Exploring microstructures in lower mantle mineral assemblages with synchrotron x-rays
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Chandler, Brian↗
SEARCH · Engineering Papers
Results for “Phase distribution”
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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The Potts model on a Bethe lattice with nonmagnetic impurities
We have obtained a solution for the Potts model on a Bethe lattice with mobile nonmagnetic impurities. A method is proposed for constructing a “pseudochaotic” impurity distribution by a vanishing correlation in the arrangement of impurity atoms for the nearest sites. For a pseudochaotic impurity distribution, we obtained the phase-transition temperature, magnetization, and spontaneous magnetization jumps at the phase-transition temperature.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Detection and Identification of Human Locomotion by Distributed Acoustic Sensing with Deep Neural Networks
This paper reports intrusion detection using distributed acoustic sensors based on phase- sensitive enhanced Rayleigh scattering optical time-domain reflectometry. Vibration data induced by human locomotion was analyzed by convolution neural networks and achieve over 76.25% accuracy on human identification.
Peng, Zhaoqiang↗
Efficient design of random metasurfaces
Random media introduce large degrees of freedom in device design and can thus address challenges in manipulating optical waves. Wave shaping with metasurfaces has mainly utilized periodic or quasi-periodic grids, and the potential of random arrangement of particles for devices has only come under investigation recently. The main difficulty in pursuing random metasurfaces is the identification of the degrees of freedom that optimize their efficiencies and functions. They can also encode information using the statistics of particle distribution. We propose a phase-map that accounts for the statistical nature of random media. The method takes into account effects of random near-field couplings that introduce phase errors by affecting the phase shift of elements. The proposed approach increases the efficiency of our random metasurface devices by up to ~20%. Furthermore, this work paves the way toward the efficient design of random metasurfaces with potential applications in highly secure optical cryptography and information encoding.
Nasari, Hadiseh↗
Alloying effect of niobium and tin on the zirconium alloy fuel cladding behavior at high temperature oxidation in steam - 2016-0072
As the materials for fuel claddings for water-cooled reactors, binary and multicomponent zirconium alloys zirconium-niobium (Zr-Nb) (E110, M5), zirconium-tin-iron (Zr-Sn-Fe) (Zircaloy-2,-4), and zirconium-niobium-tin-iron (Zr-Nb-Sn-Fe) (E635, ZIRLO{sup R} ) most commonly are used. Improvement extends, in particular, by varying their composition by niobium, tin, and iron. At the same time, importance is given to ensuring the safe operation of the fuel rods not only in normal conditions but also in emergency situations such as a loss of coolant accident. In this paper, we present the research results of studies of the influence of alloying elements niobium, tin, and iron on corrosion resistance and embrittlement at high-temperature steam oxidation of fuel claddings based on the alloy types Zr-xNb (x=1.0/2.5) and Zr-xNb-ySn-zFe (x=0.6/2.4; y=0.24/1.1; z=0.18/0.34) made by using zirconium sponge. We conducted high-temperature steam oxidation tests at temperatures of 1,000 deg. C, 1,100 deg. C, and 1,200 deg. C with continuous measurement of the weight gain during the experiment and subsequent cooling in steam with rate ∼ 20 deg. C/s. We conducted studies of kinetics of high-temperature oxidation in steam, structural-phase state changes, alloying elements distribution, absorbed hydrogen content, and residual ductility after rapid cooling of the oxidized specimens. We revealed the difference in the oxidation kinetics of the materials studied, which decreased as the oxidation temperature increased. Likewise, an increase of the tin content in the alloy influenced a specimen's breakaway oxidation intensification at 1,000 deg. C. This shows that the mechanical properties of fuel claddings oxidized under the same conditions depend on their alloying composition, and the hydrogen fraction is absorbed by the specimen and formed by the oxidation of ZrO{sub 2}, α-Zr(O), and ex-β layer structures, which in turn varies depending on the alloy composition. The increase of niobium, tin, and iron content in the zirconium alloy leads to a decrease in the residual ductility of fuel claddings after high-temperature steam oxidation. According to obtained results, among the materials studied, Zr-1.0Nb alloy is the most resistant to embrittlement during high-temperature steam oxidation at temperatures of 1,000-1,200 deg. C. (authors)
36 MATERIALS SCIENCE↗
"Sintering" Models and In-Situ Experiments: Data Assimilation for Microstructure Prediction in SLS Additive Manufacturing of Nylon Components
Selective laser sintering methods are workhorses for additively manufacturing polymer-based components. The ease of rapid prototyping also means it is easy to produce illicit components. It is necessary to have a data-calibrated in-situ physical model of the build process in order to predict expected and defective microstructure characteristics that inform component provenance. Toward this end, sintering models are calibrated and characteristics such as component defects are explored. This is accomplished by assimilating multiple data streams, imaging analysis, and computational model predictions in an adaptive Bayesian parameter estimation algorithm. From these data sources, along with a phase-field model, bulk porosity distributions are inferred. Model parameters are constrained to physically-relevant search directions by sensitivity analysis, and then matched to predictions using adaptive sampling. Using this feedback loop, data-constrained estimates of sintering model parameters along with uncertainty bounds are obtained.
