Turbulent fluctuations during pellet injection into a dipole confined plasma torus
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46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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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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Influence of baroclinic vorticity production on unsteady drag coefficient in shock–particle interaction
The influence of baroclinic vorticity production on the unsteady drag coefficient in shock–particle interaction is numerically studied in this work. Numerical simulations are performed for shock–particle interaction utilizing a high–resolution axisymmetric solver for the Euler equations that allows for multi-material interface and shock propagation in both the particle and surrounding medium. We consider an aluminum particle in nitromethane and allow for particle deformation. We compute the vorticity production and unsteady drag coefficient as a function of time to explain the complex physical mechanisms that occur during shock–particle interaction. We observe baroclinic vorticity production as the shock propagates over the particle and find that the vorticity is primarily generated at the surface of the particle. After the passage of the shock over the particle, the generated vortex traverses downstream, thus creating a sharpened particle edge and low pressure on the downstream side of the particle, followed by the trapping of the vortex at the particle edge. These mechanisms lead to the generation of a quasi-steady drag force even after the passage of the shock, thus suggesting the importance of baroclinic vorticity production to the unsteady drag coefficient. Finally, we compute the unsteady drag coefficient for various shock Mach numbers and particle ellipticities.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Investigation of turbulent inflow specification in Euler–Lagrange simulations of mid-field spray
The process of atomization of a liquid jet by a parallel high-speed gas stream results in a spray, whose downstream development is of considerable interest to several applications. The round jet spray can be spatially divided into (i) a near-field (near-nozzle) region of liquid atomization and (ii) a downstream mid-field region of fully-dispersed droplets. In order to accurately model mid-field droplet dispersion, this work aims at developing a rigorous and robust injection model for Euler–Lagrange spray simulations. Results from experiments are used to obtain the relevant droplet number density, size distribution, and mean and standard deviation velocity distributions of the injection model, systematically in a step-by-step process. Two-phase large eddy simulations are performed by stochastically generating the Lagrangian droplets at the inlet of the mid-field region. Number flux, diameter distribution, mean velocity, and other time-averaged statistics at several downstream locations are shown to agree well with the corresponding experimental data.
42 ENGINEERING↗
Principles of aerosol jet printing
Aerosol jet printing (AJP) has emerged as a promising method for microscale digital additive manufacturing using functional nanomaterial inks. While compelling capabilities have been demonstrated in the research community in recent years, the development and refinement of inks and process parameters largely follows empirical observations, with an extensive phase space over which to optimize. While this has led to general qualitative guidelines and ink- and machine-specific correlations, a more fundamental understanding based on principles of aerosol physics and fluid mechanics is lacking. This contrasts with more mature printing technologies, for which foundational physical principles have been rigorously examined. Presented here is a broad framework for describing the AJP process. Simple analytical models are employed to ensure generality and accessibility of the results, while experimental validation using a silver nanoparticle ink supports the physical relevance of the approach. In conclusion, this basic understanding enables a description of process limitations grounded in fundamental principles, as well as guidelines for improved printer design, ink formulation, and print parameter optimization.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
A Lagged Diffusivity Method for Computing Total Variation Regularized Fluid Flow
There is a great deal of recent work using optical flow methods for analyzing the dynamics of fluids, and much attention has been paid to developing regularization schemes for variational approaches that are consistent with the physics of fluid flow. In this work we show that using total variation to regularize two different kinds of optical flow functionals leads to very good flow field reconstructions for the kinds of dynamical structures that appear in fluid flow. The first optical flow functional is the classical component-based conservation of intensity, and the second approach is to reconstruct the potential of the flow, rather than the flow components. In the two cases, total variation regularization corresponds to imposing different scientific priors on the solution, which we compute using a variation of the Lagged Diffusivity Fixed Point Iteration. Numerical details are presented, and the results are demonstrated on synthetic data and on a data-driven oceanic flow model.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Progress on Demonstration of a MOOSE-Based Coupled Capability for Hot Channel Factors in Fast Reactors
