Correlation Models of Radioactive Particle Deposition in Ventilation Ducts in Nonreactor Nuclear Facilities
Explore the source record for details and available documents.
SEARCH · Engineering Papers
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.
Explore the source record for details and available documents.
Since the development of probe theory by Langmuir and Blodgett, the problem of current collection by a charged spherically or cylindrically symmetric body has been investigated by a number of authors. This paper overviews the development of a fully three-dimensional particle simulation code which can be used to understand the physics of current collection in three dimensions and can be used to analyze data resulting from the future tethered satellite system (TSS). According to the TSS configurations, two types of particle simulation models were constructed: a simple particle simulation (SIPS) and a super particle simulation (SUPS). The models study the electron transient response and its asymptotic behavior around a three dimensional, highly biased satellite. The potential distribution surrounding the satellite is determined by solving Laplace's equation in the SIPS model and by solving Poisson's equation in the SUPS model. Thus, the potential distribution in space is independent of the density distribution of the particles in the SUPS model but it does depend on the density distribution of the particles in the SUPS model. The evolution of the potential distribution in the SUPS model is described. When the spherical satellite is charged to a highly positive potential and immersed in a plasma with a uniform magnetic field, the formation of an electron torus in the equatorial plane (the plane in perpendicular to the magnetic field) and elongation of the torus along the magnetic field are found in both the SIPS and the SUPS models but the shape of the torus is different. The areas of high potential that exist in the polar regions in the SUPS model exaggerate the elongation of the electron torus along the magnetic field. The current collected by the satellite for different magentic field strengths is investigated in both models. Due to the nonlinear effects present in SUPS, the oscillating phenomenon of the current collection curve during the first 10 plasma periods can be seen (this does not appear in SIPS). From the parametric studies, it appears that the oscillating phenomenon of the current collection curve occurs only when the magnetic field strength is less than 0.2 gauss for the present model.
We review theories of dark matter (DM) beyond the collisionless paradigm, known as self-interacting dark matter (SIDM), and their observable implications for astrophysical structure in the Universe. Self-interactions are motivated, in part, due to the potential to explain long-standing (and more recent) small scale structure observations that are in tension with collisionless cold DM (CDM) predictions. Simple particle physics models for SIDM can provide a universal explanation for these observations across a wide range of mass scales spanning dwarf galaxies, low and high surface brightness spiral galaxies, and clusters of galaxies. At the same time, SIDM leaves intact the success of $Λ$CDM cosmology on large scales. This report covers the following topics: (1) small scale structure issues, including the core–cusp problem, the diversity problem for rotation curves, the missing satellites problem, and the too-big-to-fail problem, as well as recent progress in hydrodynamical simulations of galaxy formation; (2) N-body simulations for SIDM, including implications for density profiles, halo shapes, substructure, and the interplay between baryons and self-interactions; (3) semi-analytic Jeans-based methods that provide a complementary approach for connecting particle models with observations; (4) merging systems, such as cluster mergers (e.g., the Bullet Cluster) and minor infalls, along with recent simulation results for mergers; (5) particle physics models, including light mediator models and composite DM models; and (6) complementary probes for SIDM, including indirect and direct detection experiments, particle collider searches, and cosmological observations. In conclusion, we provide a summary and critical look for all current constraints on DM self-interactions and an outline for future directions.
Abstract We compare the dynamical behavior of magnetic skyrmions interacting with square and triangular defect arrays just above commensuration using both atomistic and particle-based models. Under applied drives, the initial motion is a kink traveling through the pinned skyrmion lattice. For the square defect array, both models agree well and show a regime in which the soliton motion is locked along 45°. The atomistic model also produces locking of a soliton along 30°, which is absent in the particle-based model. For the triangular defect array, the atomistic model exhibits 30° soliton motion over a wide region of external current values. In contrast, the particle-based model gives 45° soliton motion over a small range of external driving force values. The difference arises because the nondeforming particle model facilitates meandering skyrmion orbits while the deformable atomistic model enables stronger skyrmion-skyrmion interactions that reduce the meandering. Our results indicate that soliton motion through pinned skyrmion lattices on a periodic substrate is a robust effect.
