Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Diffusion coefficient”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

High altitude Venus haze from Pioneer Venus limb scans

High-resolution limb scans of Venus made with the Orbiter Cloud Photopolarimeter aboard Pioneer Venus have been used to observe the high altitude Venus haze and its variation over almost one half a Venusian year. A model for a spherical atmosphere with tangential viewing geometry was used to analyze the observations and derive the haze properties. Values are found for the particle size and refractive index, particle number density and scale height, and eddy diffusion coefficient. Single scattering computations show good agreement with observed intensities for particles smaller than 0.3 micron radius and refractive index less than 1.7, consistent with, but not limited to, concentrated sulfuric acid. Particle scale height in the 0.5 to 2 mbar pressure regions varies between 1 and 3 km over the season, latitude, and local time ranges of the observations. Detached layers of haze are sometimes present. An average particle scale height of 2.2 km at 84 km altitude yields an eddy diffusion coefficient of 130,000 sq cm/sec.

Lane, W. A.↗
NASA NTRS1993

More on the cooling history of angrite LEW 86010

Antarctic angrite LEW 86010 has many chemical and mineralogical characteristics which suggest it is closely related to Angra dos Reis (ADOR). However, these meteorites have had very different thermal histories. Olivines and pyroxenes in ADOR are nearly homogeneous, suggesting very slow cooling or extensive subsolidus equilibration. In contrast, LEW 86010 pyroxenes are extensively zoned in both major and trace elements, while olivines are nearly homogeneous, suggesting that cooling of this sample was slow enough to homogenize olivines, but too fast to homogenize pyroxenes. In an earlier study, we used Ca diffusion gradients associated with exsolution lamellae of kirsh-steinite in LEW 86010 olivines to estimate the cooling rate of this sample. We obtained cooling rates of a few x.01 deg C/yr, corresponding to a burial depth of approximately 10(exp 2) m under solid rock (thermal diffusivity = 0.004 sq cm/s), or approximately m under regolith material (10(exp -5) sq cm/s). Unfortunately, this calculation was very sensitive to the assumed temperature of initial exsolution, which we approximated from the estimated initial olivine bulk Ca content, and also to the extrapolated values for the Ca diffusion coefficient (D sub Ca). This abstract reports new cooling rate estimates obtained using a refined approach that includes the initial temperature of exsolution as one of the fitted parameters. The purpose of our new calculations is (1) to reduce uncertainties in cooling rate due to uncertainties in bulk olivine Ca content and initial exsolution temperature, (2) to investigate the effects of using different values for D sub Ca, and (3) to determine how well constrained the cooling rate is for any particular Ca diffusion coefficient.

Mckay, G.↗
DOE OSTI2024

Low-Temperature Characterization of a Nonaqueous Liquid Electrolyte for Lithium Batteries

Rechargeable batteries exhibit poor performance at low temperatures due to sluggish ion transport through the electrolytic phase. Ion transport is governed by three transport parameters—conductivity, diffusion coefficient, and the cation transference number with respect to the solvent velocity—and the thermodynamic factor. Understanding how these parameters change with temperature is necessary for designing improved electrolytes. In this work, we combine electrochemical techniques with electrophoretic NMR to determine the temperature dependence of these parameters for a liquid electrolyte, LiTFSI salt dissolved in tetraglyme between −20 and 45 °C. At colder temperatures, all species in the electrolyte tend to move more slowly due to increasing viscosity, which translates to a monotonic decrease in conductivity and diffusion coefficient with decreasing temperature. Surprisingly, we find that the field-induced velocity of solvent molecules at a particular salt concentration is a nonmonotonic function of temperature. The cation transference number with respect to the solvent velocity thus exhibits a complex dependence on temperature and salt concentration. The measured thermodynamic and transport properties are used to predict concentration gradients that will form in a lithium-lithium symmetric cell under a constant applied potential as a function of temperature using concentrated solution theory. The calculated steady current at −20 °C is lower than that at 45 °C by roughly two orders of magnitude.