Hot channel factors (HCFs) are computed values that account for the impact on predicted peak fuel, cladding, and coolant temperatures due to uncertainties in the as-built reactor’s material properties and geometry as well as uncertainties due to modeling approximations. Reduction in computed HCF values via reduction or elimination of modeling approximations may translate to significant economic savings if the reactor power can be raised due to the extra temperature margin gained. While limited historical datasets exist for sodium-cooled fast reactors (SFRs), there are no available HCF data for lead-cooled fast reactors (LFRs) outside of work generated previously within NEAMS. The computation of HCFs involves insights from reactor physics, thermal fluids and heat conduction calculations to determine how the peak temperatures respond to various uncertainties in the design. Due to the significant advantages for multi-physics coupling offered by the MOOSE framework, Griffin (MOOSE-based reactor physics code), MOOSE Heat Conduction Module, and Cardinal (MOOSE-wrapped multi-physics application which includes the NekRS thermal fluids code) are being coupled together using the MOOSE MultiApp System to develop a highfidelity multi-physics modeling capability for HCF simulations. This high-fidelity coupling workflow may also be beneficial for other fast reactor applications in the future. In previous work, Griffin and NekRS were individually assessed to ensure the necessary capabilities were in place. This work describes initial efforts to couple the codes (including folding in the MOOSE Heat Conduction Module) and determining the workflow for the perturbed calculations which will leverage the Stochastic Tools Module (STM). To our knowledge, this is the first coupling of Griffin and NekRS as well as the first exploratory use of Stochastic Tools Module for Cardinal. In this report, the neutronics code Griffin, the heat conduction solver in MOOSE, and the MOOSE-wrapped application containing NekRS (Cardinal) are linked together to demonstrate the coupled capability. Griffin and Cardinal are linked dynamically by specifying shared libraries. Different coupling hierarchies are tested for selecting the most appropriate coupling strategy. A coupling scheme is selected based on the efficiency of calculation and ease of data communication. Multiple tests are performed to choose suitable mesh structure, model configurations, scheme setup and boundary conditions to avoid loss of energy due to data interpolation between different modules or weak imposition of fluxes in finite element codes. Computational experiments are performed to study the tolerance control of each type of iteration to avoid false convergence. The coupled capability is demonstrated in both single pin and 7-pin models based on LFR materials and geometry. The study finds that the use of too large a time step size in the heat conduction module can lead to temperature oscillation even though the heat conduction equation does not have a time-derivative kernel, but only the time-dependent boundary condition. A 7-pin model without duct region achieved good convergence in the coupled calculation while a 7 pin model with duct region experienced data communication issues which need to be resolved.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Microbial Range Expansions on Liquid Substrates
Despite the importance of fluid flow for transporting and organizing populations, few laboratory systems exist to systematically investigate the impact of advection on their spatial evolutionary dynamics. To address this problem, we study the morphology and genetic spatial structure of microbial colonies growing on the surface of a nutrient-laden fluid 10 4 to 10 5 times more viscous than water in Petri dishes; the extreme but finite viscosity inhibits undesired thermal convection and allows populations to effectively live at the air-liquid interface due to capillary forces. We discover that S. cerevisiae (baker’s yeast) growing on a viscous liquid behave like “active matter”: They metabolically generate fluid flows many times larger than their unperturbed colony expansion speed, and that flow, in turn, can dramatically impact their colony morphology and spatial population genetics. We show that yeast cells generate fluid flows by consuming surrounding nutrients and decreasing the local substrate density, leading to misaligned fluid pressure and density contours, which ultimately generates vorticity via a thresholdless baroclinic instability. Numerical simulations with experimentally measured parameters demonstrate that an intense vortex ring is produced below the colony’s edge. As the viscosity of the substrate is lowered and the self-induced flow intensifies, we observe three distinct morphologies: At the highest viscosity, cell proliferation and movement produces compact circular colonies with, however, a stretched regime of exponential expansion; intermediate viscosities give rise to compact colonies with “fingers” that are usually monoclonal and then break into smaller cell clusters; at the lowest viscosity, the expanding colony fractures into many genetically diverse, mutually repelling, islandlike fragments that can colonize an entire 94-mm-diameter Petri dish within 36 hours. We propose a simple phenomenological model that predicts the early colony dynamics. Our results provide rich opportunities to study the interplay between fluid flow and spatial population genetics for future investigations.
36 MATERIALS SCIENCE↗
Computational Investigation of Melt Pool Process Dynamics and Pore Formation in Laser Powder Bed Fusion
In the laser powder bed fusion additive manufacturing process, the presence of porosity may result in cracks and significantly affects the part performance. A comprehensive understanding of the melt pool process dynamics and porosity evolution can help to improve build quality. In this study, a novel multi-physics computational fluid dynamics (CFD) model has been applied to investigate the fluid dynamics in melt pools and resultant pore defects. To accurately capture the melting and solidification process, major process physics, such as the surface tension, evaporation as well as laser multi-reflection, have been considered in the model. A discrete element method is utilized to model the generation of powder spreading upon build plate by additional numerical simulations. Multiple single track experiments have been performed to obtain the melt pool shape and cross-sectional dimension information. The predicted melt pool dimensions were found to have a reasonable agreement with experimental measurements, e.g., the errors are in the range of 1.3 to 10.6% for melt pool width, while they are between 1.4 and 15.9% for melt depth. Pores are captured by both CFD simulation and x-ray computed tomography measurement for the case with a laser power of 350 W and laser speed of 100 mm/s. The formation of keyholes maybe related to the melt pool front wall angle, and it is found that the front wall angle increases with the increase in laser line energy density. In addition, a larger laser power or smaller scanning speed can help to generate keyhole-induced pores; they also contribute to produce larger sized pores.
