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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

First-principles calculations of thermal, electrical, and thermoelectric transport properties of semiconductors

The transport properties of semiconductors are key to the performance of many solid-state devices (transistors, data storage, thermoelectric cooling and power generation devices, etc). An understanding of the transport details can lead to material designs with better performances. In recent years simulation tools based on first-principles calculations have been greatly improved, being able to obtain the fundamental ground-state properties of materials (such as band structure and phonon dispersion) accurately. Accordingly, methods have been developed to calculate the transport properties based on an ab initio approach. We focus on the thermal, electrical, and thermoelectric transport properties of semiconductors, which represent the basic transport characteristics of the two degrees of freedom in solids—electronic and lattice degrees of freedom. Starting from the coupled electron-phonon Boltzmann transport equations, we illustrate different scattering mechanisms that change the transport features and review the first-principles approaches that solve the transport equations. We then present the first-principles results on the thermal and electrical transport properties of semiconductors. The discussions are grouped based on different scattering mechanisms including phonon-phonon scattering, phonon scattering by equilibrium electrons, carrier scattering by equilibrium phonons, carrier scattering by polar optical phonons, scatterings due to impurities, alloying and doping, and the phonon drag effect. We show how the first-principles methods allow one to investigate transport properties with unprecedented detail and also offer new insights into the electron and phonon transport. The current status of the simulation is mentioned when appropriate and some of the future directions are also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Impact of hydrogenation on the stability and mechanical properties of amorphous boron nitride

Abstract Interconnect materials with ultralow dielectric constant, and good thermal and mechanical properties are crucial for the further miniaturization of electronic devices. Recently, it has been demonstrated that ultrathin amorphous boron nitride (aBN) films have a very low dielectric constant, high density (above 2.1 g cm −3 ), high thermal stability, and mechanical properties. The excellent properties of aBN derive from the nature and degree of disorder, which can be controlled at fabrication, allowing tuning of the physical properties for desired applications. Here, we report an improvement in the stability and mechanical properties of aBN upon hydrogen doping. With the introduction of a Gaussian approximation potential for atomistic simulations, we investigate the changing morphology of aBN with varying H doping concentrations. We found that for 8 at% of H doping, the concentration ofsp 3 -hybridized atoms reaches to a maximum which leads to an improvement of thermal stability and mechanical properties by 20%. These results will be a guideline for experimentalists and process engineers to tune the growth conditions of aBN films for numerous applications.

Materials Science↗
DOE OSTI2022

Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems *

Abstract We introduce a multi-tasking graph convolutional neural network, HydraGNN, to simultaneously predict both global and atomic physical properties and demonstrate with ferromagnetic materials. We train HydraGNN on an open-source ab initio density functional theory (DFT) dataset for iron-platinum with a fixed body centered tetragonal lattice structure and fixed volume to simultaneously predict the mixing enthalpy (a global feature of the system), the atomic charge transfer, and the atomic magnetic moment across configurations that span the entire compositional range. By taking advantage of underlying physical correlations between material properties, multi-task learning (MTL) with HydraGNN provides effective training even with modest amounts of data. Moreover, this is achieved with just one architecture instead of three, as required by single-task learning (STL). The first convolutional layers of the HydraGNN architecture are shared by all learning tasks and extract features common to all material properties. The following layers discriminate the features of the different properties, the results of which are fed to the separate heads of the final layer to produce predictions. Numerical results show that HydraGNN effectively captures the relation between the configurational entropy and the material properties over the entire compositional range. Overall, the accuracy of simultaneous MTL predictions is comparable to the accuracy of the STL predictions. In addition, the computational cost of training HydraGNN for MTL is much lower than the original DFT calculations and also lower than training separate STL models for each property.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

On the relation of host properties and environment of AGN galaxies across the standard optical diagnostic diagram

