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At least 649 records · Page 36

On the continuity of mean total normal stress in geometrical multiscale cardiovascular problems

In this work an iterative strategy to implicitly couple dimensionally-heterogeneous blood flow models accounting for the continuity of mean total normal stress at interface boundaries is developed. Conservation of mean total normal stress in the coupling of heterogeneous models is mandatory to satisfy energetic consistency between them. Nevertheless, existing methodologies are based on modifications of the Navier–Stokes variational formulation, which are undesired when dealing with fluid–structure interaction or black box codes. The proposed methodology makes possible to couple one-dimensional and three-dimensional fluid–structure interaction models, enforcing the continuity of mean total normal stress while just imposing flow rate data or even the classical Neumann boundary data to the models. This is accomplished by modifying an existing iterative algorithm, which is also able to account for the continuity of the vessel area, when required. Comparisons are performed to assess differences in the convergence properties of the algorithms when considering the continuity of mean normal stress and the continuity of mean total normal stress for a wide range of flow regimes. Finally, examples in the physiological regime are shown to evaluate the importance, or not, of considering the continuity of mean total normal stress in hemodynamics simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A new Green's function Monte Carlo algorithm for the solution of the two-dimensional nonlinear Poisson–Boltzmann equation: Application to the modeling of the communication breakdown problem in space vehicles during re-entry

The objective of this paper is the exposition of a recently-developed, novel Green's function Monte Carlo (GFMC) algorithm for the solution of nonlinear partial differential equations and its application to the modeling of the plasma sheath region around a cylindrical conducting object, carrying a potential and moving at low speeds through an otherwise neutral medium. The plasma sheath is modeled in equilibrium through the GFMC solution of the nonlinear Poisson–Boltzmann (NPB) equation. The traditional Monte Carlo based approaches for the solution of nonlinear equations are iterative in nature, involving branching stochastic processes which are used to calculate linear functionals of the solution of nonlinear integral equations. Over the last several years, one of the authors of this paper, K. Chatterjee has been developing a philosophically-different approach, where the linearization of the equation of interest is not required and hence there is no need for iteration and the simulation of branching processes. Instead, an approximate expression for the Green's function is obtained using perturbation theory, which is used to formulate the random walk equations within the problem sub-domains where the random walker makes its walks. However, as a trade-off, the dimensions of these sub-domains have to be restricted by the limitations imposed by perturbation theory. The greatest advantage of this approach is the ease and simplicity of parallelization stemming from the lack of the need for iteration, as a result of which the parallelization procedure is identical to the parallelization procedure for the GFMC solution of a linear problem. The application area of interest is in the modeling of the communication breakdown problem during a space vehicle's re-entry into the atmosphere. However, additional application areas are being explored in the modeling of electromagnetic propagation through the atmosphere/ionosphere in UHF/GPS applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Variational Bayesian strategies for high-dimensional, stochastic design problems

This paper is concerned with a lesser-studied problem in the context of model-based, uncertainty quantification (UQ), that of optimization/design/control under uncertainty. The solution of such problems is hindered not only by the usual difficulties encountered in UQ tasks (e.g. the high computational cost of each forward simulation, the large number of random variables) but also by the need to solve a nonlinear optimization problem involving large numbers of design variables and potentially constraints. We propose a framework that is suitable for a class of such problems and is based on the idea of recasting them as probabilistic inference tasks. To that end, we propose a Variational Bayesian (VB) formulation and an iterative VB–Expectation-Maximization scheme that is capable of identifying a local maximum as well as a low-dimensional set of directions in the design space, along which, the objective exhibits the largest sensitivity. We demonstrate the validity of the proposed approach in the context of two numerical examples involving thousands of random and design variables. In all cases considered the cost of the computations in terms of calls to the forward model was of the order of 100 or less. The accuracy of the approximations provided is assessed by information-theoretic metrics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Modeling and simulation challenges pursued by the Consortium for Advanced Simulation of Light Water Reactors (CASL)