36 MATERIALS SCIENCE↗
Development of Transient Coupled Chemical-Thermal-Fluids Simulation for Unsealed Aluminum-Clad Spent Nuclear Fuel Storage Canister
This study examines a preliminary three-dimensional (3D) multi-physics computational fluid dynamics (CFD) model of the unsealed canisters containing aluminum-clad spent nuclear fuel from INL’s ATR in the irradiated fuel storage facility. This 3D CFD model considers fully resolved fuel plates in an unsealed canister with small mass exchange with surrounding air as time evolves in the simulation and contains a network of chemical reactions to consider due to several of the side reactions occurring in the presence of water vapor, nitrogen, oxygen and carbon dioxide rather than in helium backfilled DOE standard canisters. Prior to the CFD modeling, the full set of chemical reactions under these conditions was analyzed, reduced, and refit to a more manageable number of equations for the computational efficiency of the 3D CFD simulation. To deal with the long time-scale of interest for tracking the possible buildup of trace species such as nitric acid, NOx, and hydrogen, a segregated time stepping algorithm is used, wherein the velocity field is only updated periodically, and assume to be in a pseudo steady state. This study first examines the theory of the model, workflow to establish radiolysis reaction network, and initial simulations of the evolutions of thermal fields, hydrogen gas and nitric acid concentrations within unsealed canisters in conditions relevant to the INL INTEC CPP-603 facility over a long period of time.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Development of Transient Coupled Chemical-Thermal-Fluids Simulation for Unsealed Aluminum-Clad Spent Nuclear Fuel Storage Canister
This study examines a preliminary three-dimensional (3D) multi-physics computational fluid dynamics (CFD) model of the unsealed canisters containing aluminum-clad spent nuclear fuel from INL’s ATR in the irradiated fuel storage facility. This 3D CFD model considers fully resolved fuel plates in an unsealed canister with small mass exchange with surrounding air as time evolves in the simulation and contains a network of chemical reactions to consider due to several of the side reactions occurring in the presence of water vapor, nitrogen, oxygen and carbon dioxide rather than in helium backfilled DOE standard canisters. Prior to the CFD modeling, the full set of chemical reactions under these conditions was analyzed, reduced, and refit to a more manageable number of equations for the computational efficiency of the 3D CFD simulation. To deal with the long time-scale of interest for tracking the possible buildup of trace species such as nitric acid, NOx, and hydrogen, a segregated time stepping algorithm is used, wherein the velocity field is only updated periodically, and assume to be in a pseudo steady state. This study first examines the theory of the model, workflow to establish radiolysis reaction network, and initial simulations of the evolutions of thermal fields, hydrogen gas and nitric acid concentrations within unsealed canisters in conditions relevant to the INL INTEC CPP-603 facility over a long period of time.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Development of Transient Coupled Chemical-Thermal-Fluids Simulation for Unsealed Aluminum-Clad Spent Nuclear Fuel Storage Canister - 19273
This study examines a preliminary three-dimensional (3D) multi-physics computational fluid dynamics (CFD) model of the unsealed canisters containing aluminum-clad spent nuclear fuel from INL's ATR in the irradiated fuel storage facility. This 3D CFD model considers fully resolved fuel plates in an unsealed canister with small mass exchange with surrounding air as time evolves in the simulation and contains a network of chemical reactions to consider due to several of the side reactions occurring in the presence of water vapor, nitrogen, oxygen and carbon dioxide rather than in helium backfilled DOE standard canisters. Prior to the CFD modeling, the full set of chemical reactions under these conditions was analyzed, reduced, and refit to a more manageable number of equations for the computational efficiency of the 3D CFD simulation. To deal with the long time-scale of interest for tracking the possible buildup of trace species such as nitric acid, NOx, and hydrogen, a segregated time stepping algorithm is used, wherein the velocity field is only updated periodically, and assumed to be in a pseudo steady state. This study first examines the theory of the model, workflow to establish radiolysis reaction network, and initial simulations of the evolutions of thermal fields, hydrogen gas and nitric acid concentrations within unsealed canisters in conditions relevant to the INL INTEC CPP-603 facility over a long period of time. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Effect of an oxygen plasma on the physical and chemical properties of several fluids for the liquid droplet radiator
The Liquid Droplet Radiator is one of several radiator systems currently under investigation by NASA Lewis Research Center. It involves the direct exposure of the radiator working fluid to the space environment. An area of concern is the potential harmful effects of the low-Earth-orbit atomic oxygen environment on the radiator working fluid. To address this issue, seven candidate fluids were exposed to an oxygen plasma environment in a laboratory plasma asher. The fluids studied included Dow Corning 705 Diffusion Pump Fluid, polymethylphenylsiloxane and polydimethlsiloxane, both of which are experimental fluids made by Dow Corning, Fomblin Z25, made by Montedison, and three fluids from the Krytox family of fluids, Krytox 143AB, 1502, and 16256, which are made by DuPont. The fluids were characterized by noting changes in visual appearance, physical state, mass, and infrared spectra. Of the fluids tested, the Fomblin and the three Krytoxes were the least affected by the oxygen plasma. The only effect noted was a change in mass, which was most likely due to an oxygen-catalyzed deploymerization of the fluid molecule.