25 ENERGY STORAGE↗
NASA NTRS1977

Solar particle propagation from 1 to 5 AU

The radial variation of the interplanetary propagation of solar cosmic rays is investigated on a grand scale by performing a statistical analysis of charged-particle data obtained by Pioneers 10 and 11 from launch to Jovian encounter (i.e., at distances of 1 to 5 AU). A numerical propagation model is adopted which includes diffusion, convection, and adiabatic deceleration, as well as a variable power-law diffusion coefficient. The study of solar particle events is carried out by analyzing individually each of five key parameters that are uniquely defined in each solar particle event: the time to maximum flux starting from the initial release at the sun, the anisotropy at the time to maximum flux, the flux at that time, the time width of the event at half the flux at the time to maximum, and the decay time. Combined results for the proton energy ranges from 3.4 to 5.2 MeV and 24 to 30 MeV are presented, the average radial diffusion coefficients between 1 and 5 AU are determined for each energy range, and it is found that the combination of a near-impusive injection with a temporally constant spectral index produces a reasonably good fit to the high-energy data but not as good a fit to the low-energy data. Implications of the results obtained are discussed for cosmic-ray propagation theory, solar modulation studies, and interplanetary acceleration of solar particles.

Zwickl, R. D.↗
NASA NTRS1975

Modulation of low-energy cosmic rays

The relation between the diffusion coefficient of cosmic rays in the solar wind and the power spectrum of interplanetary magnetic field fluctuations, established in recent theories, is tested directly for low energy protons (below 80 MeV). In addition, an attempt is made to determine whether the particles are scattered by magnetic field discontinuities or by fluctuations between discontinuities. Predictions of a perturbation solution of the Fokker-Planck equation are compared with observations of the cosmic ray radial gradient. It is found that at energies between 40 and 80 MeV, galactic cosmic ray protons respond to changes in the predicted diffusion coefficients (i.e., the relationship under consideration holds at these low energies). The relation between changes in the proton flux and modulation parameters is best when the contribution of discontinuities is subtracted, which means that scattering is caused by fluctuations between discontinuities. There appears to be no distinct relation between changes in the modulation parameters and changes in the intensity of 20 to 40 MeV protons.

Sari, J. W.↗
DOE OSTI2020

The Role of Demixing and Crystallization Kinetics on the Stability of Non‐Fullerene Organic Solar Cells

Abstract With power conversion efficiency now over 17%, a long operational lifetime is essential for the successful application of organic solar cells. However, most non‐fullerene acceptors can crystallize and destroy devices, yet the fundamental underlying thermodynamic and kinetic aspects of acceptor crystallization have received limited attention. Here, room‐temperature (RT) diffusion coefficients of 3.4 × 10 −23 and 2.0 × 10 −22 are measured for ITIC‐2Cl and ITIC‐2F, two state‐of‐the‐art non‐fullerene acceptors. The low coefficients are enough to provide for kinetic stabilization of the morphology against demixing at RT. Additionally profound differences in crystallization characteristics are discovered between ITIC‐2F and ITIC‐2Cl. The differences as observed by secondary‐ion mass spectrometry, differential scanning calorimetry (DSC), grazing‐incidence wide‐angle X‐ray scattering, and microscopy can be related directly to device degradation and are attributed to the significantly different nucleation and growth rates, with a difference in the growth rate of a factor of 12 at RT. ITIC‐4F and ITIC‐4Cl exhibit similar characteristics. The results reveal the importance of diffusion coefficients and melting enthalpies in controlling the growth rates, and that differences in halogenation can drastically change crystallization kinetics and device stability. It is furthermore delineated how low nucleation density and large growth rates can be inferred from DSC and microscopy experiments which could be used to guide molecular design for stability.

