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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 325 records · Page 18

Interaction between two conducting spheres in weakly ionized collisional plasma

Charging of two conducting spheres in a weakly ionized collisional plasma flow is considered. The spheres are arranged along the flow, and the plasma is assumed to consist of two ion species with the charges equal in magnitude but opposite in sign. The problem is analyzed with allowance for the external electric field, charging of the spheres due to the sedimentation of plasma ions on them, the fields of the sphere charges, the space charge field, and the processes of recombination and molecular diffusion. The interaction between the spheres and plasma is studied by numerically solving a time-dependent problem in a bispherical coordinate system by the finite difference method. The steady-state values of the sphere charges and the distributions of the space charge and ion densities in the ambient plasma are found as functions of the plasma parameters and the distance between the spheres. The electrostatic forces acting on the spheres are determined, and the effects of the external field, the space charge fields, and the fields of the sphere charges are comparatively analyzed. It is shown that, for the considered plasma parameters, the main electrostatic effect in the interaction between two spheres is their mutual approach in the external field due to the difference in their charges (one sphere catches up with the other). Due to the friction force with the neutral gas, this mutual approach is much slower than all other processes in the system. For widely spaced spheres, the results coincide with the solution obtained previously for a solitary sphere.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multi-Physics Simulations of Molten Chloride Fast Reactor using Nek5000 and PROTEUS-NODAL

This report documents the FY20 work to demonstrate a specific multi-physics capability within NEAMS tools to model molten chloride fast reactors (MCFR). Specifically, the CFD code Nek5000 and the neutronics code PROTEUS-NODAL were coupled off-line to calculate the delayed neutron precursor distribution within the flowing fuel salts in an MCFR core. An MCFR benchmark problem and a 3D test problem based on a conceptual MSR design were successfully solved through the coupled simulation of Nek5000 and PROTEUS-NODAL. In the coupled simulations for these test problems, Nek5000 provided high-quality flow field information, and PROTEUS-NODAL performed the neutron diffusion calculation along with the precursor drift model. The impact of precursor drift on the core status was also investigated. Additionally, the precursor drift model implemented in PROTEUS-NODAL was verified by making use of the reference precursor distribution generated from Nek5000. Results of these test problems suggest that the multi-physics capability of Nek5000 and PROTEUS-NODAL was properly developed for tracking delayed neutron precursor drift.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations

Data-driven discovery of differential equations has been an emerging research topic. We propose a novel algorithm subsampling-based threshold sparse Bayesian regression (SubTSBR) to tackle high noise and outliers. The subsampling technique is used for improving the accuracy of the Bayesian learning algorithm. It has two parameters: subsampling size and the number of subsamples. When the subsampling size increases with fixed total sample size, the accuracy of our algorithm goes up and then down. When the number of subsamples increases, the accuracy of our algorithm keeps going up. We demonstrate how to use our algorithm step by step and compare our algorithm with threshold sparse Bayesian regression (TSBR) for the discovery of differential equations. We show that our algorithm produces better results. We also discuss the merits of discovering differential equations from data and demonstrate how to discover models with random initial and boundary condition as well as models with bifurcations. The numerical examples are: (1) predator-prey model with noise, (2) shallow water equations with outliers, (3) heat diffusion with random initial and boundary condition, and (4) fish-harvesting problem with bifurcations.

97 MATHEMATICS AND COMPUTING↗

The Alamo multiphysics solver for phase field simulations with strong-form mechanics and block structured adaptive mesh refinement

Alamo is a high-performance scientific code that uses block-structured adaptive mesh refinement to solve such problems as: the ignition and burn of solid rocket propellant, plasticity, damage and fracture in materials undergoing loading, and the interaction of compressible flow with eroding solid materials. Alamo is powered by AMReX, and provides a set of unique methods, models, and algorithms that enable it to solve solid-mechanics problems (coupled to other physical behavior such as fluid flow or thermal diffusion) using the power of block-structured adaptive mesh refinement.

36 MATERIALS SCIENCE↗

SUNDIALS Multiphysics+MPIManyVector Performance Testing

In this report we document performance test results on a SUNDIALS-based multiphysics demonstration application. We aim to assess the large-scale parallel performance of new capabilities that have been added to the SUNDIALS suite of time integrators and nonlinear solvers in recent years under funding from both the Exascale Computing Project (ECP) and the Scientific Discovery through Advanced Scientific (SciDAC) program, specifically: 1. SUNDIALS’ new MPIManyVector module, that allows extreme flexibility in how a solution "vector" is staged on computational resources. 2. ARKode’s new multirate integration module, MRIStep, allowing high-order accurate calculations that subcycle "fast" processes within "slow" ones. 3. SUNDIALS’ new flexible linear solver interfaces, that allow streamlined specification of problem-specific linear solvers. 4. SUNDIALS’ new N_Vector additions of "fused" vector operations (to increase arithmetic intensity) and separation of reduction operations into "local" and "global" versions (to reduce latency by combining multiple reductions into a single MPI_Allreduce call). We anticipate that subsequent reports will extend this work to investigate a variety of other new features, including SUNDIALS’ generic SUNNonlinearSolver interface and accelerator-enabled N Vector modules, and upcoming MRIStep extensions to support custom "fast" integrators (that leverage problem structure) and IMEX integration of the "slow" time scale (to add diffusion).