Unprecedented climate change and anthropogenic activities have induced increasing ecohydrological problems, which have motivated the development of large-scale modeling for solutions. Water age/quality is as important as water quantity for understanding the water cycle. However, current scientific progress in tracking water parcels at large-scale with high spatiotemporal resolutions is far behind that in water balance/quantity owing to the lack of powerful tools. EcoSLIM is a particle tracking model that works with the hydrologic model ParFlow-CLM, which couples surface-subsurface hydrology with land surface processes. Here, we demonstrate a parallel framework to accelerate EcoSLIM to continental-scale on a distributed, multi-GPU platform with CUDA-Aware MPI. In tests from catchment-, to regional-, and then to continental-scale using 25-million to 1.6-billion particles, EcoSLIM shows significant speedup and excellent parallel performance. The parallel framework is portable to atmospheric and oceanic particle tracking models, where parallelization is inadequate and a standard parallel framework is absent. Parallelized EcoSLIM is a promising tool to accelerate our understanding of the terrestrial water cycle and the upscaling of subsurface hydrology to Earth system models.
Neutrinos exist in one of three types or ‘flavours’—electron, muon and tau neutrinos—and oscillate from one flavour to another when propagating through space. This phenomena is one of the few that cannot be described using the standard model of particle physics (reviewed in ref. 1), and so its experimental study can provide new insight into the nature of our Universe (reviewed in ref. 2). Neutrinos oscillate as a function of their propagation distance (L) divided by their energy (E). Therefore, experiments extract oscillation parameters by measuring their energy distribution at different locations. As accelerator-based oscillation experiments cannot directly measure E, the interpretation of these experiments relies heavily on phenomenological models of neutrino–nucleus interactions to infer E. Here we exploit the similarity of electron–nucleus and neutrino–nucleus interactions, and use electron scattering data with known beam energies to test energy reconstruction methods and interaction models. We find that even in simple interactions where no pions are detected, only a small fraction of events reconstruct to the correct incident energy. More importantly, widely used interaction models reproduce the reconstructed energy distribution only qualitatively and the quality of the reproduction varies strongly with beam energy. This shows both the need and the pathway to improve current models to meet the requirements of next-generation, high-precision experiments such as Hyper-Kamiokande (Japan) and DUNE (USA).
Some recent analyses of single-spin and azimuthal asymmetries in SIDIS and Drell-Yan processes, focusing in particular on Collins, Sivers and Boer-Mulders effects, are briefly reviewed. The perspectives for future phenomenological studies are also outlined.
Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predict turbulent transport of passive scalars are based on the Lagrangian stochastic dispersion model. The Quick Environmental Simulation (QES) tool is a low-computational-cost framework developed to provide high-resolution wind and concentration fields in a variety of complex atmospheric-boundary-layer environments. Part of the framework, QES-Plume, is a Lagrangian dispersion code that uses a time-implicit integration scheme to solve the generalized Langevin equations which require mean flow and turbulence fields. Here, QES-Plume is driven by QES-Winds, a 3D fast-response model that computes mass-consistent wind fields around buildings, vegetation, and hills using empirical parameterizations, and QES-Turb, a local-mixing-length turbulence model. In this paper, the particle dispersion model is presented and validated against analytical solutions to examine QES-Plume’s performance under idealized conditions. In particular, QES-Plume is evaluated against a classical Gaussian plume model for an elevated continuous point-source release in uniform flow, the Lagrangian scaling of dispersion in isotropic turbulence, and a non-Gaussian plume model for an elevated continuous point-source release in a power-law boundary-layer flow. In these cases, QES-Plume yields a maximum relative error below 6 % when compared with analytical solutions. In addition, the model is tested against wind-tunnel data for a uniform array of cubical buildings. QES-Plume exhibits good agreement with the experiment with 99 % of matched zeros and 59 % of the predicted concentrations falling within a factor of 2 of the experimental concentrations. Furthermore, results also emphasize the importance of using high-quality turbulence models for particle dispersion in complex environments. Finally, QES-Plume demonstrates excellent computational performance.
Landing vehicle propulsive systems introduce several risks associated with plume/surface interactions (PSI) during the final stages of descent. For example, view obscuration during descent due to the liberation of dust driven by the rocket plume’s interaction with the lunar surface was reported on several Apollo missions. Plume-driven debris impacts on vehicle and nearby assets as well as landing instabilities due to crater formation are also potential risks associated with plume/surface interactions. The importance of studying these plume/surface interactions has been elevated due to NASA’s mission to land humans on the Moon by 2024. Existing and under-development predictive simulation tools are currently being brought to application readiness under a project awarded by the NASA Space Technology Mission Directorate (STMD) Game Changing Development (GCD) program. This tool development is divided into four tasks: (1) simulating plume structure in low-pressure environments, (2) simulating crater development and ejecta, (3) regolith particle phase modeling, and (4) gas-particle interaction modeling. Recent efforts under task 1 include demonstrating existing computational fluid dynamics (CFD) tools for simulating plume structure in low pressure environments similar to those found on Mars. The results of these demonstrative simulations are compared to available experimental data. Emerging capability being developed under task 2 is also presented, demonstrating simulations of crater formation in Lunar conditions.
