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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

GLOBAL MODELING OF NEBULAE WITH PARTICLE GROWTH, DRIFT, AND EVAPORATION FRONTS. I. METHODOLOGY AND TYPICAL RESULTS

We model particle growth in a turbulent, viscously evolving protoplanetary nebula, incorporating sticking, bouncing, fragmentation, and mass transfer at high speeds. We treat small particles using a moments method and large particles using a traditional histogram binning, including a probability distribution function of collisional velocities. The fragmentation strength of the particles depends on their composition (icy aggregates are stronger than silicate aggregates). The particle opacity, which controls the nebula thermal structure, evolves as particles grow and mass redistributes. While growing, particles drift radially due to nebula headwind drag. Particles of different compositions evaporate at “evaporation fronts” (EFs) where the midplane temperature exceeds their respective evaporation temperatures. We track the vapor and solid phases of each component, accounting for advection and radial and vertical diffusion. We present characteristic results in evolutions lasting 2 × 10{sup 5} years. In general, (1) mass is transferred from the outer to the inner nebula in significant amounts, creating radial concentrations of solids at EFs; (2) particle sizes are limited by a combination of fragmentation, bouncing, and drift; (3) “lucky” large particles never represent a significant amount of mass; and (4) restricted radial zones just outside each EF become compositionally enriched in the associated volatiles. We point out implications for millimeter to submillimeter SEDs and the inference of nebula mass, radial banding, the role of opacity on new mechanisms for generating turbulence, the enrichment of meteorites in heavy oxygen isotopes, variable and nonsolar redox conditions, the primary accretion of silicate and icy planetesimals, and the makeup of Jupiter’s core.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Unsupervised Learning Based Interaction Force Model for Nonspherical Particles in Incompressible Flows

This project provides a neural network-based interaction force model for gas-solid flows from low to intermediate Reynolds numbers and concentration, which can be linked to MFiX-DEM. We have constructed a database of the interaction force between the irregular-shaped particles using a spherical harmonic method and the fluid phase based on the particle-resolved direct numerical simulation (PR-DNS) with immersed boundary-based gas kinetic scheme. Unsupervised learning method, i.e., variational auto-encoder (VAE) has been applied to extract the primitive shape factors determining the drag force, lifting forces, and torque. The interaction force model has been trained and validated with a simple but effective multi-layer feed-forward neural network: multi-layer perceptron (MLP), which will be concatenated after the encoder of the previously trained VAE for geometry feature extraction for single, irregular particles. We have trained transpose convolutional neural networks with the PR-DNS data to predict the velocity and pressure gradient of the single particle systems and utilized them to calculate drag force of multi-particle systems. This model can provide high computational efficiency because it does not require collecting multiparticle system data from PR-DNS.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1992

Parallel implementation of a particle simulation for modeling rarefied gas dynamic flow

When the conditions of flow are rarefied and hypersonic, a more suitable alternative to the use of the Navier-Stokes equations for developing a numerical solution is the Direct Simulation Monte Carlo method (DSMC), a method of simulation which employs a large number of particles in modeling a rarefied gas. The performance of a parallel DSMC code developed for the Intel iPSC/860 Touchstone Gamma prototype computer is studied and the scaleup is found to be very nearly over the range of 16-128 processors.

Fallavollita, M. A.↗
DOE OSTI2013

Reduced Quasilinear Models for Energetic Particles Interaction with Alfvenic Eigenmodes

The Line Broadened Quasilinear (LBQ) and the 1.5D reduced models are able to predict the effect of Alfvenic eigenmodes' interaction with energetic particles in burning plasmas. This interaction can result in energetic-particle losses that can damage the first wall, deteriorate the plasma performance, and even prevent ignition. The 1.5D model assumes a broad spectrum of overlapping modes and, based on analytic expressions for the growth and damping rates, calculates the pressure profiles that the energetic particles relax to upon interacting with the modes. 1.5D is validated with DIII-D experiments and predicted neutron losses consistent with observation. The model is employed to predict alpha-particle fusion-product losses in a large-scale operational parameter-space for burning plasmas. \par The LBQ model captures the interaction both in the regime of isolated modes as well as in the conventional regime of overlapping modes. Rules were established that allow quasilinear equations to replicate the expected steady-state saturation levels of isolated modes. The fitting formula is improved and the model is benchmarked with a Vlasov code, BOT. The saturation levels are accurately predicted and the mode evolution is well-replicated in the case of steady-state evolution where the collisions are high enough that coherent structures do not form. When the collisionality is low, oscillatory behavior can occur. LBQ can also exhibit non-steady behavior, but the onset of oscillations occurs for much higher collisional rates in BOT than in LBQ. For certain parameters of low collisionality, hole-clump creation and frequency chirping can occur which are not captured by the LBQ model. Also, there are cases of non-steady evolution without chirping which is possible for LBQ to study. However the results are inconclusive since the periods and amplitudes of the oscillations in the mode evolution are not well-replicated. If multiple modes exist, they can grow to the point of overlap which results in two-dimensional diffusion with cross terms. A diffusion scheme is proposed and validated to resolve this dynamics in (P,E) phase-space.

