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At least 307 records · Page 17

The calculation of electron density profiles from topside ionograms: Method and applications

A method for converting topside sounder ionograms into topside electron density profiles is discussed. The lamination method used is modified to take into account the variation of electron density and magnetic field within each lamination. Also included is a change of variable to produce a finite integrand of the integral involved, an iteration scheme that permits convergence on an initially unknown density, a second iteration scheme to overcome the problem of an uncertainty in the electron density at the satellite, and a modification to compensate for the changing satellite altitude over the duration of the sounding. Two applications of the technique are discussed: field-aligned traces for computing field-aligned profiles and computer-aided systems for scaling ionograms.

Lockwood, G. E. K.↗

Coupling finite element and integral equation solutions using decoupled boundary meshes

A method is outlined for calculating scattered fields from inhomogeneous penetrable objects using a coupled finite element-integral equation solution. The finite element equation can efficiently model fields in penetrable and inhomogeneous regions, while the integral equation exactly models fields on the finite element mesh boundary and in the exterior region. By decoupling the interior finite element and exterior integral equation meshes, considerable flexibility is found in both the number of field expansion points as well as their density. Only the nonmetal portions of the object need be modeled using a finite element expansion; exterior perfect conducting surfaces are modeled using an integral equation with a single unknown field since E(tan) is identically zero on these surfaces. Numerical convergence, accuracy, and stability at interior resonant frequencies are studied in detail.

Cwik, Tom↗

Study and modeling of finite rate chemistry effects in turbulent non-premixed flames

The development of numerical models that reflect some of the most important features of turbulent reacting flows requires information about the behavior of key quantities in well defined combustion regimes. In turbulent flames, the coupling between turbulent and chemical processes is so strong that it is extremely difficult to isolate the role played by one individual physical phenomenon. Direct numerical simulation (hereafter DNS) allows us to study in detail the turbulence-chemistry interaction in some restricted but completely defined situations. Globally, non-premixed flames are controlled by two limiting regimes: the fast chemistry case, where the turbulent flame can be pictured as a random distribution of local chemical equilibrium problems; and the slow chemistry case, where the chemistry integrates in time the turbulent fluctuations. The Damkoehler number, ratio of a mechanical time scale to chemical time scale, is used to distinguish between these regimes. Today most of the industrial computer codes are able to perform predictions in the hypothesis of local equilibrium chemistry using a presumed shape for the probability density function (pdt) of the conserved scalar. However, the finite rate chemistry situation is of great interest because industrial burners usually generate regimes in which, at some points, the flame is undergoing local extinction or at least non-equilibrium situations. Moreover, this variety of situations strongly influences the production of pollutants. To quantify finite rate chemistry effect, the interaction between a non-premixed flame and a free decaying turbulence is studied using DNS. The attention is focused on the dynamic of extinction, and an attempt is made to quantify the effect of the reaction on the small scale mixing process. The unequal diffusivity effect is also addressed. Finally, a simple turbulent combustion model based on the DNS observations and tractable in real flow configurations is proposed.

Vervisch, Luc↗

Thermomechanical Microstructural Predictions of Fracture Nucleation of Zircaloy-4 Alloys With δ and ε Hydride Distributions

Abstract A crystalline dislocation-density formulation that was incorporated with a nonlinear finite-element (FE) method was utilized to understand and to predict the thermomechanical behavior of an hexagonal closest packed (h.c.p.) zircaloy system with hydrides with either face-centered cubic (f.c.c.) or body-centered cubic (b.c.c.) hydrides. This formulation was then used with a recently developed fracture methodology that is adapted for finite inelastic strains and multiphase crystalline systems to understand how different microstructurally based fracture modes nucleate and propagate. The interrelated microstructural characteristics of the different crystalline hydride and matrix phases with the necessary orientation relationships (ORs) have been represented, such that a detailed physical understanding of fracture nucleation and propagation can be predicted for the simultaneous thermomechanical failure modes of hydride populations and the matrix. The effects of volume fraction, morphology, crystalline structure, and orientation and distribution of the hydrides on simultaneous and multiple fracture modes were investigated for radial, circumferential, and mixed distributions. Another key aspect was accounting for temperatures changes due to the effects of thermal conduction and dissipated plastic work and their collective effects on fracture. For hydrided aggregates subjected to high temperatures, thermal softening resulted in higher ductility due to increased dislocation-density activity, which led to higher shear strain accumulation and inhibited crack nucleation and growth. The predictions provide validated insights into why circumferential hydrides are more fracture-resistant than radial hydrides for different volume fractions and thermomechanical loading conditions.