ABSTRACT We study the host properties and environment of active galactic nuclei (AGNs) galaxies, taken from SDSS-DR12, across the [O iii]/H β versus [N ii]/H α diagnostic diagram. We select AGN subsamples defined as parallel and perpendicular to the star-forming locus on the BPT diagram based on the Kauffmann et al. and Schawinski et al. criteria. For parallel subsamples we find that AGN host properties exhibit a morphological evolution as they become more distant to the star-forming sequence. The local density environment shows a more evident morphology–density relationship for subsamples mainly formed by Composite and Spiral galaxies than those containing LINERs and Seyferts, where the AGN emission is the dominant source. We also analyse the properties of the five closest AGN neighbours observing no significant differences in the environment, although the AGN host properties of every subsample have noticeable variations. The AGNs belonging to perpendicular subsamples show clear differences on their host properties from left top to right bottom on the diagram. However, the analysis of the local density environment do not reflect strong dependency with the host AGN properties. This result is reinforced by the characteristics of the AGN neighbouring galaxies. These findings suggest that mixed AGN/star-forming galaxies present environmental features more similar to that of non-active galaxies. However, as AGNs at the centre of the more evolved galaxies become the dominant source, the environment tends to provide suitable conditions for the central black hole feeding with an increasing content of gas and likelihood of a higher merger rate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Unified first-principles theory of thermal properties of insulators

The conventional first-principles theory for the thermal and thermodynamic properties of insulators is based on the perturbative treatment of the anharmonicity of crystal bonds. While this theory has been a successful predictive tool for strongly bonded solids such as diamond and silicon, here we show that it fails dramatically for strongly anharmonic (weakly bonded) materials, and that the conventional quasiparticle picture breaks down at relatively low temperatures. To address this failure, we present a unified first-principles theory of the thermodynamic and thermal properties of insulators that captures multiple thermal properties within the same framework across the full range of anharmonicity from strongly bonded to weakly bonded insulators. This theory features a new phonon renormalization approach derived from many-body physics that creates well-defined quasiparticles even at relatively high temperatures, and it accurately captures the effects of strongly anharmonic bonds on phonons and thermal transport. Using a prototypical strongly anharmonic material, sodium chloride (NaCl), as an example, we demonstrate that our new first-principles framework simultaneously captures the apparently contradictory experimental observations of large thermal expansion and low thermal conductivity of NaCl on the one hand, and anomalously weak temperature dependence of phonon modes on the other, while the conventional theory fails in all three cases. Here we demonstrate that four-phonon scattering due to higher-order anharmonicity significantly lowers the thermal conductivity of NaCl and is required for a proper comparison to experiment. Furthermore, we show that our renormalization framework, along with four-phonon scattering, also successfully predicts the measured phonon frequencies and thermal properties of a weakly anharmonic material, diamond, indicating universal applicability for thermal properties of insulators. Our work gives new insights into the physics of heat flow in solids, and presents a computationally efficient and rigorous framework that captures the thermal and thermodynamic properties of both weakly and strongly bonded insulators simultaneously.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Nature of Interatomic Bonding in Controlling the Mechanical Properties of Calcium Silicate Hydrates

Calcium silicate hydrate (C–S–H) is the most important phase of hydrated cement gel which is the key material in construction industry. It is well accepted that hardened cement paste consists of either poorly crystalline or completely disordered phases. Although a myriad of speculative atomistic models of disordered C–S–H have been proposed, the fundamental basis of structure–property relationships remain elusive. This study focuses upon the correlations between mechanical properties and electronic structure based on well‐defined quantum mechanical parameters. We use 20 CSH minerals with known structure to gain fundamental understanding of structure–property relationship. The results indicate Si–O bond order density, which represents the cumulative bond strength of SiO bonds, has no direct correlation with bulk mechanical properties which is counterintuitive and against conventional wisdom. The variations are determined more precisely by the overall atomic and electronic structure dictated by bond order density of the Ca–O and hydrogen bonds ( HB ). Most importantly, there is a multifaceted balance between different types of interatomic bonds including the HB s in controlling mechanical properties. HB s categorized in relation to next nearest neighbor ( NNN ) enable us to identify specific types of HB s that are prevalent in CSH . In certain crystals such as suolunite, the HB network is organized in such a unique way that enhances its mechanical properties. The approach and findings presented in this paper points to a broad roadmap for the developing next‐generation cements.

