomparison Project Phase 2 (S-RIP2): Chemical Reanalyses & Air Quality, Tropospheric Circulation, Extreme Events, and More

Reanalysis datasets are widely used to understand numerous atmospheric processes. Different reanalyses may give very different results for the same diagnostics. The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP, https://s-rip.github.io/) is a coordinated activity to compare key diagnostics among available reanalyses, identify differences among reanalyses and their underlying causes, provide guidance on appropriate usage of reanalyses in scientific studies, and contribute to future improvements in the reanalysis products via collaborations with reanalysis centers and data users. S-RIP Phase 1 (completed in early 2022) focused primarily on the upper troposphere through the middle atmosphere and processes linking these regions to the troposphere and surface. We look forward to broadening our efforts in Phase 2 (S-RIP2), with new foci including studies of tropospheric circulation, extreme weather events, and their links to the stratosphere, and focusing on evaluation of chemical reanalyses, both those with a stratosphere / upper troposphere focus and those that focus on air quality applications. This presentation will provide a summary of Phase 1 results and discussion of future directions for S-RIP2, emphasizing applications to composition and chemistry studies as well as fostering capacity building for Early Career Scientists.

Sean M Davis↗

Broadening Systematic Reanalysis Intercomparisons in the SPARC-Reanalysis Intercomparison Project Phase 2 (S-RIP2): Chemical Reanalyses & Air Quality, Tropospheric Circulation, Extreme Events, and More

Reanalysis datasets are widely used to understand numerous atmospheric processes. Different reanalyses may give very different results for the same diagnostics. The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP, https://s-rip.github.io/) is a coordinated activity to compare key diagnostics among available reanalyses, identify differences among reanalyses and their underlying causes, provide guidance on appropriate usage of reanalyses in scientific studies, and contribute to future improvements in the reanalysis products via collaborations with reanalysis centers and data users. S-RIP Phase 1 (completed in early 2022) focused primarily on the upper troposphere through the middle atmosphere and processes linking these regions to the troposphere and surface. We look forward to broadening our efforts in Phase 2 (S-RIP2), with new foci including studies of tropospheric circulation, extreme weather events, and their links to the stratosphere, and focusing on evaluation of chemical reanalyses, both those with a stratosphere / upper troposphere focus and those that focus on air quality applications. This presentation will provide a summary of Phase 1 results and discussion of future directions for S-RIP2, emphasizing applications to composition and chemistry studies as well as fostering capacity building for Early Career Scientists.

Sean M Davis↗