Engineering↗

Dislocation dynamics during the growth of silicon ribbon

The thermal viscoplastic stresses and the dislocation densities in silicon ribbon are computed for an axially changing thermal profile by using an iterative finite difference method. A material constitutive equation (Haasen-Sumino model) which involves an internal variable (mobile dislocation density) is used. The results are interpreted as showing that there is a maximum width of silicon ribbon that can be grown when viscoplasticity and dislocations are considered. This maximum width limitation does not exist if the material behavior is elastic.

Dillon, O. W., Jr.↗

Exploring Li-Air Batteries for High Specific Energy and High Power Applications: A Simulation Study

Commercialization of lithium-air batteries face many challenges, such as electrolyte decomposition, short cycle life, low energy efficiency, low power density, etc. However, commercialization of Li-air batteries for mass sensitive applications such as electric vehicles, portable power source, and drones is more challenging due to additional constraints of safety, electrolyte evaporation, high specific energy requirements, and reliable discharge times. In this presentation, we will present our finite element simulation results comparing Li-O2 and Li-air batteries using power density, energy density, specific power, and discharge times as metrics to evaluate different electrolytes and electrode geometry to reduce total mass and maximize discharge current. We use a finite element model and a discharge product model developed in which is based on porous electrode and concentrated electrolyte theories and the discharge product is modeled using quantum tunneling; for reaction kinetics and oxygen diffusion, an improved model was used. The electrolyte properties such as ion conductivity and ion diffusion were obtained from Molecular Dynamics (MD) simulations while the other parameters for the finite element model were calibrated to match experiments at high discharge current densities (>1.5 mA/cm2). The mass densities of different electrolytes were computed using MD simulations as well. For this presentation, we examine the practical electrochemical mass of a system at different current ratings, the sensitivity of mass to the use of ambient air as compared to pure oxygen as well as the electrolyte, which affects maximum current density and the total mass associated with the electrolyte (which includes the mass of additional components), and, the optimization of battery geometry for total discharge time, average discharge voltage, maximum discharge current, and minimum electrochemical mass.

Mehta, M.↗

Enhanced analysis of experimental x-ray spectra through deep learning

X-ray spectroscopic data from high-energy-density laser-produced plasmas has long required thorough, time-consuming analysis to extract meaningful source conditions. There are often confounding factors due to rapidly evolving states and finite spatial gradients (e.g., the existence of multi-temperature, multi-density, multi-ionization states, etc.) that make spectral measurements and analysis difficult. Here, in this paper, we demonstrate how deep learning can be applied to enhance x-ray spectral data analysis in both speed and intricacy. Neural networks (NNs) are trained on ensemble atomic physics simulations so that they can subsequently construct a model capable of extracting plasma parameters directly from experimental spectra. Through deep learning, the models can extract temperature distributions as opposed to single or dual temperature/density fits from standard trial-and-error atomic modeling at a significantly reduced computational cost compared to traditional trial-and-error methods. These NNs are envisioned to be deployed with high repetition rate x-ray spectrometers in order to provide detailed real-time analysis of experimental spectra.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Pit Stability Predictions of Additively Manufactured SS316 Surfaces Using Finite Element Analysis

Stainless steels are susceptible to localized forms of corrosion attack, such as pitting. The size and lifetime of a nucleated pit can vary, depending on a critical potential or current density criterion, which determines if the pit repassivates or continues growing. This work uses finite element method (FEM) modeling to compare the critical pit radii predicted by thermodynamic and kinetic repassivation criteria. Experimental electrochemical boundary conditions are used to capture the active pit kinetics. Geometric and environmental parameters, such as the pit shape and size (analogous to additively manufactured lack-of-fusion pores), solution concentration, and water layer thickness were considered to assess their impact on the pit repassivation criterion. The critical pit radius (the transition point from stable growth to repassivation) predicted for a hemispherical pit was larger when using the repassivation potential (E rp ) criteria, as opposed to the current density criteria (pit stability product). Including both the pit stability product and E rp into its calculations, the analytical maximum pit model predicted a critical radius two times more conservative than the FEA approach, under the conditions studied herein. The complex pits representing lack-of-fusion pores were shown to have minimal impact on the critical radius in atmospheric conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spectral quadrature for the first principles study of crystal defects: Application to magnesium