The Consortium for the Advanced Simulation of Light Water Reactors (CASL), the first Energy Innovation Hub of the Department of Energy, was established in 2010 with the goal of providing modeling and simulation (M&S) capabilities that support and accelerate the improvement of nuclear energy's economic competitiveness and the reduction of spent nuclear fuel volume per unit energy, and all while assuring nuclear safety. To accomplish this requires advances in M&S capabilities in radiation transport, thermal-hydraulics, fuel performance and corrosion chemistry. To focus CASL's R&D, industry challenge problems have been defined, which equate with long standing issues of the nuclear power industry that M&S can assist in addressing. To date CASL has developed a multi-physics “core simulator” based upon pin-resolved radiation transport and subchannel (within fuel assembly) thermal-hydraulics, capitalizing on the capabilities of high performance computing. CASL's fuel performance M&S capability can also be optionally integrated into the core simulator, yielding a coupled multi-physics capability with untapped predictive potential. Material models have been developed to enhance predictive capabilities of fuel clad creep and growth, along with deeper understanding of zirconium alloy clad oxidation and hydrogen pickup. Understanding of corrosion chemistry (e.g., CRUD formation) has evolved at all scales: micro, meso and macro. CFD R&D has focused on improvement in closure models for subcooled boiling and bubbly flow, and the formulation of robust numerical solution algorithms. For multiphysics integration, several iterative acceleration methods have been assessed, illuminating areas where further research is needed. Finally, uncertainty quantification and data assimilation techniques, based upon sampling approaches, have been made more feasible for practicing nuclear engineers via R&D on dimensional reduction and biased sampling. Industry adoption of CASL's evolving M&S capabilities, which is in progress, will assist in addressing long-standing and future operational and safety challenges of the nuclear industry. - Highlights: • Complexity of physics based modeling of light water reactor cores being addressed. • Capability developed to help address problems that have challenged the nuclear power industry. • Simulation capabilities that take advantage of high performance computing developed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

An algorithm for computing the 2D structure of fast rotating stars

Stars may be understood as self-gravitating masses of a compressible fluid whose radiative cooling is compensated by nuclear reactions or gravitational contraction. The understanding of their time evolution requires the use of detailed models that account for a complex microphysics including that of opacities, equation of state and nuclear reactions. The present stellar models are essentially one-dimensional, namely spherically symmetric. However, the interpretation of recent data like the surface abundances of elements or the distribution of internal rotation have reached the limits of validity of one-dimensional models because of their very simplified representation of large-scale fluid flows. In this article, we describe the ESTER code, which is the first code able to compute in a consistent way a two-dimensional model of a fast rotating star including its large-scale flows. Compared to classical 1D stellar evolution codes, many numerical innovations have been introduced to deal with this complex problem. First, the spectral discretization based on spherical harmonics and Chebyshev polynomials is used to represent the 2D axisymmetric fields. A nonlinear mapping maps the spheroidal star and allows a smooth spectral representation of the fields. The properties of Picard and Newton iterations for solving the nonlinear partial differential equations of the problem are discussed. It turns out that the Picard scheme is efficient on the computation of the simple polytropic stars, but Newton algorithm is unsurpassed when stellar models include complex microphysics. Finally, we discuss the numerical efficiency of our solver of Newton iterations. This linear solver combines the iterative Conjugate Gradient Squared algorithm together with an LU-factorization serving as a preconditioner of the Jacobian matrix.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Implicit filtered P{sub N} for high-energy density thermal radiation transport using discontinuous Galerkin finite elements

In this work, we provide a fully-implicit implementation of the time-dependent, filtered spherical harmonics (FP{sub N}) equations for non-linear, thermal radiative transfer. We investigate local filtering strategies and analyze the effect of the filter on the conditioning of the system, showing in particular that the filter improves the convergence properties of the iterative solver. We also investigate numerically the rigorous error estimates derived in the linear setting, to determine whether they hold also for the non-linear case. Finally, we simulate a standard test problem on an unstructured mesh and make comparisons with implicit Monte Carlo (IMC) calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Acceptability of Iterative Reconstruction Algorithms in Head CT: An Assessment of Sinogram Affirmed Iterative Reconstruction (SAFIRE) vs. Filtered Back Projection (FBP) Using Phantoms

Computed tomography (CT) is the primary imaging investigation for many neurologic conditions with a proportion of patients incurring cumulative doses. Iterative reconstruction (IR) allows dose optimization, but head CT presents unique image quality complexities and may lead to strong reader preferences.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Inducing polarity in [VO{sub 3}]{sub n}{sup n-} chain compounds using asymmetric hydrogen-bonding networks