3D printing, Additive Manufacturing, polymer, sint↗
Effect of thermal annealing on microstructure evolution and mechanical behavior of an additive manufactured AlSi10Mg part
The powder-bed laser additive manufacturing (AM) process is widely used in the fabrication of three-dimensional metallic parts with intricate structures, where kinetically controlled diffusion and microstructure ripening can be hindered by fast melting and rapid solidification. Therefore, the microstructure and physical properties of parts made by this process will be significantly different from their counterparts produced by conventional methods. This work investigates the microstructure evolution for an AM fabricated AlSi10Mg part from its nonequilibrium state toward equilibrium state. Special attention is placed on silicon dissolution, precipitate formation, collapsing of a divorced eutectic cellular structure, and microstructure ripening in the thermal annealing process. These events alter the size, morphology, length scale, and distribution of the beta silicon phase in the primary aluminum, and changes associated with elastic properties and microhardness are reported. In conclusion, the relationship between residual stress and silicon dissolution due to changes in lattice spacing is also investigated and discussed.
36 MATERIALS SCIENCE↗
Muon Beam Dynamics and Spin Dynamics in the g-2 Storage Ring
The goal of the new g-2 experiment at fermilab is a measurement of the anomalous magnetic moment of the muon, with uncertainty of less than 140 ppb. The experimental method is to store a beam of polarized muons in a storage ring with pure vertical dipole field and electrostatic focusing, and to measure the precession frequency. Control of the systematics depends on unprecedented knowledge of the details of the phase space of the muon distribution. That knowledge is derived from direct measurements with scintillating fiber detectors that are inserted into the muon beam for diagnostic measurements, traceback straw tube tracking chambers, as well as the calorimeters that measure energy, time and position of the decay positrons. The interpretation of the measurements depends on a detailed model of the storage ring guide field. This invited talk presents results of studies of the distribution from the commissioning run of the experiment.
43 PARTICLE ACCELERATORS↗
On the Numerical Dispersion of Electromagnetic Particle-In-Cell Code : Finite Grid Instability
The Particle-In-Cell (PIC) method is widely used in relativistic particle beam and laser plasma modeling. However, the PIC method exhibits numerical instabilities that can render unphysical simulation results or even destroy the simulation. For electromagnetic relativistic beam and plasma modeling, the most relevant numerical instabilities are the finite grid instability and the numerical Cherenkov instability. We review the numerical dispersion relation of the electromagnetic PIC algorithm to analyze the origin of these instabilities. We rigorously derive the faithful 3D numerical dispersion of the PIC algorithm, and then specialize to the Yee FDTD scheme. In particular, we account for the manner in which the PIC algorithm updates and samples the fields and distribution function. Temporal and spatial phase factors from solving Maxwell's equations on the Yee grid with the leapfrog scheme are also explicitly accounted for. Numerical solutions to the electrostatic-like modes in the 1D dispersion relation for a cold drifting plasma are obtained for parameters of interest. In the succeeding analysis, we investigate how the finite grid instability arises from the interaction of the numerical 1D modes admitted in the system and their aliases. The most significant interaction is due critically to the correct representation of the operators in the dispersion relation. We obtain a simple analytic expression for the peak growth rate due to this interaction.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
CTF Void Drift Validation Study
This milestone report is a summary of work performed in support of expansion of the validation and verification (V&V) matrix for the thermal-hydraulic subchannel code, CTF. The focus of this study is on validating the void drift modeling capabilities of CTF and verifying the supporting models that impact the void drift phenomenon. CTF uses a simple turbulent-diffusion approximation to model lateral cross-flow due to turbulent mixing and void drift. The void drift component of the model is based on the Lahey and Moody model. The models are a function of two-phase mass, momentum, and energy distribution in the system; therefore, it is necessary to correctly model the ow distribution in rod bundle geometry as a first step to correctly calculating the void distribution due to void drift.