Dharmawardhana, Chamila↗
DOE OSTI2016

Ab initio Modeling of the Electronic Structures and Physical Properties of a‐Si 1− x Ge x O 2 Glass ( x = 0 to 1)

The amorphous silica (a‐SiO 2 ) and germania (a‐GeO 2 ) have a wide range of applications in glass industry. Based on a previously constructed near‐perfect continuous random network model with 1296 atoms and periodic boundary conditions, we extend our study to amorphous Si 1− x G e x O 2 models of homogeneous random substitution of Si by Ge with x ranging from 0 to 1. We have calculated the structural, electronic, mechanical, and optical properties for the series by using the first‐principles density functional theory methods. The x ‐dependence of the variations in the properties is analyzed and critically compared with available experimental data. The mass density, volume, total bond order density, bulk mechanical properties, and refractive index are found to vary linearly as a function of x . For x = 0.5, we have also constructed six different kinds of particle immersion models to test the effect of inclusion of spherical particles of one glass of different sizes in the medium of the other glass on their physical properties. It is shown that particle sizes do affect the properties of particle immersion. Our calculations provide deep insight on the properties of mixture and nanocomposites of a‐SiO 2 and a‐GeO 2 glasses.

Baral, Khagendra↗
DOE OSTI2024

A recyclable self-healing composite with advanced sensing property

Polymer-based composites frequently encounter damage, often lurking beneath the surface and proving challenges to their early detection and repair. While material-based sensors show promise for encoding self-sensing properties within these composites, their in situ healing and reprocessability remain significant challenges. Therefore, the overarching goal of this study is the creation of a reprocessable polymeric composite encoded with self-healing attributes and the ability to autonomously sense damage. At the core of this innovation are vitrimers, a polymeric material characterized by a covalently adaptive dynamic network responsive to external factors such as heat. They combine thermoset-like resilience with thermoplastic-like flowability on demand under external stimuli. We nanoengineer a polyester-based vitrimeric polymer by incorporating piezoresistive carbon nanotubes (CNTs) as reinforcing elements that not only enhance its mechanical strength but also create a percolation network within the composite, thereby enabling piezoresistive self-sensing properties, all the while preserving the intrinsic self-healing capabilities offered by the vitrimeric matrix. The fabrication process of the composite involves a solvent-free in situ polymerization method that combines epoxy and anhydride-containing monomers with ~ 0.1 wt.% of CNTs. Once it was established that the introduction of CNTs into the polymeric matrix did not compromise the mechanical properties of the composite, their strain-sensing properties were characterized by applying cyclic loading while measuring their electrical resistance. Strikingly, CNT-enhanced vitrimer composite consistently retains its mechanical and sensing properties through repeated cycles of reshaping and reprocessing, underscoring its potential as a robust distributed strain sensor. This polyester-based vitrimeric composite is also easily recyclable without harsh chemical treatments. Preliminary findings from this study conclusively demonstrate that the bulk composite boasts both self-sensing capabilities and in situ detect healing properties, charting a promising course towards the development of a mechanically resilient multifunctional composite that seamlessly integrates selfsensing and healing capabilities.

Rohewal, Sargun Singh↗
DOE OSTI2014

SU-E-QI-08: Fourier Properties of Cone Beam CT Projection

Purpose: To explore the Fourier properties of cone beam CT (CBCT) projections and apply the property to directly estimate noise level of CBCT projections without any prior information. Methods: By utilizing the property of Bessel function, we derivate the Fourier properties of the CBCT projections for an arbitrary point object. It is found that there exists a double-wedge shaped region in the Fourier space where the intensity is approximately zero. We further derivate the Fourier properties of independent noise added to CBCT projections. The expectation of the square of the module in any point of the Fourier space is constant and the value approximately equals to noise energy. We further validate the theory in numerical simulations for both a delta function object and a NCAT phantom with different levels of noise added. Results: Our simulation confirmed the existence of the double-wedge shaped region in Fourier domain for the x-ray projection image. The boundary locations of this region agree well with theoretical predictions. In the experiments of estimating noise level, the mean relative error between the theory estimation and the ground truth values is 2.697%. Conclusion: A novel theory on the Fourier properties of CBCT projections has been discovered. Accurate noise level estimation can be achieved by applying this theory directly to the measured CBCT projections. This work was supported in part by NIH(1R01CA154747-01), NSFC((No. 61172163), Research Fund for the Doctoral Program of Higher Education of China (No. 20110201110011) and China Scholarship Council.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Invasive Plants Rapidly Reshape Soil Properties in a Grassland Ecosystem