In this work, we present an accurate and efficient finite-difference formulation and parallel implementation of Kohn-Sham Density (Operator) Functional Theory (DFT) for non periodic systems embedded in a bulk environment. Specifically, employing non-local pseudopotentials, local reformulation of electrostatics, and truncation of the spatial Kohn-Sham Hamiltonian, and the Linear Scaling Spectral Quadrature method to solve for the pointwise electronic fields in real-space and the non-local component of the atomic force, we develop a parallel finite difference framework suitable for distributed memory computing architectures to simulate non-periodic systems embedded in a bulk environment. Choosing examples from magnesium-aluminum alloys, we first demonstrate the convergence of energies and forces with respect to spectral quadrature polynomial order, and the width of the spatially truncated Hamiltonian. Next, we demonstrate the parallel scaling of our framework, and show that the computation time and memory scale linearly with respect to the number of atoms. Next, we use the developed framework to simulate isolated point defects and their interactions in magnesium-aluminum alloys. Our findings conclude that the binding energies of divacancies, Al solute-vacancy and two Al solute atoms are anisotropic and are dependent on cell size. Furthermore, the binding is favorable in all three cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Particle-number fluctuations near the critical point of nuclear matter

Equation of state with the quantum statistics corrections is used for particle-number fluctuations ω of the isotopically symmetric nuclear matter with interparticle van der Waals and Skyrme local density interactions. Here, the fluctuations, ω ∝ 1/K, are analytically derived through the isothermal incompressibility K at first order over a small quantum-statistics parameter. Our approximate analytical results appear to be in good agreement with the results of accurate numerical calculations. These results are also close to those obtained by using more accurate Tolman and Rowlinson expansions of the incompressibility K near the critical point. More general formula for fluctuations ω, improved at the critical point, was obtained for a finite particle-number average $\langle$N$\rangle$ by neglecting, for simplicity, small quantum statistics effects. It is shown that for a large dimensionless parameter, α ∝ K 2 $\langle$N$\rangle$/K", where K" is the second derivative of the incompressibility K as function of the average particle density n, far from the critical point (α >> 1), one finds the traditional asymptote, ω ∝ 1/K, for the fluctuations ω. For a small parameter, α << 1, near the critical point, where K = 0 and α = 0, one obtains another asymptote of ω. These fluctuations, having a maximum near the critical point as function of the average density n, for finite values of $\langle$N$\rangle$ are finite and relatively small, in contrast to the results of the traditional calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Numerical investigations of low-density nozzle flow by solving the Boltzmann equation

A two-dimensional finite-difference code to solve the BGK-Boltzmann equation has been developed. The solution procedure consists of three steps: (1) transforming the BGK-Boltzmann equation into two simultaneous partial differential equations by taking moments of the distribution function with respect to the molecular velocity u(sub z), with weighting factors 1 and u(sub z)(sup 2); (2) solving the transformed equations in the physical space based on the time-marching technique and the four-stage Runge-Kutta time integration, for a given discrete-ordinate. The Roe's second-order upwind difference scheme is used to discretize the convective terms and the collision terms are treated as source terms; and (3) using the newly calculated distribution functions at each point in the physical space to calculate the macroscopic flow parameters by the modified Gaussian quadrature formula. Repeating steps 2 and 3, the time-marching procedure stops when the convergent criteria is reached. A low-density nozzle flow field has been calculated by this newly developed code. The BGK Boltzmann solution and experimental data show excellent agreement. It demonstrated that numerical solutions of the BGK-Boltzmann equation are ready to be experimentally validated.

Deng, Zheng-Tao↗

Effects of midplane density gradient in the propagation of high-harmonic fast waves considering high temperature anisotropy in the scrape-off layer of NSTX-U

High-Harmonic Fast Wave (HHFW) heating experiments in NSTX have shown that up to 60% of the injected power can be lost in the Scrape-Off Layer (SOL) when the density is above the fast wave cutoff density in front of the antenna, for which the fast wave is able to propagate into the plasma. This work models HHFW propagation in the SOL plasmas of NSTX-U using a 2D divertor SOL profile derived from the pressure assumption and the finite element temperature solution, which accounts for the high anisotropy of heat conduction in a 2D axisymmetric geometry. In this work, the two-dimensional axisymmetric SOL temperature profile is first evaluated by solving the steady-state non-linear heat conduction equation, in which thermal conductivity depends on temperature, using a finite element approach in the Petra-M workbench. A 2D density profile is then obtained from a prescribed density profile at the outer midplane assuming pressure is uniform along a flux tube in the SOL. This approach results in density and temperature profiles in which the strong asymmetric nature of heat conduction between the parallel and perpendicular background magnetic field is successfully captured. Furthermore, this work focuses on investigating the effect of the SOL plasma density profile on parasitic HHFW propagation in the SOL. The simulation results show that the radial gradient of the density profile affects the wavefield propagation in the SOL. As the density profile broadens, the wavefield intensity and its poloidal extent are reduced in the SOL, and the core coupling increases. Similarly, as shown by collisional power deposition, a proxy for power absorption, the fraction of power deposited in the SOL decreases with a broadening profile.