1,4-Bis(3-aminopropyl)piperazine, (R)-3-aminopiperidine and (S)-3-aminopiperidine were used in the syntheses of [C{sub 10}H{sub 26}N{sub 4}][VO{sub 3}]{sub 2}{center_dot}2H{sub 2}O, [(R)-C{sub 5}H{sub 14}N{sub 2}][VO{sub 3}]{sub 2} and [(S)-C{sub 5}H{sub 14}N{sub 2}][VO{sub 3}]{sub 2}, which all contain similar [VO{sub 3}]{sub n}{sup n-} chains. Inversion symmetry within the 1,4-bis(3-aminopropyl)piperazine allows for crystallization of [C{sub 10}H{sub 26}N{sub 4}][VO{sub 3}]{sub 2}{center_dot}2H{sub 2}O in a centrosymmetric space group, while the use of enantiomerically pure sources of either (R)-3-aminopiperidine or (S)-3-aminopiperidine forces crystallographic noncentrosymmetry. Moreover, asymmetry in the hydrogen-bonding networks between the metavanadate chains and either [(R)-3-aminopiperidineH{sub 2}]{sup 2+} or [(S)-3-aminopiperidineH{sub 2}]{sup 2+} cations directs alignment of the chains and crystallization in a polar space group (C2, no. 5). Component and net dipole moments were calculated using iterative-Hirshfeld partial atomic charges. [(R)-C{sub 5}H{sub 14}N{sub 2}][VO{sub 3}]{sub 2} and [(S)-C{sub 5}H{sub 14}N{sub 2}][VO{sub 3}]{sub 2} both display type 1 phase-matching capabilities and exhibit second harmonic generation activities of {approx}140 Multiplication-Sign {alpha}-SiO{sub 2}. - Graphical abstract: One centrosymmetric and a pair of polar noncentrosymmetric templated metavanadates were synthesized under mild hydrothermal conditions. Asymmetry in the hydrogen-bonding between either [(R)-C{sub 5}H{sub 14}N{sub 2}]{sup 2+} or [(S)-C{sub 5}H{sub 14}N{sub 2}]{sup 2+} and [VO{sub 3}]{sub n}{sup n-} chains results in polar structures that exhibit type 1 phase-matching capabilities. Hirshfeld surfaces were used to probe the hydrogen-bonding networks and component and net dipole moments were calculated from atomic positions and iterative-Hirshfeld partial charges. Highlights: Black-Right-Pointing-Pointer One centrosymmetric and a pair of polar templated metavanadate chain compounds are reported. Black-Right-Pointing-Pointer Asymmetry in the hydrogen-bonding networks drives the compound polarities. Black-Right-Pointing-Pointer Iterative-Hirshfeld partitioning was used to calculate partial atomic charges. Black-Right-Pointing-Pointer Net and component dipole moments are calculated for each compound. Black-Right-Pointing-Pointer Type 1 phase-matching behavior and SHG activities of {approx}140 Multiplication-Sign {alpha}-SiO{sub 2} are found.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flexible all-carbon photovoltaics with improved thermal stability

The structurally robust nature of nanocarbon allotropes, e.g., semiconducting single-walled carbon nanotubes (SWCNTs) and C{sub 60}s, makes them tantalizing candidates for thermally stable and mechanically flexible photovoltaic applications. However, C{sub 60}s rapidly dissociate away from the basal of SWCNTs under thermal stimuli as a result of weak intermolecular forces that “lock up” the binary assemblies. Here, we explore use of graphene nanoribbons (GNRs) as geometrically tailored protecting layers to suppress the unwanted dissociation of C{sub 60}s. The underlying mechanisms are explained using a combination of molecular dynamics simulations and transition state theory, revealing the temperature dependent disassociation of C{sub 60}s from the SWCNT basal plane. Our strategy provides fundamental guidelines for integrating all-carbon based nano-p/n junctions with optimized structural and thermal stability. External quantum efficiency and output current–voltage characteristics are used to experimentally quantify the effectiveness of GNR membranes under high temperature annealing. Further, the resulting C{sub 60}:SWCNT:GNR ternary composites display excellent mechanical stability, even after iterative bending tests. - Graphical abstract: The incorporation of solvent resistant, mechanically flexible and electrically addressable 2-D soft graphene nanoribbons facilitates the assembly of photoconductive carbon nano-p/n junctions for thermally stable and flexible photovoltaic cells.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Proton discrimination in CLYC for fast neutron spectroscopy