97 MATHEMATICS AND COMPUTING↗
IMoFi - Intelligent Model Fidelity: Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration (Final Report)
This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO) to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.
14 SOLAR ENERGY↗
Predictive Tools for Customizing Heat Treatment of Additively Manufactured Aerospace Components
Laser-bed powder fusion (LBPF) additive manufacturing is increasingly being used to produce components of complex geometries using the Ni-base superalloy Inconel 718. The composition and the microstructure of the alloy are currently well optimized for wrought components made using conventional manufacturing processes such as rolling, forging, extrusion, etc. The attractive mechanical properties of the alloy result from the underlying austenitic matrix with fine equiaxed grains, and a high density and uniform distribution of the precipitation hardening phase, γ". Heat treatment steps such as homogenization, solutioning and aging are well documented for the wrought alloy. However, when the same wrought alloy compositions are used for the additive manufacturing (AM) processes, the asprocessed microstructure is significantly different, because of the different thermal history associated with LBPF, including rapid solidification and multiple temperature excursions that lead to multiple re-melting and reheating in the solid state. Rapid solidification introduces potential non-equilibrium effects at the moving solid-liquid interfaces that impact the extent of solute segregation, as well as the morphology of the dendritic grains that form. In order to recover the target mechanical properties, AM components have to undergo post-process heat treatments. However, such heat treatments have to be custom designed for the AM process and the component geometry because of the expected vast differences in the microstructure at various locations of a component with complex geometry. The homogenization and precipitation steps should be optimized for the component so that target mechanical properties can be obtained throughout the part. The objective of this research is to utilize High Performance Computing in phase field simulations of microstructure evolution during post-processing of AM components. The physics-based modeling will be beneficial in reducing the experimental effort required for heat treatment process selection, optimization, and certification, thus leading to a significant reduction in energy consumption for AM and post-processing heat treatment. The optimization study will help identify heat treatments steps that are critical for development of a final desired microstructure with the minimum energy input. This combined with shortening of the production cycle (time-to-market) by reducing the number of failed parts (property targets), and reduction in the number of iterations for process optimization, will enable 30-40% savings in the energy costs. Phase field simulations of the degree of homogenization and the effect of local matrix composition on the nucleation and growth of competing precipitating phases were performed using the Microstructure Evolution Using Massively Parallel Phase Field Simulations code developed in-house at the Oak Ridge National Laboratory. The simulations were able to successfully capture the kinetics of nucleation and growth, and morphologies of various precipitating phases as a function of local matrix compositions and composition gradients characteristic of local microstructures arising from location-dependent variations in the thermal conditions. Future work will involve extending the simulations to a length scale consisting of multiple dendrites, so that the effect of homogenization on the coarsening of the dendrites can be simulated and used as an additional input to the optimization of the heat treatment process.
36 MATERIALS SCIENCE↗
IMoFi (Intelligent Model Fidelity): Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration Updated Accomplishments
This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO), including some updates from the previous report SAND2022-0215, to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.
14 SOLAR ENERGY↗
Automated Particle Analysis of Hanford Tank Wastes 241-AN-106, 241-AN-101, and 241-AW-105
This effort is involved in developing particle size and density distribution (PSDD) for the major phases within Hanford tank waste sludge. The object of this work has been to use automated particle analysis (APA) methods on the Scanning Electron Microscope (SEM) to provide PSDDs. The PSDD can be used to quantify the proportion of gibbsite particles likely to settle quickly and enable blending of wastes that may be prone to pipeline plugging such as the uranium phase, clarkeite with other wastes. The Hanford tank waste solids were analyzed with SEM combined with x-ray Energy Dispersive Spectroscopy (EDS) using APA. This method can allow thousands of individual particles to be characterized and so may provide a more representative view of the samples and information PSDDs. We characterized several as-received sludge samples and developed PSDD with APA. Sample preparation methods were found to impact the collected results, as it was more difficult to collect representative samples of the larger particles. Much of the material was also dried and cemented together that further impacted results.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Synthesis and Lithium Storage Properties of Spinel (Al 0.2 Mn 0.2 Co 0.2 Ni 0.2 Zn 0.2 ) 3 O 4 High-Entropy Oxide
High-entropy oxides (HEOs) have garnered significant interest as next-generation anode materials for lithium-ion batteries (LIBs) due to their high theoretical specific capacity and excellent structural stability. This study successfully synthesized spinel-structured (Al 0.2 Mn 0.2 Co 0.2 Ni 0.2 Zn 0.2 ) 3 O 4 HEO via a sol–gel method. The material was characterized by XRD, Raman and TEM, confirming a homogeneous single-phase spinel structure, with uniformly distributed elements-a hallmark of HEOs. Electrochemical tests demonstrated a stable cycling performance (438 mAh g −1 at 100 mA g −1 after 100 cycles and 350 mAh g −1 at 1 A g −1 after 1000 cycles) and rate capacity of 159 mAh g −1 at 2 A g −1 , The remarkable long-term cyclability and good rate capability highlight the potential of this HEO for practical applications in durable, high-power lithium-ion batteries. This work underscores the advantage of incorporating structurally stabilizing elements in HEOs for advanced energy storage.