97 MATHEMATICS AND COMPUTING↗

Time-dependent Perpendicular Transport of Energetic Particles for Different Turbulence Configurations and Parallel Transport Models

Recently, a new theory for the transport of energetic particles across a mean magnetic field was presented. Compared to other nonlinear theories the new approach has the advantage that it provides a full time-dependent description of the transport. Furthermore, a diffusion approximation is no longer part of that theory. The purpose of this paper is to combine this new approach with a time-dependent model for parallel transport and different turbulence configurations in order to explore the parameter regimes for which we get ballistic transport, compound subdiffusion, and normal Markovian diffusion.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploring the Performance and Reliability of Screen-Printable Fire-Through Copper Paste on PERC Solar Cells

For 40 TW of PV required to transition our planet to 100% renewables, the silver (Ag) should disappear from PV production. Advantages of copper (Cu) over silver (Ag) include 1) bulk Cu has a similar conductivity to Ag (1.7 mu O-cm for Cu, 1.6 mu O-cm for Ag) and 2) Cu is approximately 100 times cheaper than Ag, making it an excellent potential replacement. Problems associated with copper (Cu) contacts include 1) easy oxidation and 2) diffusion into the Si cell and recombination activity.

copper paste↗

A localized artificial diffusivity method to simulate compressible multiphase flows using the stiffened gas equation of state: A localized artificial diffusivity method to simulate compressible multiphase flows using the stiffened gas equation of state

The development of numerical approaches to perform direct numerical simulations of compressible multiphase flows has been an active field of research for several years. Proper treatment of fluid interfaces is crucial as important physics occur in this infinitesimally small region. Furthermore, the compressibility of the fluid requires proper treatment of discontinuities. Artificial diffusivity is among a number of methods widely used for compressible flows. This study develops a general form of consistent artificial diffusion fluxes and extends the localized artificial diffusivity method for high-order central schemes to solve multiphase flows with an interface-capturing method. These fluxes ensure an oscillation-free interface for pressure, velocity, and temperature without employing a sharpening technique. Moreover, the high-order representation of all scales in the flow helps capture the wide range of instabilities inherent in these flows. The goal is to develop an approach capable of performing high-fidelity simulations supported by physics-driven validation. lastly, this is achieved by solving the five-equation model with the stiffened-gas equation of state using the proposed method for multicomponent and multiphase flows on a variety of 1D and 2D problems.

42 ENGINEERING↗

Influence of multi-species solute transport on modeling of hydrated Portland cement leaching in strong nitrate solutions

The differences between the predictions of Fickian diffusion and Nernst-Planck electro-diffusion based reactive transport models are investigated in the context of an important practical problem – leaching of Portland cement in strong nitrate porewater solutions under saturated conditions. Numerical results are presented for three distinct porewater solutions: deionized water, ammonium nitrate solution, and diluted porewater from a cementitious low-activity nuclear waste form. Solute concentrations predicted by the two transport models show significant differences: as much as a factor of two for ammonium nitrate leaching and as much as a factor of four for waste form leaching; whereas, negligible differences are observed for deionized water leaching. The major conclusion is that Fickian diffusion may be accurate enough for deionized water leaching, but electro-diffusion should be considered in the reactive solute transport modeling of ammonium nitrate decalcification and in the degradation modeling of cementitious materials exposed to nuclear waste form solutions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds

Here, we demonstrate, on a scramjet combustion problem, a constrained probabilistic learning approach that augments physics-based datasets with realizations that adhere to underlying constraints and scatter. The constraints are captured and delineated through diffusion maps, while the scatter is captured and sampled through a projected stochastic differential equation. The objective function and constraints of the optimization problem are then efficiently framed as non-parametric conditional expectations. Different spatial resolutions of a large-eddy simulation filter are used to explore the robustness of the model to the training dataset and to gain insight into the significance of spatial resolution on optimal design.