In this study, we show how invasive plant species drive rapid shifts in the soil environment from surrounding native communities. Each of the three plant invaders had different but consistent effects on soils. Thus, there does not appear to be a one-size-fits-all strategy for how plant invaders alter grassland soil environments. This work represents a crucial step toward understanding how invaders might be able to prevent or impair native reestablishment by changing soil biotic and abiotic properties. Plant invasions often reduce native plant diversity and increase net primary productivity. Invaded soils appear to differ from surrounding soils in ways that impede restoration of diverse native plant communities. We hypothesize that invader-mediated shifts in edaphic properties reproducibly alter soil microbial community structure and function. Here, we take a holistic approach, characterizing plant, prokaryotic, and fungal communities and soil physicochemical properties in field sites, invasion gradients, and experimental plots for three invasive plant species that cooccur in the Rocky Mountain West. Each invader had a unique impact on soil physicochemical properties. We found that invasions drove shifts in the abundances of specific microbial taxa, while overall belowground community structure and functional potential were fairly constant. Forb invaders were generally enriched in copiotrophic bacteria with higher 16S rRNA gene copy numbers and showed greater microbial carbohydrate and nitrogen metabolic potential. Older invasions had stronger effects on abiotic soil properties, indicative of multiyear successions. Overall, we show that plant invasions are idiosyncratic in their impact on soils and are directly responsible for driving reproducible shifts in the soil environment over multiyear time scales. IMPORTANCE In this study, we show how invasive plant species drive rapid shifts in the soil environment from surrounding native communities. Each of the three plant invaders had different but consistent effects on soils. Thus, there does not appear to be a one-size-fits-all strategy for how plant invaders alter grassland soil environments. This work represents a crucial step toward understanding how invaders might be able to prevent or impair native reestablishment by changing soil biotic and abiotic properties.

Microbiology↗
DOE OSTI2024

A Deep Multimodal Representation Learning Framework for Accurate Molecular Properties Prediction

Drug discovery is a complex and challenging process, requiring the optimization of candidate compounds to identify those with the potential to become safe and effective drugs. Predicting molecular properties is an indispensable step in the drug discovery pipeline. Traditionally, this process is costly and time-intensive, involving multiple rounds of experiments and clinical trials, rendering it impractical for every candidate compound. Deep learning techniques have emerged as a promising approach to drug discovery to reduce the cost and time required to identify novel drugs. However, prevalent research in deep learning models focused on predicting molecular properties has primarily fixated on single-modal models, which utilize a single modality of data, neglecting the potential benefits of combining different data modalities. To overcome this limitation, we introduce MRL-Mol: a deep \textbf{M}ultimodal \textbf{R}epresentation \textbf{L}earning framework for accurate \textbf{Mol}ecular properties prediction. MRL-Mol harnesses three data modalities: sequence, graph, and image, augmenting the depth of comprehension. Leveraging a large-scale unlabeled dataset~($\sim$1M unique molecules), we pretrain MRL-Mol to extract inter- and intra-modal information. Our study demonstrates the superior performance of MRL-Mol in predicting molecular properties across six benchmark datasets, including both classification and regression tasks. Notably, MRL-Mol outperforms other state-of-the-art molecular properties prediction models. These findings suggest that by combining information from multiple data modalities, MRL-Mol can comprehend molecules better than single-modal deep learning models and identify molecular properties with better accuracy.

Yang, Yuxin↗
DOE OSTI2016

Experimental correlation between nonlinear optical and magnetotransport properties observed in Au-Co thin films

Magnetic materials where at least one dimension is in the nanometer scale typically exhibit different magnetic, magnetotransport, and magnetooptical properties compared to bulk materials. Composite magnetic thin films where the matrix composition, magnetic cluster size, and overall composite film thickness can be experimentally tailored via adequate processing or growth parameters offer a viable nanoscale platform to investigate possible correlations between nonlinear magnetooptical and magnetotransport properties, since both types of properties are sensitive to the local magnetization landscape. As a result, it has been shown that the local magnetization contrast affects the nonlinear magnetooptical properties as well as the magnetotransport properties in magnetic-metal/nonmagnetic metal multilayers; thus, nanocomposite films showcase another path to investigate possible correlations between these distinct properties which may prove useful for sensing applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Cover Crops and Corn Residue Removal: Impacts on Soil Hydraulic Properties and Their Relationships with Carbon