Aerosol effects on climate, weather, and air quality depend on characteristics of individual particles, which are tremendously diverse and change in time. Particle-resolved models are the only models able to capture this diversity in particle physiochemical properties, and these models are computationally expensive. As a strategy for accelerating particle-resolved microphysics models, we introduce Graph-based Learning of Aerosol Dynamics (GLAD) and use this model to train a surrogate of the particle-resolved model PartMC-MOSAIC. GLAD implements a Graph Network-based Simulator (GNS), a machine learning framework that has been used to simulate particle-based fluid dynamics models. In GLAD, each particle is represented as a node in a graph, and the evolution of the particle population over time is simulated through learned message passing. Here, we demonstrate our GNS approach on a simple aerosol system that includes condensation of sulfuric acid onto particles composed of sulfate, black carbon, organic carbon, and water. A graph with particles as nodes is constructed, and a graph neural network (GNN) is then trained using the model output from PartMC-MOSAIC. The trained GNN can then be used for simulating and predicting aerosol dynamics over time. Results demonstrate the framework's ability to accurately learn chemical dynamics and generalize across different scenarios, achieving efficient training and prediction times. We evaluate the performance across four scenarios, highlighting the framework's robustness and adaptability in modeling aerosol microphysics and chemistry.
Methods and lessons learned in developing GUI-enabled radiative modeling suite for particle-based simulations including accelerated MCRT, distribution factor surrogate-models, and volumetric participating media
We discuss model building in tribrid inflation, which is a framework for realising inflation in the matter sector of supersymmetric particle physics models. The inflaton is a D-flat combination of matter fields, and inflation ends by a phase transition in which some Higgs field obtains a vacuum expectation value. We first describe the general procedure for implementing tribrid inflation in realistic models of particle physics that can be applied to a wide variety of BSM particle physics models around the GUT scale. We then demonstrate how the procedure works for an explicit lepton flavour model based on an A{sub 4} family symmetry. The model is both predictive and phenomenologically viable, and illustrates how tribrid inflation connects cosmological and particle physics parameters. In particular, it predicts a relation between the neutrino Yukawa coupling and the running of the spectral index α{sub s}. We also show how topological defects from the flavour symmetry breaking can be avoided automatically.
The peridynamic theory of solid mechanics is applied to modeling the deformation and fracture of micrometer-sized particles made of organic crystalline material. A new peridynamic material model is proposed to reproduce the elastic–plastic response, creep, and fracture that are observed in experiments. The model is implemented in a three-dimensional, meshless Lagrangian simulation code. In the small deformation, elastic regime, the model agrees well with classical Hertzian contact analysis for a sphere compressed between rigid plates. Under higher load, material and geometrical nonlinearity is predicted, leading to fracture. Finally, the material parameters for the energetic material CL-20 are evaluated from nanoindentation test data on the cyclic compression and failure of micrometer-sized grains.
This report fulfills the M3 milestones M3SF-21PN010207025 & M3SF-20PN0102070412. During fiscal year (FY) 2020, Pacific Northwest National Laboratory (PNNL) worked to further develop the FY 2019 deposition and particle tracking models. This status report outlines these efforts and presents the progress made so far. Model development work is ongoing and is planned to continue in FY 2021. The FY 2020 model development included work on: Wind Effects. Model development and sensitivity studies, investigated how wind direction and speed affect deposition; Brownian Motion. Implementing Brownian Motion into existing models; Particle Size Variability. Depending on the particle composition, the diameter of the particle may vary with changes in relative humidity. Models were developed to analyze this; Multiphase and Fluid Film Modeling. Investigating canister surface wetting and drying, and how this effects overall deposition. Models were developed to analyze this; Difusophoresis. Performing initial work to implement diffusiophoresis into the existing models; Turbophoresis. Performing initial work to implement turbophoresis into the existing models. Much of this work will continue into FY21. The authors present initial results and discus current and future work.