burning plasmas↗
DOE OSTI2023

A hydride model for solid and liquid cerium ejecta particles

Cerium ejecta particles form after a shock wave impacts a cerium plate with a rough surface or prescribed surface perturbation. When these particles are ejected into hydrogen or deuterium gas the material reacts exothermically and raises the temperature of the particle. Two models are developed to capture the heat and mass transfer that occurs during this process. One model assumes that for larger solid ejecta particles, the loss of mass is negligible while for smaller liquid ejecta particles, the loss of mass during reaction is accounted for. The loss of mass is assumed to occur from the hydride layer being extremely brittle and the fact that it will be relatively easy for the hydride material on the outside of the particle to go into tension, crack and flake off. The model is tested by performing simulations similar to the original experiments that motivated the development of these models and comparing the particle temperatures. While the model is able to capture some general features of the flowfield, inaccuracies clearly exist that must be addressed and the results underscore the need for more isolated experiments where fewer assumptions and physical processes are present simultaneously.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Modeling Deep Burn TRISO Particle Nuclear Fuel

Under the DOE Deep Burn program TRISO fuel is being investigated as a fuel form for consuming plutonium and minor actinides, and for greater efficiency in uranium utilization. The result will thus be to drive TRISO particulate fuel to very high burn-ups. In the current effort the various phenomena in the TRISO particle are being modeled using a variety of techniques. The chemical behavior is being treated utilizing thermochemical analysis to identify phase formation/transformation and chemical activities in the particle, including kernel migration. First principles calculations are being used to investigate the critical issue of fission product palladium attack on the SiC coating layer. Density functional theory is being used to understand fission product diffusion within the plutonia oxide kernel. Kinetic Monte Carlo techniques are shedding light on transport of fission products, most notably silver, through the carbon and SiC coating layers. The diffusion of fission products through an alternative coating layer, ZrC, is being assessed via DFT methods. Finally, a multiscale approach is being used to understand thermal transport, including the effect of radiation damage induced defects, in a model SiC material.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1993

Particle bed reactor modeling

The topics are presented in viewgraph form and include the following: particle bed reactor (PBR) core cross section; PBR bleed cycle; fuel and moderator flow paths; PBR modeling requirements; characteristics of PBR and nuclear thermal propulsion (NTP) modeling; challenges for PBR and NTP modeling; thermal hydraulic computer codes; capabilities for PBR/reactor application; thermal/hydralic codes; limitations; physical correlations; comparison of predicted friction factor and experimental data; frit pressure drop testing; cold frit mask factor; decay heat flow rate; startup transient simulation; and philosophy of systems modeling.

Sapyta, Joe↗
NASA NTRS1984

Structure of the Uranian rings. I - Square-well model and particle-size constraints

A least squares fitting is added to the diffraction model for the Uranian rings and the model is then used to determine the relative optical depths of the rings at visible and near-IR wavelengths. Light transmission is assumed constant on a scale of a few radial km in the rings. The amount of starlight passing through the rings is calculated from occultations with account taken of a monolayer ring, diffraction effects, and multiple ring layers. A diffracted occultation profile is generated with consideration given to the angular diameter of the star, the impulse response of the detector, and atmospheric aberrations. Calculation procedures which remove noise are outlined and results are compared with the observational data base. The wavelength dependence of optical depth is formulated. It is shown that occultation data do not support the presence of a large fraction of submicron particles. No optical depth variations are projected for 0.88-2.2 microns wavelengths. Unchopped data are needed to verify the model predictions.