Large-scale crop residue removal may negatively affect soil water dynamics. Integrating cover crop (CC) with crop residue management can be a strategy to offset potential adverse effects of residue removal. We studied: (i) the impact of corn (Zea mays L.) residue removal (56%) with and without the use of winter rye (Secale cereale L.) CC on soil hydraulic properties, (ii) whether CC would ameliorate residue removal effects on hydraulic properties, and (iii) relationships of hydraulic properties with soil organic C (SOC) and other properties under irrigated no-till continuous corn on a silt loam in south central Nebraska after 5 and 6 yr of management. Cover crops did not affect soil hydraulic properties. However, residue removal reduced cumulative water infiltration by about 45% in one year. Across years, residue removal reduced plant available water (PAW) by 32% and mean weight diameter of water-stable aggregates (MWD) by 23% for the upper 5-cm soil depth. Under no CC, residue removal reduced SOC concentration by 25% in the 0- to 5-cm and by 11% in the 5- to 10-cm depths. Under residue removal, CC increased SOC concentration by 18% in the 0- to 5-cm and by 8% in the 5 to 10-cm depths. Cover crop did not completely offset the residue removal-induced decrease in SOC concentration in the upper 5-cm depth. Furthermore, plant available water decreased as SOC concentration and MWD decreased. After 6 yr, corn residue removal adversely affected soil hydraulic properties and SOC concentration, but CC was unable to fully offset such adverse impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Characterization of Thermal, Hydraulic, and Gas Diffusion Properties in Variably Saturated Sand Grades

Core Ideas This study provides physical, hydraulic, and thermal properties of five sand grades. An extended three‐region thermal conductivity model is proposed. A gas diffusivity‐based variable tortuosity parameter is examined. Useful parametric functions and descriptive models were tested. Detailed characterization of partially saturated porous media is important for understanding and predicting vadose zone transport processes. While basic properties (e.g., particle‐ and pore‐size distributions and soil‐water retention) are, in general, essential prerequisites for characterizing most porous media transport properties, key transport parameters such as thermal conductivity and gas diffusivity are particularly important to describe temperature‐induced heat transport and diffusion‐controlled gas transport processes, respectively. Despite many experimental and numerical studies focusing on a specific porous media characteristic, a single study presenting a wide range of important characteristics, together with the best‐performing functional relationships, can seldom be found. This study characterized five differently textured sand grades (Accusand no. 12/20, 20/30, 30/40, 40/50, and 50/70) in relation to physical properties, water retention, hydraulic conductivity, thermal conductivity, and gas diffusivity. We used measured basic properties and transport data to accurately parameterize the characteristic functions (particle‐ and pore‐size distributions and water retention) and descriptive transport models (thermal conductivity, saturated hydraulic conductivity, and gas diffusivity). An existing thermal conductivity model was improved to describe the distinct three‐region behavior in observed thermal conductivity–water saturation relations. Applying widely used parametric models for saturated hydraulic conductivity and soil‐gas diffusivity, we characterized porous media tortuosity in relation to grain size. Strong relations among average particle diameter, characteristic pore diameter from soil‐water retention measurements, and saturated hydraulic conductivity were found. Thus, the results of this work are useful toward better describing, linking, and predicting mass transfer and pore network properties in variably saturated porous media.

Chamindu Deepagoda, T. K. K.↗
DOE OSTI2015

Thermal Properties for the Thermal-Hydraulics Analyses of the BR2 Maximum Nominal Heat Flux

This memo describes the assumptions and references used in determining the thermal properties for the various materials used in the BR2 HEU (93% enriched in 235 U) to LEU (19.75% enriched in 235 U) conversion feasibility analysis. More specifically, this memo focuses on the materials contained within the pressure vessel (PV), i.e., the materials that are most relevant to the study of impact of the change of fuel from HEU to LEU. Section 2 provides a summary of the thermal properties in the form of tables while the following sections and appendices present the justification of these values. Section 3 presents a brief background on the approach used to evaluate the thermal properties of the dispersion fuel meat and specific heat capacity. Sections 4 to 7 discuss the material properties for the following materials: i) aluminum, ii) dispersion fuel meat (UAlx-Al and U-7Mo-Al), iii) beryllium, and iv) stainless steel. Section 8 discusses the impact of irradiation on material properties. Section 9 summarizes the material properties for typical operating temperatures. Appendix A elaborates on how to calculate dispersed phase’s volume fraction. Appendix B provides a revised methodology for determining the thermal conductivity as a function of burnup for HEU and LEU.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Test to Extract Soil Properties Using the Seismic HammerTM Active Seismic Source

