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DOE OSTI2022

Modeling Isotope Separation in Electrochemical Lithium Deposition

Naturally occurring Li consists of two stable isotopes, 6 Li with an abundance of about 7.5%, and 7 Li making up the remainder with 92.5%. The development of a 6 Li enrichment technique, in terms of technical reliability and environmental safety to reach 6 Li future requirements, represents a key step in the roadmap for nuclear fusion energy supply worldwide. This paper uses finite element analysis-based models to simulate electrochemical Li isotope separation, which is an attractive method in terms of simplicity, safety, and scalability. In the model, we quantitatively analyze how different electrochemical factors including thermodynamics, charge-transfer kinetics, and diffusivities affect the separation process (separation factor), together with cell parameters, such as cell length and current density. The maximum separation factor of 1.128 could be obtained with the cell under the optimal thermodynamic, kinetic, and diffusive conditions, which is among the highest separation factors ever reported. Furthermore, these results will assist in designing the actual isotope separation setup with large separation factor and appropriate timing for sample collection.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2017

Broadening of Cloud Droplet Spectra through Eddy Hopping: Turbulent Adiabatic Parcel Simulations

Abstract This paper investigates spectral broadening of droplet size distributions through a mechanism referred to as the eddy hopping. The key idea, suggested a quarter century ago, is that droplets arriving at a given location within a turbulent cloud follow different trajectories and thus experience different growth histories and that this leads to a significant spectral broadening. In this study, the adiabatic parcel model with superdroplets is used to contrast droplet growth with and without turbulence. Turbulence inside the parcel is described by two parameters: (i) the dissipation rate of the turbulent kinetic energy ε and (ii) the linear extent of the parcel L. As expected, an adiabatic parcel without turbulence produces extremely narrow droplet spectra. In the turbulent parcel, a stochastic scheme is used to account for vertical velocity fluctuations that lead to local supersaturation fluctuations for each superdroplet. These fluctuations mimic the impact of droplets hopping turbulent eddies in a natural cloud. For L smaller than a few meters, noticeable spectral broadening is possible only for strong turbulence—say, ε > 100 cm2 s−3. For L typical for grid lengths of large-eddy simulation (LES) models (say, L between 10 and 100 m), the impact is significant even with relatively modest turbulence intensities. The impact increases with both L and ε. The representation of eddy hopping developed in this paper can be included in a straightforward way in the subgrid-scale scheme of a Lagrangian LES cloud model and may lead to a significant acceleration of simulated rain development through collision–coalescence.

Grabowski, Wojciech W.↗

DOE OSTI2017

Patient-specific modeling of individual sickle cell behavior under transient hypoxia

Sickle cell disease (SCD) is a highly complex genetic blood disorder in which red blood cells (RBC) exhibit heterogeneous morphology changes and decreased deformability. We employ a kinetic model for cell morphological sickling that invokes parameters derived from patient-specific data. This model is used to investigate the dynamics of individual sickle cells in a capillary-like microenvironment in order to address various mechanisms associated with SCD. We show that all RBCs, both hypoxia-unaffected and hypoxia-affected ones, regularly pass through microgates under oxygenated state. However, the hypoxia-affected cells undergo sickling which significantly alters cell dynamics. In particular, the dense and rigid sickle RBCs are obstructed thereby clogging blood flow while the less dense and deformable ones are capable of circumnavigating dead (trapped) cells ahead of them by choosing a serpentine path. Informed by recent experiments involving microfluidics that provide in vitro quantitative information on cell dynamics under transient hypoxia conditions, we have performed detailed computational simulations of alterations to cell behavior in response to morphological changes and membrane stiffening. Our model reveals that SCD exhibits substantial heterogeneity even within a particular density-fractionated subpopulation. These findings provide unique insights into how individual sickle cells move through capillaries under transient hypoxic conditions, and offer novel possibilities for designing effective therapeutic interventions for SCD.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Model Development in MARMOT for High Burn-up Structure Formation