Elliot, J. L.↗
NASA NTRS2008

Model of Image Artifacts from Dust Particles

A mathematical model of image artifacts produced by dust particles on lenses has been derived. Machine-vision systems often have to work with camera lenses that become dusty during use. Dust particles on the front surface of a lens produce image artifacts that can potentially affect the performance of a machine-vision algorithm. The present model satisfies a need for a means of synthesizing dust image artifacts for testing machine-vision algorithms for robustness (or the lack thereof) in the presence of dust on lenses. A dust particle can absorb light or scatter light out of some pixels, thereby giving rise to a dark dust artifact. It can also scatter light into other pixels, thereby giving rise to a bright dust artifact. For the sake of simplicity, this model deals only with dark dust artifacts. The model effectively represents dark dust artifacts as an attenuation image consisting of an array of diffuse darkened spots centered at image locations corresponding to the locations of dust particles. The dust artifacts are computationally incorporated into a given test image by simply multiplying the brightness value of each pixel by a transmission factor that incorporates the factor of attenuation, by dust particles, of the light incident on that pixel. With respect to computation of the attenuation and transmission factors, the model is based on a first-order geometric (ray)-optics treatment of the shadows cast by dust particles on the image detector. In this model, the light collected by a pixel is deemed to be confined to a pair of cones defined by the location of the pixel s image in object space, the entrance pupil of the lens, and the location of the pixel in the image plane (see Figure 1). For simplicity, it is assumed that the size of a dust particle is somewhat less than the diameter, at the front surface of the lens, of any collection cone containing all or part of that dust particle. Under this assumption, the shape of any individual dust particle artifact is the shape (typically, circular) of the aperture, and the contribution of the particle to the attenuation factor for a given pixel is the fraction of the cross-sectional area of the collection cone occupied by the particle. Assuming that dust particles do not overlap, the net transmission factor for a given pixel is calculated as one minus the sum of attenuation factors contributed by all dust particles affecting that pixel. In a test, the model was used to synthesize attenuation images for random distributions of dust particles on the front surface of a lens at various relative aperture (F-number) settings. As shown in Figure 2, the attenuation images resembled dust artifacts in real test images recorded while the lens was aimed at a white target.

Willson, Reg↗
DOE OSTI2025

Subject-specific modeling framework for particle deposition using computational fluid dynamics

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

AI↗
DOE OSTI2023

Particle-in-cell modeling of electron beam generated plasma

Plasmas generated using energetic electron beams are well known for their low electron temperature (T e ) and plasma potential, which makes them attractive for atomic-precision plasma processing applications such as atomic layer etch and deposition. A 2-dimensional particle-in-cell model for an electron beam-generated plasma in argon confined by a constant applied magnetic field is described here in this article. Plasma production primarily occurs in the path of the beam electrons in the center of the chamber. The resulting plasma spreads out in the chamber through non-ambipolar diffusion with a short-circuiting effect allowing unequal electron and ion fluxes to different regions of the bounding conductive chamber walls. The cross-field transport of the electrons (and thus the steady-state characteristics of the plasma) are strongly impacted by the magnetic field. T e is anisotropic in the electron beam region, but low and isotropic away from the plasma production zone. The plasma density increases and the plasma becomes more confined near the region of production when the magnetic field strengthens. The magnetic field reduces both electron physical and energy transport perpendicular to the magnetic field. T e is uniform along the magnetic field lines and slowly decreases perpendicular to it. Electrons are less energetic in the sheath regions where the sheath electric field repels and confines the low-energy electrons from the bulk plasma. Even though electron and ion densities are similar in the bulk plasma due to quasi-neutrality, electron and ion fluxes on the grounded chamber walls are unequal at most locations. Electron confinement by the magnetic field weakens with increasing pressure, and the plasma spread out farther from the electron beam region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1991

Validation of chemistry models employed in a particle simulation method

The chemistry models employed in a statistical particle simulation method, as implemented in the Intel iPSC/860 multiprocessor computer, are validated and applied. Chemical relaxation of five-species air in these reservoirs involves 34 simultaneous dissociation, recombination, and atomic-exchange reactions. The reaction rates employed in the analytic solutions are obtained from Arrhenius experimental correlations as functions of temperature for adiabatic gas reservoirs in thermal equilibrium. Favorable agreement with the analytic solutions validates the simulation when applied to relaxation of O2 toward equilibrium in reservoirs dominated by dissociation and recombination, respectively, and when applied to relaxation of air in the temperature range 5000 to 30,000 K. A flow of O2 over a circular cylinder at high Mach number is simulated to demonstrate application of the method to multidimensional reactive flows.