HHFW↗

Stability and Convergence of Solutions to Stochastic Inverse Problems Using Approximate Probability Densities

Data-consistent inversion is designed to solve a class of stochastic inverse problems where the solution is a pullback of a probability measure specified on the outputs of a quantities of interest (QoI) map. Here, this work presents stability and convergence results for the case where finite QoI data result in an approximation of the solution as a density. Given their popularity in the literature, separate results are proven for three different approaches to measuring discrepancies between probability measures: f-divergences, integral probability metrics, and L p metrics. In the context of integral probability metrics, we also introduce a pullback probability metric that is well-suited for data-consistent inversion. This fills a theoretical gap in the convergence and stability results for data-consistent inversion that have mostly focused on convergence of solutions associated with approximate maps. Numerical results are included to illustrate key theoretical results with intuitive and reproducible test problems that include a demonstration of convergence in the measure-theoretic "almost" sense.

97 MATHEMATICS AND COMPUTING↗

Improving stability of ALD ZrN thin film coatings over U-Mo dispersion fuel

Atomic layer deposition (ALD) of ZrN is a candidate technology for coating U-Mo dispersion fuel as a diffusion barrier coating. During the early development stages of the coating the ZrN deposition showed to be mechanically unstable and ultimately resulted in spalling. Based on experimental outcomes it was found that instabillity can be eliminated through the introduction of a thin amorphous (a) Al 2 O 3 interlayer coating deposited in between the ~1-μm thick ZrN and the U-Mo. substrate. To elucidate these findings simulations were performed with density functional theory (DFT) to measure work of adhesions at different interfaces while finite element modeling (FEM) was performed to measure the residual stress distribution. DFT indicated that the ZrN coating deposited over (a)-Al 2 O 3 is ~2.5 times stronger when compared to direct deposition over U or UO 2 substrate. While calculations from FEM recognized; (1) large stress concentrations can originate from the irregularly distributed native surface oxides (UO 2 ) over U-Mo and (2) stress concentrations can be reduced if those surface UO 2 can be modified to a uniform layer (achieved after application of a 8 nm (a)-Al 2 O 3 interlayer). These results provided explanations and confirmed the role played by interlayer in eliminating the original mechanical instability of the ZrN.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Minimum feature size control in level set topology optimization via density fields

A level set topology optimization approach that uses an auxiliary density field to nucleate holes during the optimization process and achieves minimum feature size control in optimized designs is explored. The level set field determines the solid-void interface and the density field describes the distribution of a fictitious porous material using the solid isotropic material with penalization. These fields are governed by two sets of independent optimization variables which are initially coupled using a penalty for hole nucleation. The strength of the density field penalization and projection is gradually increased during the optimization process to promote a 0-1 density distribution. In addition, a second penalty regulates the evolution of the density field in the void phase. The treatment of the density field combined with the second penalty mitigate the appearance of small design features. The minimum feature size of optimized designs is controlled by the radius of the linear filter applied to the density optimization variables. The structural response is predicted by the extended finite element method, the sensitivities by the adjoint method, and the optimization variables are updated by a gradient-based optimization algorithm. Numerical examples investigate the robustness of this approach with respect to algorithmic parameters and mesh refinement. The results show the applicability of the combined density level set topology optimization approach for both optimal hole nucleation and for minimum feature size control in 2D and 3D. This comes, however, at the cost of a more complex problem formulation and additional computational cost due to an increased number of optimization variables.

42 ENGINEERING↗

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗

Noniterative finite amplitude methods for giant resonances and the application to the neutron radiative capture cross sections

We calculate the electric dipole (E1) and the magnetic dipole (M1) giant resonances with noniterative finite amplitude methods and demonstrate how the fully microscopic density functional theory predicts the giant resonances without any phenomenological parameters. Then, we calculate neutron capture reactions based on the statistical Hauser-Feshbach theory with the result of E1 and M1 transitions and find that the capture cross sections for deformed nuclei are enhanced due to the contribution from the low energy M1 scissors mode.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Correlation-assisted quantized charge pumping

Here, we investigate charge pumping in the vicinity of order-obstructed topological phases, i.e., symmetry-protected topological phases masked by spontaneous symmetry breaking in the presence of strong correlations. To explore this, we study a prototypical Su-Schrieffer-Heeger model with finite-range interaction that gives rise to orbital charge density wave order and characterize the impact of this order on the model's topological properties. In the ordered phase, where the many-body topological invariant loses quantization, we find that not only is quantized charge pumping still possible, but it is even assisted by the collective nature of the orbital charge density wave order. Remarkably, we show that the Thouless pump scenario may be used to uncover the underlying topology of order-obstructed phases.

1-dimensional systems↗