In this work, we develop a “charged” dissipative particle dynamics (cDPD) model for simulating mesoscopic electrokinetic phenomena governed by the stochastic Poisson-Nernst-Planck and the Navier-Stokes equations. In particular, the transport equations of ionic species are incorporated into the DPD framework by introducing extra degrees of freedom and corresponding evolution equations associated with each DPD particle. Diffusion of ionic species driven by the ionic concentration gradient, electrostatic potential gradient, and thermal fluctuations is captured accurately via pairwise fluxes between DPD particles. The electrostatic potential is obtained by solving the Poisson equation on the moving DPD particles iteratively at each time step. For charged surfaces in bounded systems, an effective boundary treatment methodology is developed for imposing both the correct hydrodynamic and electrokinetics boundary conditions in cDPD simulations. To validate the proposed cDPD model and the corresponding boundary conditions, we first study the electrostatic structure in the vicinity of a charged solid surface, i.e., we perform cDPD simulations of the electrostatic double layer and show that our results are in good agreement with the well-known mean-field theoretical solutions. Furthermore, we simulate the electrostatic structure and capacity densities between charged parallel plates in salt solutions with different salt concentrations. Moreover, we employ the proposed methodology to study the electro-osmotic and electro-osmotic/pressure-driven flows in a micro-channel. In the latter case, we simulate the dilute poly-electrolyte solution drifting by electro-osmotic flow in a micro-channel, hence demonstrating the flexibility and capability of this method in studying complex fluids with electrostatic interactions at the micro- and nano-scales.
Here, a new particle-resolved three dimensional direct numerical simulation (DNS) model is developed that combines Lagrangian droplet tracking with the Eulerian field representation of turbulence near the Kolmogorov microscale. Six numerical experiments are performed to investigate the processes of entrainment of clear air and subsequent mixing with cloudy air and their interactions with cloud microphysics. The experiments are designed to represent different combinations of three configurations of initial cloudy area and two turbulence modes (decaying and forced turbulence). Five existing measures of microphysical homogeneous mixing degree are examined, modified, and compared in terms of their ability as a unifying measure to represent the effect of various entrainment-mixing mechanisms on cloud microphysics. Also examined and compared are the conventional Damköhler number and transition scale number as a dynamical measure of different mixing mechanisms. Relationships between the various microphysical measures and dynamical measures are investigated in search for a unified parameterization of entrainment-mixing processes. The results show that even with the same cloud water fraction, the thermodynamic and microphysical properties are different, especially for the decaying cases. Further analysis confirms that despite the detailed differences in cloud properties among the six simulation scenarios, the variety of turbulent entrainment-mixing mechanisms can be reasonably represented with power-law relationships between the microphysical homogeneous mixing degrees and the dynamical measures.
Multiparameter radar and polarized microwave radiative transfer models for arbitrarily shaped particles are developed. The ice crystals modeled are horizontally oriented hexagonal plates, columns, and needles. The ice water content is fixed at 0.1 g/cu m, and a realistic size distribution is used. The radar modeling is done for S through K-band, and the passive microwave calculations are at 37, 85, and 157 GHz. The modeling results show that particle shape is important for both multiparameter radar and passive microwave radiometry. Radar reflectivity and upwelling microwave brightness temperatures depend strongly on the individual particle volume, which in turn depends on the ice crystal shape. Radar differential reflectivity is high for the plates and lower for needles and columns. Linear depolarization calculations indicate that oblate ice crystals such as plates can be distinguished from prolate crystals such as columns. At 85 and 157 GHz, significant polarization brightness temperature differences are calculated for plates and columns. The particle bulk density strongly affects the radar and radiometer observables. Recent measurements of ice crystals are discussed to show that the model results have practical applicability.
Particle-based hydrodynamics models offer distinct advantages over Eulerian and Lagrangian hydrocodes in particular shock physics applications. Particle models are designed to avoid the mesh distortion and state variable diffusion problems which can hinder the effective use of Lagrangian and Eulerian codes respectively. However conventional particle-in-cell and smooth particle hydrodynamics methods employ particles which are actually moving interpolation points. A new particle-based modeling methodology, termed Hamiltonian particle hydrodynamics, was developed by Fahrenthold and Koo (1997) to provide an alternative, fully Lagrangian, energy-based approach to shock physics simulations. This alternative formulation avoids the tensile and boundary instabilities associated with standard smooth particle hydrodynamics formulations and the diffusive grid- to-particle mapping schemes characteristic of particle-in-cell methods. In the work described herein, the method of Fahrenthold and Koo has been extended, by coupling the aforementioned hydrodynamic particle model to a hexahedral finite element based description of the continuum dynamics. The resulting continuum model retains all of the features (including general contact-impact effects) of Hamiltonian particle hydrodynamics, while in addition accounting for tensile strength, plasticity, and damage effects important in the simulation of hypervelocity impact on orbital debris shielding. A three dimensional, vectorized, and autotasked implementation of the extended particle method described here has been coded for application to orbital debris shielding design. Source code for the pre-processor (PREP), analysis code (EXOS), post-processor (POST), and rezoner (ZONE), have been delivered separately, along with a User's Guide describing installation and application of the software.