Hu, Huawei↗
DOE OSTI2025

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Magnetic Field Amplification in the Thin X-Ray Rims of SN 1006

Several young supernova remnants, including SN 1006, emit synchrotron X-rays in narrow filaments, hereafter thin rims, along their periphery. The widths of these rims imply 50–100 μG fields in the region immediately behind the shock, far larger than expected for the interstellar medium compressed by unmodified shocks, assuming electron radiative losses limit rim widths. However, magnetic field damping could also produce thin rims. Here we review the literature on rim width calculations, summarizing the case for magnetic field amplification. We extend these calculations to include an arbitrary power-law dependence of the diffusion coefficient on energy, D ∝ Eμ. Loss-limited rim widths should shrink with increasing photon energy, while magnetic-damping models predict widths almost independent of photon energy. We use these results to analyze Chandra observations of SN 1006, in particular the southwest limb. We parameterize the FWHM in terms of energy as FWHM ∝ EmE γ. Filament widths in SN 1006 decrease with energy; mE ∼ −0.3 to −0.8, implying magnetic field amplification by factors of 10–50, above the factor of four expected in strong unmodified shocks. For SN 1006, the rapid shrinkage rules out magnetic damping models. It also favors short mean free paths (small diffusion coefficients) and strong dependence of D on energy (μ ≥ 1).

MAGNETIC FIELD AMPLIFICATION IN THE THIN X-RAY RIM↗
DOE OSTI2024

Complete quasilinear model for the acceleration-driven lower hybrid drift instability and a computational assessment of its validity

A complete quasilinear model is derived for the electrostatic acceleration-driven lower hybrid drift instability in a uniform two-species low-beta plasma in which current is perpendicular to the background magnetic field. The model consists of coupled nonlinear velocity space diffusion equations for the volume-averaged ion and electron distribution functions. Each species' diffusion coefficient depends on a time-evolving spectral density of the electric-field energy per unit volume and a time-evolving dispersion relation. The dispersion relation is expressed analytically in integral form without the use of asymptotic limits and applies to arbitrary distribution functions, so long as they can be expressed as a function of one velocity coordinate, e.g., f⁡(vy) or f⁡(v⊥). The quasilinear model conserves energy and is complete in that it fully describes the evolution of the distribution functions, including resonant and nonresonant particle-wave interactions, while accounting for distribution-function-dependent mixed-complex frequencies. Further, the quasilinear diffusion model is solved numerically and self-consistently using a Crank-Nicolson temporal discretization and a second-order finite-volume velocity-space discretization. Numerical solutions are compared to nonlinear fourth-order accurate continuum kinetic Vlasov-Poisson simulations. Evolution of electric-field energy, growth rates, distribution functions, and diffusion coefficients are shown to be in agreement with Vlasov simulations. The quasilinear model is shown to predict anomalous transport terms, like resistivity and heating, to within a factor of order unity. Discrepancies between the quasilinear model and Vlasov simulations are assessed and attributed primarily to lack of damping in the quasilinear description and to the use of unperturbed-orbit susceptibilities in the linear theory dispersion relation. The results illuminate the predictive accuracy of the quasilinear model, place approximate bounds on its validity, and provide much needed vetting of quasilinear theory's ability to predict the nonlinear state of a microturbulent plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

We developed a new class of physics-informed generative adversarial networks (PI-GANs) to solve forward, inverse, and mixed stochastic problems in a unified manner based on a limited number of scattered measurements. Unlike standard GANs relying solely on data for training, here we encoded into the architecture of GANs the governing physical laws in the form of stochastic differential equations (SDEs) using automatic differentiation. In particular, we applied Wasserstein GANs with gradient penalty (WGAN-GP) for its enhanced stability compared to vanilla GANs. We first tested WGAN-GP in approximating Gaussian processes of different correlation lengths based on data realizations collected from simultaneous reads at sparsely placed sensors. We obtained good approximation of the generated stochastic processes to the target ones even if there is a mismatch between the input noise dimensionality and the effective dimensionality of the target stochastic processes. We also studied the overfitting issue for both the discriminator and the generator, and we found that overfitting occurs also in the generator in addition to the discriminator as previously reported. Subsequently, we considered the solution of elliptic SDEs requiring approximations of three stochastic processes, namely the solution, the forcing, and the diffusion coefficient. Here again, we assumed data collected from simultaneous reads at a limited number of sensors for the multiple stochastic processes. Furthermore, three generators were used for the PI-GANs: two of them were feed forward deep neural networks (DNNs), while the other one was the neural network induced by the SDE. For the case where we have one group of data, we employed one feed forward DNN as the discriminator, while for the case of multiple groups of data we employed multiple discriminators in PI-GANs. We solved forward, inverse, and mixed problems without changing the framework of PI-GANs, obtaining both the means and the standard deviations of the stochastic solution and the diffusion coefficient in good agreement with benchmarks. In this work, we have demonstrated the effectiveness of PI-GANs in solving SDEs for about 120 dimensions. In principle, PI-GANs could tackle very high dimensional problems given more sensor data with low-polynomial growth in computational cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Modeling turbulent impurity transport in the SOL of DIII-D with a reduced model