Geologic material properties are necessary parameters for ground motion modeling and are difficult and expensive to obtain via traditional methods. Alternative methods to estimate soil properties require a measurement of the ground's response to a force. A possible method of obtaining these measurements is active-source seismic surveys, but measurements of the ground response at the source must also be available. The potential of seismic sources to obtain soil properties is limited, however, by the repeatability of the source. Explosives, and hammer surveys are not repeatable because of variable ground coupling or swing strength. On the other hand, the Seismic Hammer TM (SH) is consistent in the amount of energy it inputs into the ground. In addition, it leaves large physical depressions as a result of ground compaction. The volume of ground compaction varies by location. Here, we hypothesize that physical depressions left in the earth by the SH correlate to energy recorded by nearby geophones, and therefore are a measurement of soil physical properties. Using measurements of the volume of shot holes, we compare the spatial distribution of the volume of ground compacted between the different shot locations. We then examine energy recorded by the nearest 50 geophones and compare the change in amplitude across hits at the same location. Finally, we use the percent difference between the energy recorded by the first and later hits at a location to test for a correlation to the volume of the shot depressions. We find that: * Ground compaction at the shot-depression does cluster geographically, but does not correlate to known surface features. * Energy recorded by nearby geophones reflects ground refusal after several hits. * There is no correlation to shot volume and changes in energy at particular shot locations. Deeper material properties (i.e. below the depth of surface compaction) may be contributing to the changes in energy propagation. * Without further processing of the data, shot-depression volumes are insufficient to understanding ground response to the SH. Without an accurate understanding of the ground response, we cannot extract material properties in conjunction with the SH survey. Additional processing including picking direct arrivals and static corrections may yield positive results.

58 GEOSCIENCES↗
DOE OSTI2019

Developing a Macro-scale SiC-cladding Behavior Model Based on Localized Mechanical and Thermal Property Evaluation on Pre- and Post-Irradiation SiC-SiC Composites (Final Report)

Silicon carbide is being investigated for accident tolerant fuel cladding applications due to its good neutronic performance, high temperature strength, exceptional stability under irradiation, and reduced oxidation compared to Zircaloy under accident conditions. The development and investigation of these materials is particularly important in the light of the Fukushima event and subsequent emphasis in DOE on accident tolerant fuel (ATF) concepts. In this work, we propose to develop and improve upon existing small-scale mechanical and thermal characterization methods, including micro-cantilever bend tests and fiber push-out tests, and time-domain thermo-reflectance measurements. These techniques will be applied to evaluate micro-scale properties of SiC-SiC composite constituents (matrix, fibers, interphase). The results will be coupled with meso-scale fiber and void structural information and be used as input to develop a comprehensive, finite element-based model based on constituent properties. The goal of this multi-scale model is to be used to predict anisotropic mechanical and thermal cladding behaviors. The model will be benchmarked against measurements of bulk properties and validated for radiation-damaged materials by utilizing irradiated SiC-SiC composites available from General Atomics. The characterization approach developed under this program will have particular application in the property prediction of reactor irradiated materials, as only small volumes need to be tested, minimizing associated hazards and costs. The micro-scale test methods developed here will be used along with meso-scale structural data to inform a finite element model of the full SiC-based cladding system. This model will capture fabrication and irradiation effects and importantly include for the first-time separate material data for each system component. The incorporation of these micro-scale effects will lead to a more accurate model of SiC-SiC composite behavior, enabling further advancements in the development and design of SiC-based materials for improved fuel cladding performance. The aim of this work is to develop advanced localized material characterization techniques to directly measure mechanical and thermal properties of the individual constituents of SiC-based claddings at the relevant micro-scale. SiC-SiC composites will be evaluated before and after irradiation and these results will be coupled with macro-scale properties and microstructural information in order to provide the input parameters for a comprehensive finite element model, which will be developed in this program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Macro-physical Properties of Shallow Cumulus from Integrated ARM Observations (Final Report)

Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.

54 ENVIRONMENTAL SCIENCES↗