A phase field model for the formation of High Burn-up Structure (HBS) was developed and implemented in MARMOT. The model takes into consideration the chemical energy of gas atoms, interfacial energies of grain boundaries and bubble surfaces, and strain energy associated with dislocations, which renders the model capable of simulating the concurrent formation and growth of both bubbles and sub-grains. Moreover, in contrast to existing phase-field models of recrystallization, the current model makes no ad hoc or a priori assumptions for the nucleation rate or recrystallized grain size and shape. All the model parameters were quantified in terms of thermodynamic and kinetic properties. The model predicts a strong effect of magnitude and distribution of dislocation density, grain boundary energy, and bubble surface energy on the formation of sub-grains. The model results were shown to agree well with theoretical predictions. For polycrystalline UO 2 at 1200K, the recrystallized average grain size was found to be on the order of of 0.6-1.3 microns at a burn-up in the range of 98-105 GWD/tU. These values lie well within the range of reported data in literature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

Development of a High Throughput Platform for Screening Glycoside Hydrolases Based on Oxime-NIMS

Cost-effective hydrolysis of biomass into sugars for biofuel production requires high-performance low-cost glycoside hydrolase (GH) cocktails that are active under demanding process conditions. Improving the performance of GH cocktails depends on knowledge of many critical parameters, including individual enzyme stabilities, optimal reaction conditions, kinetics, and specificity of reaction. With this information, rate- and/or yield-limiting reactions can be potentially improved through substitution, synergistic complementation, or protein engineering. Given the wide range of substrates and methods used for GH characterization, it is difficult to compare results across a myriad of approaches to identify high performance and synergistic combinations of enzymes. Here, we describe a platform for systematic screening of GH activities using automatic biomass handling, bioconjugate chemistry, robotic liquid handling, and nanostructure-initiator mass spectrometry (NIMS). Twelve well-characterized substrates spanning the types of glycosidic linkages found in plant cell walls are included in the experimental workflow. To test the application of this platform and substrate panel, we studied the reactivity of three engineered cellulases and their synergy of combination across a range of reaction conditions and enzyme concentrations. We anticipate that large-scale screening using the standardized platform and substrates will generate critical datasets to enable direct comparison of enzyme activities for cocktail design.

09 BIOMASS FUELS↗

DOE OSTI2024

Atomic Diffusivities of Yttrium, Titanium and Oxygen Calculated by Ab Initio Molecular Dynamics in Molten 316L Oxide-Dispersion-Strengthened Steel Fabricated via Additive Manufacturing

Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing steps required. Additive manufacturing (AM) can directly incorporate dispersion elements (e.g., Y, Ti and O) during component fabrication, thus bypassing the need for an ODS steel supply chain, the scale-up challenges of powder processing routes, the buoyancy challenges associated with casting ODS steels, and the joining issues for net-shape component fabrication. In the AM process, the diffusion of the dispersion elements in the molten steel plays a key role in the precipitation of the oxide particles, thereby influencing the microstructure, thermal stability and high-temperature mechanical properties of the resulting ODS steels. In this work, the atomic diffusivities of Y, Ti, and O in molten 316L stainless steel (SS) as functions of temperature are determined by ab initio molecular dynamics simulations. The latest Vienna Ab initio Simulation Package (VASP) package that incorporates an on-the-fly machine learning force field for accelerated computation is used. At a constant temperature, the time-dependent coordinates of the target atoms in the molten 316L SS were analyzed in the form of mean square displacement in order to obtain diffusivity. The values of the diffusivity at multiple temperatures are then fitted to the Arrhenius form to determine the activation energy and the pre-exponential factor. Given the challenges in experimental measurement of atomic diffusivity at such high temperatures and correspondingly the lack of experimental data, this study provides important physical parameters for future modeling of the oxide precipitation kinetics during AM process.

Chemistry↗

NASA NTRS1977

Modeling the complete Otto cycle: Preliminary version

A description is given of the equations and the computer program being developed to model the complete Otto cycle. The program incorporates such important features as: (1) heat transfer, (2) finite combustion rates, (3) complete chemical kinetics in the burned gas, (4) exhaust gas recirculation, and (5) manifold vacuum or supercharging. Changes in thermodynamic, kinetic and transport data as well as model parameters can be made without reprogramming. Preliminary calculations indicate that: (1) chemistry and heat transfer significantly affect composition and performance, (2) there seems to be a strong interaction among model parameters, and (3) a number of cycles must be calculated in order to obtain steady-state conditions.