A novel impurity transport model that approximates SOL turbulence as a fluctuating poloidal electric field is shown to be an acceptable replacement for the traditional approach of assigning an arbitrary radial diffusion coefficient to the impurity ions. The model is implemented in the DIVIMP impurity transport code and applied to an L-Mode tungsten divertor experiment on DIII-D. The poloidal electric field is represented as fluctuating between ±1000 V m –1 based on previous measurements. The resulting intermittent v r = E θ × B T transport causes ions to transport both into the core as well as into the far-SOL. Simultaneous agreement with estimates of the W density just inside the separatrix as well as in the far-SOL is obtained (n W ~ 10 14 m –3 and n W ~ 10 12 m –3 , respectively). Prompt re-deposition of the W ions was necessary to obtain agreement (f redep ~ 99%). Here, we conclude that simulating impurity transport using a physics-based approximation for turbulence in the SOL, versus arbitrarily assigning diffusion coefficients, may enable better reactor scale predictions of core impurity contamination.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1984

Use of the Burton-prim-slichter Equation at High Growth Rates

The following must be assumed in order to derive the classic Burton-Prim-Slichter equation for segregation during crystal growth: isobaric, isothermal, isopotential or uncharged species, binary, planar interface, steady state, constant diffusion coefficient in fluid, no diffusion in crystal, no lateral convection within fluid film at interface with complete mixing beyond (stagnant film model), and either density, total concentration or partial molar volumes constant in the fluid phase. In addition, the effective distribution coefficient and the interfacial distribution coefficient must be defined properly. The velocity in the equation is the growth rate times a factor correcting for the difference in volumetric properties between crystal and fluid. The stagnant film thickness is found to be a function of freezing rate, with the precise functionality depending on the type of stirring occurring in the growth fluid.

Wilcox, W. R.↗
DOE OSTI2021

Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture

Abstract Recently, machine learning (ML) has been used to address the computational cost that has been limiting ab initio molecular dynamics (AIMD). Here, we present GNNFF, a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant, but rotationally-covariant to the coordinate of the atoms. We demonstrate that GNNFF not only achieves high performance in terms of force prediction accuracy and computational speed on various materials systems, but also accurately predicts the forces of a large MD system after being trained on forces obtained from a smaller system. Finally, we use our framework to perform an MD simulation of Li 7 P 3 S 11 , a superionic conductor, and show that resulting Li diffusion coefficient is within 14% of that obtained directly from AIMD. The high performance exhibited by GNNFF can be easily generalized to study atomistic level dynamics of other material systems.

Chemistry↗
NASA NTRS1987

Vertical constituent transport in the mesosphere

Ground-based microwave spectroscopy measurements of mesospheric CO and H2O vertical mixing ratio profiles are used to infer vertical mixing rates in the upper mesosphere. The CO and H2O data consistently imply vertical eddy diffusion coefficients in the 70- to 85-km region of 100,000-200,000 sq cm/s during spring through summer at midlatidues. Although chemical acceleration of vertical transport is substantial for O and O3, below the mesopause, the divergences of their associated fluxes are modest, with at most a factor of 2 effect on the concentrations of O and O3 for measured variability in gravity wave activity. Comparison of Solar Mesosphere Explorer (SME) O3 data with model results reinforces the conclusions of slow vertical mixing in the upper mesosphere as a consequence of the reduced HO(x) catalytic loss of odd oxygen. The changes in chemical rate constants recommended by Rusch and Eckman (1985), in conjunction with slow vertical mixing, yield good agreement with SME O3 data. The slow vertical mixing deduced in this study is consistent with upper limits obtained from studies of the mesospheric heat budget and could be construed as evidence for an advectively controlled mesosphere. A comparison of the vertical eddy diffusion coefficients for momentum stresses, constituent transport, and heat transport suggests that the eddy Prandtl number must be of order 10.