anode materials↗
Detecting Long-period Variability in the SDSS Stripe 82 Standards Catalog
We report the results of a search for long-period (100 < P < 600 days) periodic variability in the SDSS Stripe 82 standards catalog. The SDSS coverage of Stripe 82 enables such a search because there are on average 20 observations per band in ugriz bands for about one million sources, collected over about 6 yr, with a faint limit of r ~ 22 mag and precisely calibrated 1%–2% photometry. We calculated the periods of variable source candidates in this sample using the Lomb–Scargle periodogram and considered the three highest periodogram peaks in each of the gri filters as relevant. Only those sources with gri periods consistent within 0.1% were later studied. We use the Kuiper statistic to ensure uniform distribution of data points in phased light curves. We present five sources with the spectra consistent with quasar spectra and plausible periodic variability. This SDSS-based search bodes well for future sensitive large-area surveys, such as the Rubin Observatory Legacy Survey of Space and Time, which, due to its larger sky coverage (about a factor of 60) and improved sensitivity (~2 mag), will be more powerful for finding such sources.
79 ASTRONOMY AND ASTROPHYSICS↗
Axial dispersion and mixing of coolant gas within a separate-effect prismatic modular reactor
Multiphase Reactors Engineering and Applications Laboratory performed gas phase dispersion experiments in a separate-effect cold-flow experimental setup for coolant flow within heated channels of the prismatic modular reactor under accident scenario using gaseous tracer technique. The separate-effect experimental setup was designed on light of local velocity measurements obtained by using hot wire anemometry. The measurements consist of pulse-response of gas tracer that is flowing through the mimicked riser channel using air as a carrier. The dispersion of the gas phase within the separate-effect riser channel was described using one-dimensional axial dispersion model. The axial dispersion coefficient and Peclet number of the coolant gas phase and their residence time distribution within were measured. Effect of heating intensities in terms of heat fluxes on the coolant gas dispersion along riser channels were mimicked in the current study by a certain range of volumetric air flow rate ranging from 0.0015 to 0.0034 m 3 /s which corresponding to heating intensity range from 200 to 1400 W/m 2 . Results confirm a reduction in the response curve spreads is achieved by increasing the volumetric air velocity (representing heating intensity). Also, the results reveal a reduction in values of axial dispersion coefficient with increasing the air volumetric flow rate.
Said, Ibrahim↗
Impacts of secondary ice production on Arctic mixed-phase clouds based on ARM observations and CAM6 single-column model simulations
For decades, measured ice crystal number concentrations have been found to be orders of magnitude higher than measured ice-nucleating particle number concentrations in moderately cold clouds. This observed discrepancy reveals the existence of secondary ice production (SIP) in addition to the primary ice nucleation. However, the importance of SIP relative to primary ice nucleation remains highly unclear. Furthermore, most weather and climate models do not represent SIP processes well, leading to large biases in simulated cloud properties. This study demonstrates a first attempt to represent different SIP mechanisms (frozen raindrop shattering, ice–ice collisional breakup, and rime splintering) in a global climate model (GCM). The model is run in the single column mode to facilitate comparisons with the Department of Energy (DOE)'s Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE) observations. We show the important role of SIP in four types of clouds during M-PACE (i.e., multilayer, single-layer stratus, transition, and frontal clouds), with the maximum enhancement in ice crystal number concentrations up to 4 orders of magnitude in moderately supercooled clouds. We reveal that SIP is the dominant source of ice crystals near the cloud base for the long-lived Arctic single-layer mixed-phase clouds. The model with SIP improves the occurrence and phase partitioning of the mixed-phase clouds, reverses the vertical distribution pattern of ice number concentrations, and provides a better agreement with observations. The findings of this study highlight the importance of considering SIP in GCMs.
54 ENVIRONMENTAL SCIENCES↗