The Cs 2 LiYCl 6 :Ce (CLYC) elpasolite scintillator is known for its response to fast and thermal neutrons along with good γ-ray energy resolution. While the 35 Cl(n,p) reaction has been identified as a potential means for CLYC-based fast neutron spectroscopy in the absence of time-of-flight (TOF), previous efforts to functionalize CLYC as a fast neutron spectrometer have been thwarted by the inability to isolate proton interactions from 6 Li(n,α) and 35 Cl(n,α) signals. This work introduces a new approach to particle discrimination in CLYC for fission spectrum neutrons using a multi-gate charge integration algorithm that provides excellent separation between protons and heavier charged particles. Neutron TOF data were collected using a 252 Cf source, an array of EJ-309 organic liquid scintillators, and a 6 Li-enriched CLYC scintillator outfitted with fast electronics. Modal waveforms were constructed corresponding to the different reaction channels, revealing significant differences in the pulse characteristics of protons and heavier charged particles at ultrafast, fast, and intermediate time scales. These findings informed the design of a pulse shape discrimination algorithm, which was validated using the TOF data. This study also proposes an iterative subtraction method to mitigate contributions from confounding reaction channels in proton and heavier charged particle pulse height spectra, opening the door for CLYC-based fast neutron and γ-ray spectroscopy while preserving sensitivity to thermal neutron capture signals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Advanced two-phase subchannel method via non-linear iteration

A fast-running, robust two-phase flow, sub-channel model is presented based on non-linear solution of the steady-state subchannel fluid flow equations. The drift-flux model solves for conservation of liquid and vapor mass, mixture energy, and axial and transverse mixture momentum as part of an efficient planar marching scheme and nonlinear, nested outer and inner iteration. Here, models based on mechanistic subcooled boiling, two-phase turbulent void mixing, and drift are included. Solution verification and mesh convergence studies were performed for modern GE 10 × 10 fuel geometry and are shown to have excellent convergence behavior. Run time performance for a 50 axial mesh model showed 2.2 seconds on a single CPU core to tightly converge all 3D distributions (flow, void, pressure) for the GE 10 × 10 fuel geometry, supporting its efficient use within the Virtual Environment for Reactor Applications boiling water reactor framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Probing the role of solids loading and mix procedure on the properties of acoustically mixed materials for additive manufacturing

We report resonant acoustic mixing has been of particular interest for use in additive manufacturing since viscous, solids-loaded materials can be difficult to mix and inhomogeneity has adverse effects on print quality. In this study, we detail a method to iterate through different formulations and mix procedures and assess mixture quality. The approach utilizes a constant pressure-driven flow test to collect statistics on flow rate through a standard geometry. This test is first applied to well mixed formulations containing particulate solids and find that the results are sensitive to viscosity produced by solids content. We then consider the formulations at various stages of mixing and find that the spread in the volume measurements is indicative of the mixing quality; poorly mixed material yields measurements with wide distributions. We believe this testing approach can be useful when screening new formulations, developing mixing processes, or for quality control.

36 MATERIALS SCIENCE↗

Multireference Equation-of-Motion Driven Similarity Renormalization Group: Theoretical Foundations and Applications to Ionized States

We present a formulation and implementation of an equation-of-motion (EOM) extension of the multireference driven similarity renormalization group (MR-DSRG) formalism for ionization potentials (IP-EOM-DSRG). The IP-EOM-DSRG formalism results in a Hermitian generalized eigenvalue problem, delivering accurate ionization potentials for strongly correlated systems. The EOM step scales as O(N 5 ) with the basis set size N, allowing for efficient calculation of spectroscopic properties, such as transition energies and intensities. The IP-EOM-DSRG formalism is combined with three truncation schemes of the parent MR-DSRG theory: an iterative nonperturbative method with up to two-body excitations [MR-LDSRG(2)] and second- and third-order perturbative approximations [DSRG-MRPT2/3]. We benchmark these variants by computing (1) the vertical valence ionization potentials of a series of small molecules at both equilibrium and stretched geometries; (2) the spectroscopic constants of several low-lying electronic states of the OH, CN, N 2 + , and CO + radicals; and (3) the binding curves of low-lying electronic states of the CN radical. A comparison with experimental data and theoretical results shows that all three IP-EOM-DSRG methods accurately reproduce the vertical ionization potentials and spectroscopic constants of these systems. Notably, the DSRG-MRPT3 and MR-LDSRG(2) versions outperform several state-of-the-art multireference methods of comparable or higher cost.