42 ENGINEERING↗

Tensor Network Space-Time Spectral Collocation Method for Time-Dependent Convection-Diffusion-Reaction Equations

Emerging tensor network techniques for solutions of partial differential equations (PDEs), known for their ability to break the curse of dimensionality, deliver new mathematical methods for ultra-fast numerical solutions of high-dimensional problems. Here, we introduce a Tensor Train (TT) Chebyshev spectral collocation method, in both space and time, for the solution of the time-dependent convection-diffusion-reaction (CDR) equation with inhomogeneous boundary conditions, in Cartesian geometry. Previous methods for numerical solution of time-dependent PDEs often used finite difference for time, and a spectral scheme for the spatial dimensions, which led to a slow linear convergence. Spectral collocation space-time methods show exponential convergence; however, for realistic problems they need to solve large four-dimensional systems. We overcome this difficulty by using a TT approach, as its complexity only grows linearly with the number of dimensions. We show that our TT space-time Chebyshev spectral collocation method converges exponentially, when the solution of the CDR is smooth, and demonstrate that it leads to a very high compression of linear operators from terabytes to kilobytes in TT-format, and a speedup of tens of thousands of times when compared to a full-grid space-time spectral method. These advantages allow us to obtain the solutions at much higher resolutions.

97 MATHEMATICS AND COMPUTING↗

Suppressing 1 H Spin Diffusion in Fast MAS Proton Detected Heteronuclear Correlation Solid-State NMR Experiments

Fast magic angle spinning (MAS) and indirect detection by high gyromagnetic ratio (γ) nuclei such as proton or fluorine are increasingly utilized to obtain 2D heteronuclear correlation (HETCOR) solid-state NMR spectra of spin-1/2 nuclei by using cross polarization (CP) for coherence transfer. However, one major drawback of CP HETCOR pulse sequences is that 1 H spin diffusion during the back X→ 1 H CP transfer step results in relayed correlations. This problem is particularly pronounced for the indirect detection of very low-γ nuclei such as 89 Y, 103 Rh, 109 Ag and 183 W where long contact times on the order of 10 to 30 ms are necessary for optimal CP transfer. In this work, we propose two methods that eliminate relayed correlations and allow more reliable distance information to be obtained from 2D HETCOR NMR spectra. The first method uses Lee-Goldburg (LG) CP during the X→ 1 H back-transfer step to suppress 1 H spin diffusion. We determine LG conditions compatible with fast MAS frequencies (ν rot ) of 40- 95 kHz and show that 1 H spin diffusion can be efficiently suppressed at low effective radiofrequency (RF) fields (ν 1,eff << 0.5ν rot ) and also at high effective RF fields (ν 1,eff >> 2ν rot ). We describe modified Hartmann-Hahn LG-CP match conditions compatible with fast MAS and suitable for indirect detection of moderate-γ nuclei such as 13 C, and low-γ nuclei such as 89 Y. The second method uses D-RINEPT (dipolar refocused insensitive nuclei enhanced by polarization transfer) during the X→ 1 H back-transfer step of the HETCOR pulse sequence. The effectiveness of these methods for acquiring HETCOR spectra with reduced relayed signal intensities is demonstrated with 1 H{ 13 C} HETCOR NMR experiments on L-histidine•HCl•H 2 O and 1 H{ 89 Y} HETCOR NMR experiments on an organometallic yttrium complex.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Diffusion, atomic transport, and ordering in Al-Zr alloys: FCC and liquid phases

Additive manufacturing of materials with controlled microstructure demands knowledge of atomic scale properties near the solid-liquid transition state. Many of these properties are not affordable by experimental techniques and computer modeling is the possible solution to the problem. In this paper, we present the results of an extended atomistic study of intrinsic atomic transport due to vacancy diffusion in FCC and L12 solid phases and diffusion in the liquid phase of Al-Zr alloys. A deceleration of the overall self-diffusion was observed when Zr was added to Al. The effect was stronger in the solid and weaker in the liquid. Additionally, the effect was strongly temperature dependent in the solid phases, but not in the liquid. Atomic transport was chemically biased: transport of Zr atoms was significantly slower than that of Al atoms, and this bias effect was stronger in the solid phases. The overall diffusion and chemical ordering processes in the liquid state were five to six orders in magnitude faster than in the solid. Chemical short-range order parameters in the liquid saturated at values close to those in the ordered L12 structure of Al3Zr. Chemical and structural ordering in the solid phases was negligible over the modeled microsecond time scale. Here, the results are discussed in view of optimizing additive manufacturing parameters for the controlled formation of metastable L1 2 precipitates.