Strobel, Darrell F.↗
NASA NTRS1999

The Atmospheric Effects of HSCT Emissions Simulated by a 3-Wave Interactive Model

An interactive model which couples a semi-spectral dynamical model, a radiative transfer code and a two-dimensional chemistry transport model (2-D CTM), is used to assess the atmospheric effects of the High-Speed Civil Transport (HSCT) engine emissions. The residual mean meridional circulation, the zonal-mean temperature and the eddy diffusion coefficients are calculated using zonal means and three longest zonal waves of dynamical variables integrated in the semi-spectral dynamical model. They are used in the 2-D CTM to simulate the distribution of trace gases in the atmosphere. The simulated ozone is sent to the radiative transfer code to calculate the heating rates, which drive the dynamics. This radiative coupling connects the dynamical and photochemical processes and creates feedback when the atmosphere is perturbed. It is found that in most areas the ozone depletion caused by HSCT emissions calculated using the 3-wave model has the features similar to, but with significantly larger magnitude than that calculated by the AER 2-D CTM with prescribed transport parameters and temperature. The difference is mostly due to the differences in the circulation in the two models. The radiative feedback effects are investigated by comparing the ozone depletion calculated with the baseline dynamics and with the dynamics perturbed by the HSCT emissions. The feedback through changes in the residual mean meridional circulation and the eddy diffusion coefficients has moderate effects on the simulated ozone depletion. It reduced the ozone depletion by 20-30% in northern mid and high-latitudes. However, the feedback through changes in the zonal- mean temperature is negligible.

Shia, R.-L.↗
DOE OSTI2021

Electrochemical Study on the Kinetic Properties of Fe 2+ /Fe, Ni 2+ /Ni, Cr 2+ /Cr and Cr 3+ /Cr 2+ in Molten MgCl 2 -KCl-NaCl Salts

Here, the fundamental kinetic parameters of corrosion product ions (Fe, Ni and Cr ions) are of significant importance to understand the corrosion mechanisms of the structural materials in the molten salts. In the present study, the fundamental data of Fe 2+ , Ni 2+ , Cr 2+ and Cr 3+ (diffusion coefficient D, exchange current density i 0 , charge transfer coefficient α, limiting current density i L and standard rate constant k0) were measured at different concentrations (1.53 × 10 –6 –7.48 × 10 –4 mol cm –3 ) and temperatures (600 °C–800 °C). The values of D are independent of concentrations and follow Arrhenius law with temperature, which descend in the order of D Cr 2+ > D Fe 2+ > D Cr 3+ > D Ni 2+ with values ranging from 0.94 × 10 –5 to 3.31 × 10 –5 cm 2 s –1 . Both i 0 and k 0 depend on the temperatures, which also follow Arrhenius law.

14 SOLAR ENERGY↗
DOE OSTI2021

Particle Size Distribution Dynamics Can Help Constrain the Phase State of Secondary Organic Aerosol

Particle phase state is a property of atmospheric aerosols that has important implications for the formation, evolution, and gas/particle partitioning of secondary organic aerosol (SOA). In this work, we use a size-resolved chemistry and microphysics model (SOM-TOMAS), updated to include an explicit treatment of particle phase state, to constrain the bulk diffusion coefficient (Db) of SOA produced from ??- pinene ozonolysis. By leveraging data from laboratory experiments performed in the absence of a seed and under dry conditions, we find that the Db for SOA can be constrained (1-7 ×10-15 cm2 s-1 in these experiments) by simultaneously reproducing the time-varying SOA mass concentrations and the evolution of the particle size distribution. Another version of our model that used the predicted SOA composition to calculate the glass transition temperature, viscosity, and, ultimately, Db (~10-15 cm2 s-1) of the SOA was able to reproduce the mass and size distribution measurements when we included oligomer formation (oligomers accounted for about a fifth of the SOA mass). Our work highlights the potential of a size resolved SOA model to constrain the particle phase state of SOA by utilizing historical measurements of the evolution of the particle size distribution.