Zeleznik, F. J.↗

NASA NTRS1977

Modeling the complete Otto cycle - Preliminary version

Zeleznik, F. J.↗

NASA NTRS1982

Plasmaspheric helium ion distribution from satellite observations of He II 304-A

High sensitivity and spatial resolution observations of the He II 304-A emission line intensity in the earth's nightglow have been carried out by the extreme ultraviolet telescope on the Apollo-Soyuz mission in July, 1975. The data, obtained over a wide range of plasmasphere parameters, are compared to the predictions of a kinetic equilibrium model of plasmaspheric ion density. Excellent agreement between observation and theory is found using as inputs a temperature model, solar flux and H(+) and O(+) number densities determined by extrapolating nearly simultaneous Atmospheric Explorer C measurements at 300 km. The observations in the Northern Hemisphere are well fit by a model having 285 He(+) ions/cu cm at 500 km independent of latitude or longitude, while those in the south require 430 He(+) ions/cu cm at the same altitude. This result is consistent with available information on the interhemispheric asymmetry of He(+) observed by a mass spectrometer on Explorer 32 and on the winter neutral helium bulge.

Chakrabarti, S.↗

NASA NTRS1989

External control of the Saturn kilometric radiation by the solar wind - Comparison between Voyager 1 and 2 observations

The long-term modulation of Saturn's nonthermal radio emission in the kilometric wavelength range has been studied based upon data obtained by Voyagers 1 and 2. A comparison of the ballistic and hydrodynamic propagation of solar wind features from the spacecraft to Saturn allows the uncertainty inherent in the projection to be determined. The results confirm the previous suggestion that momentum, ram pressure, and kinetic energy flux are the primary solar wind parameters that drive the nonthermal radio emission. It is suggested that, under certain conditions and for limited periods of time, the magnetic properties and time derivatives of the solar wind have increased importance.

Rucker, H. O.↗

NASA NTRS1994

Ionospheric projections of magnetospheric regions under low and high solar wind pressure conditions

The projection of magnetospheric regions into the dayside ionosphere as determined by particle precipitation characteristics was studied for dependence on solar wind parameters. It was found that the solar wind kinetic pressure p dramatically affected the map of magnetospheric projections. Under the constraint that p greater than or equal 4 nPa(yielding (p) = 5.9 nPa), the area of the cusp (magnetic latitude times magnetic local time extent) was 4.83 degree-hours; whereas under the constraint that p greater than or equal 2 nPa (yielding (p) = 1.5 nPa), the cusp area was only 1.01 degree-hours. The ionospheric footprint of the low-latitude boundary layer was similarly affected. Various possible correlations of p with other solar wind variables, including n, v, and absolute value of B(sub z), proved unable to account for the pressure effect. Because one criterion for identifying the cusp is high fluxes, the effect of nv was investigated with particular care, both in examples and statistically. Again, p itself had by far the most striking effect. Thus we concluded that some physical mechanism is needed to account for the pressure effect. One possibility is that increased direct solar wind plasma penetration of the magnetopause occurs under high-p conditions in the manner suggested by various proponents of impulsive penetration models. An alternative, which we find promising, is that, regardless of the original interplanetary magnetic field (IMF) strength, a high-p solar wind leads to a large compression factor for the magnetosheath field, which is the field actually in contact with the magnetosphere. From this latter viewpoint, the chief effect of high particle pressure is simply to enhance the effectiveness of the interaction of the IMF with the magnetosphere.

Newell, Patrick T.↗

NASA NTRS2005

Partially-Averaged Navier Stokes Model for Turbulence: Implementation and Validation

Partially-averaged Navier Stokes (PANS) is a suite of turbulence closure models of various modeled-to-resolved scale ratios ranging from Reynolds-averaged Navier Stokes (RANS) to Navier-Stokes (direct numerical simulations). The objective of PANS, like hybrid models, is to resolve large scale structures at reasonable computational expense. The modeled-to-resolved scale ratio or the level of physical resolution in PANS is quantified by two parameters: the unresolved-to-total ratios of kinetic energy (f(sub k)) and dissipation (f(sub epsilon)). The unresolved-scale stress is modeled with the Boussinesq approximation and modeled transport equations are solved for the unresolved kinetic energy and dissipation. In this paper, we first present a brief discussion of the PANS philosophy followed by a description of the implementation procedure and finally perform preliminary evaluation in benchmark problems.