Gulino, D. A.↗
Effect of an oxygen plasma on the physical and chemical properties of several fluids for the Liquid Droplet Radiator
The Liquid Droplet Radiator is one of several radiator systems currently under investigation by NASA Lewis Research Center. It involves the direct exposure of the radiator working fluid to the space environment. An area of concern is the potential harmful effects of the low-Earth-orbit atomic oxygen environment on the radiator working fluid. To address this issue, seven candidate fluids were exposed to an oxygen plasma environment in a laboratory plasma asher. The fluids studied included Dow Corning 705 Diffusion Pump Fluid, polymethylphenylsiloxane and polydimethylsiloxane, both of which are experimental fluids made by Dow Corning, Fomblin Z25, made by Montedison, and three fluids from the Krytox family of fluids, Krytox 143AB, 1502, and 16256, which are made by DuPont. The fluids were characterized by noting changes in visual appearance, physical state, mass, and infrared spectra. Of the fluids tested, the Fomblin and the three Krytoxes were the least affected by the oxygen plasma. The only effect noted was a change in mass, which was most likely due to an oxygen-catalyzed depolymerization of the fluid molecule.
Gulino, Daniel A.↗
Transient Coupled Chemical-Thermal-Fluid Field Simulation for Sealed Aluminum-clad Spent Nuclear Fuel Storage Canister
As the first step toward developing three-dimensional (3D) multi-physics computational fluid dynamics (CFD) model for unsealed and vented canister storage system, a 3D CFD model coupled with bulk gas radiolysis reactions was developed first for sealed DOE standard canisters filled with inert gas and trace amount of air and water. The workflow for constructing canister-scale 3D CFD models and coupling with gas phase radiolysis reactions were established, which can be readily extended to unsealed, vented canister storage system. This interim milestone report documents the theory of the model, workflow to establish radiolysis reaction network, and initial simulations of the evolutions of thermal fields and hydrogen gas concentrations within sealed DOE standard canisters over long period of time. In addition, a mesh refinement test was done to show that increasing the models mesh refinement had negligible impact upon the temperature profiles.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Development of Transient Coupled Chemical-Thermal-Fluid Multiphysics Simulation for Unsealed, Vented Aluminum-clad Spent Nuclear Fuel Storage Canister
As the second step towards modeling three-dimensional (3D) multi-physics computational fluid dynamics (CFD) of the unsealed containers in the IFSF facility, the previous methodology used for developing the sealed DOE standard canister model was utilized here. This 3D CFD model considers unsealed canister with small mass exchange with surrounding air as time evolves in the simulation and contains a larger network of chemical reactions to consider due to several of the side reactions occurring in the presence of water vapor, nitrogen, oxygen and carbon dioxide rather than a helium backfilled canister. Similar to the sealed system, the set of full radiolytic chemical reactions of bulk moist air were established, and then reduced to a more manageable set of equations for the computational efficiency of the 3D CFD simulation. Due to the similar size of the unsealed canisters to the sealed DOE canisters, it is assumed that the chemical and thermal response times to changes in the conditions remains similar such that the same time-stepping algorithm can be utilized. This report documents the theory of the model, workflow to establish radiolysis reaction network, and initial simulations of the evolutions of thermal fields, hydrogen gas and nitric acid concentrations within unsealed canisters in conditions relevant to INL INTEC CPP-603 over a long period of time.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Striving to translate shale physics across ten orders of magnitude: What have we learned?