He, Yicong↗
DOE OSTI2025

MOSCATO Development and Integration in Fiscal Year 2025: Implementation of Multiphase, Multiphysics Modeling Capabilities for Molten Salt Systems

MOSCATO (Molten Salt Chemistry and Transport) is a multiphysics code that provides high-fidelity, coupled simulations of fluid flow, heat transfer, mass transfer, chemistry, electrochemical phenomena, and alloy corrosion for molten salt systems. In FY25, significant developments were made to the code package, enhancing its capabilities for modeling all relevant phenomena within operating moltens salt reactors (MSRs). The developments and activities in FY25 included: 1. Implementation of Level-Set methods to enable modeling of single-bubble behavior in molten salts. In FY25, the Level-Set two-phase flow modeling implementation was improved to simulate single bubble behavior with molten salt media. The large density and viscosity ratios between typical gases and molten salt liquids present challenges for these types of numerical solvers. With enhancements to the pressure projection method, MOSCATO’s Level-Set solver was able to be successfully validated to experiments related to helium bubble rise in stagnant molten salt. The simulated bubble rising velocity showed reasonable good agreement with experimental measurements. The bubble shape and dynamics were also visually compared with experimental snapshots, demonstrating a good qualitative match. 2. Generation of mass transfer correlations for multiphase flow systems. To enable calculations of the tritium transport across the interface between gas bubbles and salt, we modeled high- Schmidt-number mass transfer around a sphere across a broad range of Reynolds numbers. The mesh near the sphere surface was highly refined to resolve steep concentration gradients caused by the low diffusion coefficient. Literature-based mass transfer correlations were compared with the numerical results, and modifications were proposed to improve agreement, particularly at higher Schmidt numbers. These mass transfer correlations were subsequently provided to other national laboratories to help enable high quality mass transfer simulations using lower-order solvers under development within the NEAMS program. 3. Preliminary implementation of a bubbly flow solver. To model bubbly flow in molten salt, we implemented a bubbly flow solver for void fractions less than 5%. To do so, an algebraic relative velocity model that assumes small bubbles with rapid momentum equilibration was added to MOSCATO to compute bubble velocities. Preliminary comparisons with experimental data showed reasonable agreement, and further improvements are underway. 4. Generation of mass transfer correlations for MSRE subchannel The Molten-Salt Reactor Experiment (MSRE) was a landmark historical project that demonstrated the feasibility of molten-salt reactor technology. The MSRE campaign also generated a significant body of experimental data and reports that continue to support molten-salt–related research. In this report, the MSRE core subchannel was used as the reference geometry for a mass transfer study performed with MOSCATO. The geometry and computational mesh were adapted from a previous study, providing adequate resolution for the relatively low Reynolds number in this case. Additional mesh refinement was applied to reach higher Schmidt numbers, enabling the derivation of a reliable mass-transfer correlation for the present scenario. 5. Simulations of oxygen ingressions into molten salt. In the previous fiscal year, we initiated a study to simulate oxygen ingression in stagnant salt. As oxygen enters the salt through its surface, it reacts with Ce 3+ to form solid CeO 2 and other reaction products. To more fully capture the complex diffusion-convection-reaction mechanisms, capabilities for modeling natural convection in the salt vessel were added. These were needed as the flow of the ingressed gas induced flow in the salt caused by surface shear and non-isothermal effects. With these updated physics in place, we were able to successfully reproduce the experimental results for the rate of change of CeCl 3 concentrations versus time. 6. Flow corrosion model validation. In FY24, MOSCATO’s corrosion model was validated against static corrosion experiments. In FY25, this work was extended to a flow corrosion experiment, where FLiNaK salt was driven by natural convection, with initial salt impurities to initiate corrosion. Despite uncertainties in parameters such as elemental diffusion coefficients in the alloy and unknown H + concentrations, the simulations achieved good agreement with experimental results, especially in predicting sample mass losses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