Hamiltonians↗

Firefly Algorithm Applied to Noncollinear Magnetic Phase Materials Prediction

In most noncollinear crystal magnets, the number of metastable states is quite large and any calculation that tries to predict the ground state can fall into one of the possible metastable phases. In this work, we generalize the population based meta-heuristic firefly algorithm to the problem of the noncollinear magnetic phase ground state prediction within density functional theory (DFT). We extend the different steps in the firefly algorithm to this specific problem by using polarized constrained DFT calculations, whereby using Lagrange multipliers the directions of the atom magnetic moments remain fixed. By locking the directions of the magnetic moments at each search iteration, the method allows one to explore the entire Born–Oppenheimer energy surface of existing and physically plausible noncollinear configurations present in a crystal. Finally, we demonstrate that the number of minima can be large, which restrains the use of exhaustive searches.

Algorithms↗

Chirality Amplified: Long, Discrete Helicene Nanoribbons

Here we report the synthesis of two polyhelicene frameworks consisting, from end-to-end, of 18 and 24 fused benzene rings. The latter exhibits the largest electronic circular dichroism in the visible spectrum of any molecule. These shape-persistent helical nanoribbons incorporate multiple helicenes, a class of contorted polycyclic aromatic molecules consisting of ortho-annulated rings. These conjugated, chiral molecules have interesting chemical, biological, and chiroptical properties; however, there are very few helicenes with extraordinary chiroptical response over a broad range of the visible spectrum—a key criterion for applications such as chiral optoelectronics. In this report, we show that coupling the polyhelicene framework with multiple perylene-diimide subunits elicits a significant chiroptic response. Notably, the molar circular dichroism increases faster than the absorptivity of these molecules as their helical axis lengthens. Computational analysis reveals that the greatly amplified circular dichroism arises from exciton-like interactions between the perylene-diimide and the helicene moieties. As a result, we predict that even greater chiroptic enhancement will result from further axial elongation of these nanoribbons, which can be readily enabled via the iterative synthetic method presented herein.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Long-time simulations for fixed input states on quantum hardware

Publicly accessible quantum computers open the exciting possibility of experimental dynamical quantum simulations. While rapidly improving, current devices have short coherence times, restricting the viable circuit depth. Despite these limitations, we demonstrate long-time, high fidelity simulations on current hardware. Specifically, we simulate an XY-model spin chain on Rigetti and IBM quantum computers, maintaining a fidelity over 0.9 for 150 times longer than is possible using the iterated Trotter method. Our simulations use an algorithm we call fixed state Variational Fast Forwarding (fsVFF). Recent work has shown an approximate diagonalization of a short time evolution unitary allows a fixed-depth simulation. fsVFF substantially reduces the required resources by only diagonalizing the energy subspace spanned by the initial state, rather than over the total Hilbert space. We further demonstrate the viability of fsVFF through large numerical simulations, and provide an analysis of the noise resilience and scaling of simulation errors.

97 MATHEMATICS AND COMPUTING↗

Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography

Obtaining high-quality 3D reconstructions from electron tomography of crystalline particles embedded in lighter support elements is crucial for various material systems such as catalysts for fuel cell applications. However, significant challenges arise due to the limited tilt range, sparse and low signal-to-noise ratio of the measurements. In addition, small metal particles can cause strong streaking and shading artifacts in the 3D reconstructions when using conventional reconstruction algorithms due to the presence of Bragg diffraction and the large scattering cross-section difference between the materials of the particles and the background support regions. These artifacts lead to errors in the downstream characterization affecting extraction of critical features such as the size of the metal particles, their distribution and the volume of the lighter support regions. In this paper, we present a two-stage algorithm based on metal artifact reduction, utilizing model-based iterative reconstruction methods with adaptive adjustment of regularization parameters. Our approach yields high-quality 3D reconstructions compared to traditional algorithms, accurately capturing both the metal particles as well as the background support. We demonstrate the effectiveness of our algorithm through simulated and experimental bright-field electron tomography data, showing significant improvements in reconstruction quality compared to traditional methods.

97 MATHEMATICS AND COMPUTING↗