36 MATERIALS SCIENCE↗

Density Large Deviations for Multidimensional Stochastic Hyperbolic Conservation Laws

We investigate the density large deviation function for a multidimensional conservation law in the vanishing viscosity limit, when the probability concentrates on weak solutions of a hyperbolic conservation law. When the mobility and diffusivity matrices are proportional, i.e. an Einstein-like relation is satisfied, the problem has been solved in Bellettini and Mariani (Bull Greek Math Soc 57:31–45, 2010). When this proportionality does not hold, we compute explicitly the large deviation function for a step-like density profile, and we show that the associated optimal current has a non trivial structure. We also derive a lower bound for the large deviation function, valid for a more general weak solution, and leave the general large deviation function upper bound as a conjecture.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Homology modeling and docking of AahII-Nanobody complexes reveal the epitope binding site on AahII scorpion toxin

Highlights: • AahII specific nanobodies share common CDRs sequence patterns. • Residues forming sequences' pattern interact specifically with AahII. • CDR1 Tyr27, Tyr29 and Ser30 polar residues are involved in AahII neutralization. • Interacting AahII Arg62/NbAahII10 CDR3 Asp112 charged residues are crucial. • AahII-NbAahII10 trapping involves a distinct toxin 3D orientation. Scorpion envenoming and its treatment is a public health problem in many parts of the world due to highly toxic venom polypeptides diffusing rapidly within the body of severely envenomed victims. Recently, 38 AahII-specific Nanobody sequences (Nbs) were retrieved from which the performance of NbAahII10 nanobody candidate, to neutralize the most poisonous venom compound namely AahII acting on sodium channels, was established. Herein, structural computational approach is conducted to elucidate the Nb-AahII interactions that support the biological characteristics, using Nb multiple sequence alignment (MSA) followed by modeling and molecular docking investigations (RosettaAntibody, ZDOCK software tools). Sequence and structural analysis showed two dissimilar residues of NbAahII10 CDR1 (Tyr27 and Tyr29) and an inserted polar residue Ser30 that appear to play an important role. Indeed, CDR3 region of NbAahII10 is characterized by a specific Met104 and two negatively charged residues Asp115 and Asp117. Complex dockings reveal that NbAahII17 and NbAahII38 share one common binding site on the surface of the AahII toxin divergent from the NbAahII10 one's. At least, a couple of NbAahII10 – AahII residue interactions (Gln38 – Asn44 and Arg62, His64, respectively) are mainly involved in the toxic AahII binding site. Altogether, this study gives valuable insights in the design and development of next generation of antivenom.

60 APPLIED LIFE SCIENCES↗

Metastability of stratified magnetohydrostatic equilibria and their relaxation

Motivated by explosive releases of energy in fusion, space and astrophysical plasmas, we consider the nonlinear stability of stratified magnetohydrodynamic equilibria against two-dimensional interchanges of straight magnetic-flux tubes. We demonstrate that, even within this restricted class of dynamics, the linear stability of an equilibrium does not guarantee its nonlinear stability: equilibria can be metastable. We show that the minimum-energy state accessible to a metastable equilibrium under non-diffusive two-dimensional dynamics can be found by solving a combinatorial optimisation problem. These minimum-energy states are, to good approximation, the final states reached by our simulations of destabilised metastable equilibria for which turbulent mixing is suppressed by viscosity. To predict the result of fully turbulent relaxation, we construct a statistical mechanical theory based on the maximisation of Boltzmann's mixing entropy. This theory is analogous to the Lynden-Bell statistical mechanics of collisionless stellar systems and plasma, and to the Robert–Sommeria–Miller theory of two-dimensional vortex turbulence. Our theory reproduces well the results of our numerical simulations for sufficiently large perturbations to the metastable equilibrium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Investigating the crust of neutron stars with neural-network quantum states

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm −3 and 0.1 fm −3 , matter transitions from neutron-rich nuclei to various higher-density pasta shapes, before ultimately reaching a uniform liquid. In this work, we introduce a variational Monte Carlo method based on a neural Pfaffian-Jastrow quantum state, which allows us to model the transition from the liquid phase to neutron-rich nuclei microscopically. At low densities, nuclear clusters dynamically emerge from the microscopic interactions among protons and neutrons, which we model based on pionless effective field theory. Our variational Monte Carlo approach represents a significant improvement over the state-of-the-art auxiliary-field diffusion Monte Carlo method, which is severely hindered by the fermion-sign problem in this low-density regime and cannot capture the onset of clusters. In addition to computing the energy per particle of symmetric nuclear matter and pure neutron matter, we analyze an intermediate isospin-asymmetry configuration to elucidate the formation of nuclear clusters. We also provide evidence that the presence of such nuclear clusters influences the amount of protons in the crust compared to protons in beta-equilibrated, neutrino-transparent matter.

Nuclear astrophysics↗