Shales will play an important role in the successful transition of energy from fossil-based resources to renewables in the coming decades. Aside from being a significant source of low-carbon intensity fuels, like natural gas, they also serve as geologic seals of subsurface formations that may be used to isolate nuclear waste, sequester CO 2 , or store intermittent energy (e.g., solar hydrogen). Despite their importance, shales pose significant engineering and environmental challenges due to their nanoporous structure and extreme heterogeneity that spans at least ~10 orders of magnitude in spatial scale. Two challenges inhibit a system-level understanding: (1) the physics of fluid flow and phase behavior in shales are poorly understood due to the dominant molecular interactions between minerals and fluids under confinement, and (2) the apparent lack of scale separation that prevents a reliable (closed) description of the physics at any single scale of observation. In this review, we focus on the latter issue and discuss scale translation, which in its broadest sense is transforming data or simulations from one spatiotemporal scale to another. While effective scale translation is not exclusive to shales, but all geologic porous media, the need for it is especially acute in shales given their high degree of heterogeneity. Classical theories like homogenization, while indispensable, fail when scales are not separated. Other methods, like numerical upscaling, scale-translate in only one direction: small to large, but not the reverse, called downscaling. However, the confluence of advances in three areas are bringing challenging problems such as shales within reach: increased computational power and scalable algorithms; high-resolution imaging and multi-modal data acquisition; and machine learning to process massive amounts of data. While these advances equip geoscientists with a wide array of experimental and computational tools, no individual tool can probe the entire gamut of heterogeneity in shales. Their effective use, therefore, requires an ability to bridge between various data types obtained at different scales. The aim of this review is to present a coherent account of computational and experimental methods that may be used to achieve just that, i.e., to perform scale translation. We provide a broader definition of scale translation, one that transcends classical homogenization and upscaling methods, but is consistent with them and accommodates notions like downscaling and data translation. After a brief introduction to homogenization, we review hybrid methods, numerical upscaling and its recent extensions, multiscale computing, high-resolution imaging, and machine learning. We place particular emphasis on multiscale computing and propose an algorithmic framework to bridge between the pore (micro) and Darcy (macro) scales. Throughout the paper, we draw comparisons between the various methods and highlight their (often hidden) similarities, differences, benefits, and pitfalls. We finally conclude with two case studies on shales that exemplify some of the methods presented.
58 GEOSCIENCES↗
Imaging shapes of atomic nuclei in high-energy nuclear collisions
Atomic nuclei are self-organized, many-body quantum systems bound by strong nuclear forces within femtometre-scale space. These complex systems manifest a variety of shapes, traditionally explored using non-invasive spectroscopic techniques at low energies. However, at these energies, their instantaneous shapes are obscured by long-timescale quantum fluctuations, making direct observation challenging. Here we introduce the collective-flow-assisted nuclear shape-imaging method, which images the nuclear global shape by colliding them at ultrarelativistic speeds and analysing the collective response of outgoing debris. This technique captures a collision-specific snapshot of the spatial matter distribution within the nuclei, which, through the hydrodynamic expansion, imprints patterns on the particle momentum distribution observed in detectors. We benchmark this method in collisions of ground-state uranium-238 nuclei, known for their elongated, axial-symmetric shape. Our findings show a large deformation with a slight deviation from axial symmetry in the nuclear ground state, aligning broadly with previous low-energy experiments. This approach offers a new method for imaging nuclear shapes, enhances our understanding of the initial conditions in high-energy collisions and addresses the important issue of nuclear structure evolution across energy scales.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Physics-Based Modeling and Simulation of Self-Reacting Friction Stir Welding Using Computational Fluid Dynamics
A physics-based model was developed to simulate the behavior of material in a self-reacting friction stir welding (SR-FSW) process for the joining of metals. This steady-state model builds upon fundamental computational fluid dynamic (CFD) principles within Ansys Fluent to solve the discretized equations. The effective viscosity is calculated using a viscoplastic model using a Sheppard-Wright formulation of flow stress. Numerous advancements have been made in the incorporated physics including (1) temperature-dependent material properties; (2) locally adaptable flow and thermal boundary conditions; and (3) adapting material properties in nugget in response to microstructural changes. Simulation strategies to accelerate computation and improve numerical stability include adapting the mesh refinement and solver relaxation factors during simulation. The result is a highly robust and computationally efficient model capable of providing the material flow and temperature history across the domain. As material history determines the local microstructure and ultimately weld strength, an accurate and detailed physics-based model has the potential to accelerate SR-FSW process development. The model is highly adaptable to changes in process parameters, tool design, or alloy.
Process Modeling↗