Girimaji, Sharath S.↗

NASA NTRS2007

Multi-Scale Modeling of Magnetospheric Reconnection

One of the major challenges in modeling the magnetospheric magnetic reconnection is to quantify the interaction between large-scale global magnetospheric dynamics and microphysical processes in diffusion regions near reconnection sites. There is still considerable debate as to what degree microphysical processes on kinetic scales affect the global evolution and how important it is to substitute numerical dissipation and/or ad hoc anomalous resistivity by a physically motivated model of dissipation. Comparative studies of magnetic reconnection in small scale geometries demonstrated that MHD simulations that included non-ideal processes in terms of a resistive term $\eta J$ did not produce the fast reconnection rates observed in kinetic simulations. For a broad range of physical parameters in collisionless magnetospheric plasma, the primary mechanism controlling the dissipation in the vicinity of the reconnection site is non-gyrotropic effects with spatial scales comparable with the particle Larmor radius. We utilize the global MHD code BATSRUS and incorporate nongyrotropic effects in diffusion regions in terms of corrections to the induction equation. We developed an algorithm to search for magnetotail reconnection sites, specifically where the magnetic field components perpendicular to the local current direction approaches zero and form an X-type configuration. Spatial scales of the diffusion region and magnitude of the reconnection electric field are calculated selfconsistently using MHD plasma and field parameters in the vicinity of the reconnection site. The location of the reconnection sites is updated during the simulations. To clarify the role of nongyrotropic effects in diffusion region on the global magnetospheric dynamic we perform simulations with steady southward IMF driving of the magnetosphere. Ideal MHD simulations with magnetic reconnection supported by numerical resistivity produce steady configuration with almost stationary near-earth neutral line (NENL). Simulations with non-gyrotropic corrections demonstrate dynamic quasi-periodic response to the steady driving condition. The loading/unloading cycle in non-gyrotropic MHD results has a non-stationary reconnection site in the magnetotail, with the retreating during the stretching phase and then a new NENL forming in the resulting thin plasma sheet. We expect that this model will lead to improved representations of space weather event in the magnetosphere.

Kuznetsova, M. M.↗

NASA NTRS1978

A study of the atmospheric energetics of a six-layer operational forecast model

Verification data for twice-daily analyses of horizontal wind and temperature are compared with 00, 12, 24, 36, 60, and 84 hour forecasts prepared for winter 1975-76 from a six-layer operational forecast model; the comparison focuses on certain energy components in the forecast fields. Significant losses (15 to 20%) of zonal available potential energy and zonal kinetic energy appear beyond the 36-hour forecasts; the zonal kinetic energy loss is associated with a large increase in this parameter during the first 12-hour forecast period, due to a downward and northward movement of the mean jet-stream core. In addition, energy losses in the eddy potential and kinetic energy components are noted in the initialization procedure.

Hauser, R. K.↗

DOE OSTI2015

Image-derived and arterial blood sampled input functions for quantitative PET imaging of the angiotensin II subtype 1 receptor in the kidney

Purpose: The radioligand {sup 11}C-KR31173 has been introduced for positron emission tomography (PET) imaging of the angiotensin II subtype 1 receptor in the kidney in vivo. To study the biokinetics of {sup 11}C-KR31173 with a compartmental model, the input function is needed. Collection and analysis of arterial blood samples are the established approach to obtain the input function but they are not feasible in patients with renal diseases. The goal of this study was to develop a quantitative technique that can provide an accurate image-derived input function (ID-IF) to replace the conventional invasive arterial sampling and test the method in pigs with the goal of translation into human studies. Methods: The experimental animals were injected with [{sup 11}C]KR31173 and scanned up to 90 min with dynamic PET. Arterial blood samples were collected for the artery derived input function (AD-IF) and used as a gold standard for ID-IF. Before PET, magnetic resonance angiography of the kidneys was obtained to provide the anatomical information required for derivation of the recovery coefficients in the abdominal aorta, a requirement for partial volume correction of the ID-IF. Different image reconstruction methods, filtered back projection (FBP) and ordered subset expectation maximization (OS-EM), were investigated for the best trade-off between bias and variance of the ID-IF. The effects of kidney uptakes on the quantitative accuracy of ID-IF were also studied. Biological variables such as red blood cell binding and radioligand metabolism were also taken into consideration. A single blood sample was used for calibration in the later phase of the input function. Results: In the first 2 min after injection, the OS-EM based ID-IF was found to be biased, and the bias was found to be induced by the kidney uptake. No such bias was found with the FBP based image reconstruction method. However, the OS-EM based image reconstruction was found to reduce variance in the subsequent phase of the ID-IF. The combined use of FBP and OS-EM resulted in reduced bias and noise. After performing all the necessary corrections, the areas under the curves (AUCs) of the AD-IF were close to that of the AD-IF (average AUC ratio =1 ± 0.08) during the early phase. When applied in a two-tissue-compartmental kinetic model, the average difference between the estimated model parameters from ID-IF and AD-IF was 10% which was within the error of the estimation method. Conclusions: The bias of radioligand concentration in the aorta from the OS-EM image reconstruction is significantly affected by radioligand uptake in the adjacent kidney and cannot be neglected for quantitative evaluation. With careful calibrations and corrections, the ID-IF derived from quantitative dynamic PET images can be used as the input function of the compartmental model to quantify the renal kinetics of {sup 11}C-KR31173 in experimental animals and the authors intend to evaluate this method in future human studies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Data-Driven Tailoring Optimization of Thermoset Polymers Using Ultrasonics and Machine Learning