Haas, Brian L.↗
DOE OSTI2016

Mathematical modeling of quartz particle melting process in plasma-chemical reactor

Among silica-based materials vitreous silica has a special place. The paper presents the melting process of a quartz particle under conditions of low-temperature plasma. A mathematical model is designed for stages of melting in the experimental plasma-chemical reactor. As calculation data show, quartz particles having the radius of 0.21≤ r{sub p} ≤0.64 mm completely melt at W = 0.65 l/s particle feed rate depending on the Nusselt number, while 0.14≤ r{sub p} ≤0.44 mm particles melt at W = 1.4 l/s. Calculation data showed that 2 mm and 0.4 mm quartz particles completely melted during and 0.1 s respectively. Thus, phase transformations occurred in silicon dioxide play the important part in its heating up to the melting temperature.

42 ENGINEERING↗
DOE OSTI2023

Numerical study of magnetic island coalescence using magnetohydrodynamics with adaptively embedded particle-in-cell model

Collisionless magnetic reconnection typically requires kinetic treatment that is, in general, computationally expensive compared to fluid-based models. In this study, we use the magnetohydrodynamics with an adaptively embedded particle-in-cell (MHD-AEPIC) model to study the interaction of two magnetic flux ropes. This innovative model embeds one or more adaptive PIC regions into a global MHD simulation domain such that the kinetic treatment is only applied in regions where the kinetic physics is prominent. We compare the simulation results among three cases: (1) MHD with adaptively embedded PIC regions, (2) MHD with statically (or fixed) embedded PIC regions, and (3) a full PIC simulation. The comparison yields good agreement when analyzing their reconnection rates and magnetic island separations as well as the ion pressure tensor elements and ion agyrotropy. In order to reach good agreement among the three cases, large adaptive PIC regions are needed within the MHD domain, which indicates that the magnetic island coalescence problem is highly kinetic in nature, where the coupling between the macro-scale MHD and micro-scale kinetic physics is important.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Searching for long-lived particles beyond the Standard Model at the Large Hadron Collider

Particles beyond the Standard Model (SM) can generically have lifetimes that are long compared to SM particles at the weak scale. When produced at experiments such as the Large Hadron Collider (LHC) at CERN, these long-lived particles (LLPs) can decay far from the interaction vertex of the primary proton–proton collision. Such LLP signatures are distinct from those of promptly decaying particles that are targeted by the majority of searches for new physics at the LHC, often requiring customized techniques to identify, for example, significantly displaced decay vertices, tracks with atypical properties, and short track segments. Given their non-standard nature, a comprehensive overview of LLP signatures at the LHC is beneficial to ensure that possible avenues of the discovery of new physics are not overlooked. Here we report on the joint work of a community of theorists and experimentalists with the ATLAS, CMS, and LHCb experiments—as well as those working on dedicated experiments such as MoEDAL, milliQan, MATHUSLA, CODEX-b, and FASER—to survey the current state of LLP searches at the LHC, and to chart a path for the development of LLP searches into the future, both in the upcoming Run 3 and at the high-luminosity LHC. The work is organized around the current and future potential capabilities of LHC experiments to generally discover new LLPs, and takes a signature-based approach to surveying classes of models that give rise to LLPs rather than emphasizing any particular theory motivation. We develop a set of simplified models; assess the coverage of current searches; document known, often unexpected backgrounds; explore the capabilities of proposed detector upgrades; provide recommendations for the presentation of search results; and look towards the newest frontiers, namely high-multiplicity 'dark showers', highlighting opportunities for expanding the LHC reach for these signals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Development of a Grain Boundary Pinning Model that Considers Particle Size Distribution Using the Phase Field Method

Grain boundary (GB) migration significantly impacts material behavior. However, GB migration is slowed or even halted by resistive pressure applied by pores or particles. Zener’s original investigation of particle pinning, and subsequent modifications by other researchers, describe the resistive pressure for various spatial distributions of particles with respect to GBs. In this work, we develop a pinning model that considers the impact of the particle size distribution and we verify it by comparing to mesoscale phase field and Monte Carlo simulations. Resistive pressure expressions are developed that are functions of the percentage of GB area covered by particles and of the particle volume fraction for any spatial distribution of particles. In both expressions, the mean value of the resistive pressure decreases with increasing standard deviation of the particle radius.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Particle-in-cell modeling of gas-confined barrier discharge

Gas-confined barrier discharge is studied using the one-dimensional Particle-in-Cell Monte Carlo Collisions model for the conditions reported by Guerra-Garcia and Martinez-Sanchez [Appl. Phys. Lett. 106, 041601 (2015)]. Depending on the applied voltage, two modes of discharge are observed. In the first mode, the discharge develops in the entire interelectrode gap. In the second mode, the discharge is ignited and develops only in the gas layer having smaller breakdown voltage. The one-dimensional model shows that for the conditions considered, there is no streamer stage of breakdown as is typical for a traditional dielectric barrier discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