Thermoset polymers are highly demanded for their structural robustness, thermal stability, and chemical resistance. Tailoring the properties of these polymers for high-performance applications is often preferred to designing brand-new polymers. However, the traditional destructive techniques used to characterize their properties as a function of manufacturing parameters are expensive and time-consuming. A novel non-destructive, data-driven method leveraging ultrasonics and machine learning techniques to tailor the properties of thermosets as a function of the manufacturing parameters is demonstrated. Thermoset epoxy samples with varying curing temperatures (15–40 °C) and curing agent amounts (±40%) were manufactured and tested. Their curing kinetics were monitored by determining the sound speed in the material in real time, while the longitudinal modulus of the samples was determined post-cure. Machine learning models were developed using a k-nearest neighbors algorithm. These models were implemented to predict the curing and final elastic properties using the manufacturing parameters, i.e., stoichiometry and curing temperature, and vice versa. Understanding and modeling how these parameters affect the cure kinetics and final properties will allow for efficient and reliable optimization of thermoset tailoring and manufacturing.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Suppressing the enhancement of stimulated Raman scattering in inhomogeneous plasmas by tuning the modulation frequency of a broadband laser

The stimulated Raman scattering (SRS) instability can inhibit the performance of laser driven inertial confinement fusion (ICF) implosions by scattering light into unwanted directions or by generating hot electrons that preheat the target fuel. In principle, ICF target designs can avoid parameter regimes conducive to large, linear SRS gains. In practice, kinetic inflation—the nonlinear enhancement of SRS due to electron trapping in the excited plasma wave—makes this difficult. Here we show that laser bandwidth in the form of frequency modulation can either decrease or increase the inflationary SRS (iSRS) threshold in inhomogeneous plasmas depending on the maximum chirp of the laser pulse. The threshold, mapped out by a series of particle-in-cell simulations, exhibits a minimum when the frequency change within the pulse cancels the spatial detuning due to density inhomogeneities along the trajectory of the scattered light. In conclusion, by tuning the pump laser parameters away from this minimum, the iSRS threshold can be larger than at zero bandwidth, providing a path to mitigating kinetic inflation in ignition relevant plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Additive friction stir deposition of SS316: Effect of process parameters on microstructure evolution

Solid state nature of additive friction stir deposition (AFSD) additive manufacturing process is very advantageous in terms of defect formation and microstructural refinement in the material. Current study presents the process optimization, microstructural evolution and kinetics of recrystallization for AFSD deposited low stacking fault energy material - SS316. As deposited microstructure shows equiaxed ultra fine grains with an average grain size of ~5.0 ± 0.5 μm. Shear deformation at high temperature during processing leads to the operation of restoration mechanisms. Observation of necklace type microstructure in the as deposited SS316 is attributed to discontinuous dynamic recrystallization during processing. Recrystallization kinetics of the AFSD SS316 is characterized using Johnson-Mehl-Avarami-Kolmogorov (JMAK) model. Deformation – thermal cycling during AFSD process resulted in inconsistent recrystallization kinetics. Variation in strain, strain rate and temperature during processing with processing parameters result in varying microstructure and tool wear. Further, high strength-ductility combination and sustained work hardening in as deposited SS316 appear to arise from transformation and twinning during deformation, leading to the formation of hierarchical twins and martensitic phase after deformation.

36 MATERIALS SCIENCE↗