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At least 361 records · Page 20

An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems

The goal of this paper is to solve a class of stochastic optimal control problems numerically, in which the state process is governed by an Itô type stochastic differential equation with control process entering both in the drift and the diffusion, and is observed partially. The optimal control of feedback form is determined based on the available observational data. In this work, we call this type of control problems the data driven feedback control. The computational framework that we introduce to solve such type of problems aims to find the best estimate for the optimal control as a conditional expectation given the observational information. To make our method feasible in providing timely feedback to the controlled system from data, we develop an efficient stochastic optimization algorithm to implement our computational framework.

97 MATHEMATICS AND COMPUTING↗

Tackling the curse of dimensionality in fractional and tempered fractional PDEs with physics-informed neural networks

Fractional and tempered fractional partial differential equations (PDEs) are effective models of long-range interactions, anomalous diffusion, and non-local effects. Traditional numerical methods for these problems are mesh-based, thus struggling with the curse of dimensionality (CoD). Physics-informed neural networks (PINNs) offer a promising solution due to their universal approximation, generalization ability, and mesh-free training. In principle, Monte Carlo fractional PINN (MC-fPINN) estimates fractional derivatives using Monte Carlo methods and thus could lift CoD. However, this may cause significant variance and errors, hence affecting convergence; in addition, MC-fPINN is sensitive to hyperparameters. In general, numerical methods and specifically PINNs for tempered fractional PDEs are under-developed. Herein, we extend MC-fPINN to tempered fractional PDEs to address these issues, resulting in the Monte Carlo tempered fractional PINN (MC-tfPINN). To reduce possible high variance and errors from Monte Carlo sampling, we replace the one-dimensional (1D) Monte Carlo with 1D Gaussian quadrature, applicable to both MC-fPINN and MC-tfPINN. We validate our methods on various forward and inverse problems of fractional and tempered fractional PDEs, scaling up to 100,000 dimensions. Our improved MC-fPINN/MC-tfPINN using quadrature consistently outperforms the original versions in accuracy and convergence speed in very high dimensions.

42 ENGINEERING↗

A multi-phase-field model of topological pattern formation during electrochemical dealloying of binary alloys

Porous metal structures produced by electrochemical dealloying have been extensively studied for use in various applications that require high surface areas. A new comprehensive multi-phase-field (MPF) model is proposed to study topological porous patterns formed by spontaneously etching a bulk binary alloy that involves electrochemical reactions, bulk and surface diffusion, ion transport, applied electrode potential, and charge conservation. The governing equations for the alloy-porous cluster-electrolyte system account for a generalized Butler-Volmer electrochemical reaction and are in accordance with the classical nucleation theory. Based on a quantitative examination of the effects of electrode potential and precursor composition, the simulation results reproduce typical phenomena including passive surface dealloying, active porosity evolution, critical potential, and characteristic length scale in two-dimension (2-D) and three-dimension (3-D). To consider more complicated dealloying systems, the evolutions of a bimodal porous metal structure, nanocomposite, and nested porous network with a structured hierarchy are investigated. Finally, the proposed model can be a useful tool for understanding and predicting the morphology evolution of diverse porous structures during electrochemical dealloying.

Hierarchical porous structure↗

From synchrotrons for XFELs: the soft x-ray near-edge spectrum of the ESCA molecule

A predictive understanding of soft x-ray near-edge absorption spectra of small molecules is an enduring theoretical challenge and of current interest for x-ray probes of molecular dynamics. We report the experimental absorption spectrum for the electron spectroscopy for chemical analysis (ESCA) molecule (ethyl trifluoroacetate) near the carbon 1s absorption edge between 285-300 eV. Furthermore, the ESCA molecule with four chemically distinct carbon sites has previously served as a theoretical benchmark for photoelectron spectra and now for photoabsorption spectra. We report a simple edge-specific approach for systematically expanding standard basis sets to properly describe diffuse Rydberg orbitals and the importance of triple excitations in equation-of-motion coupled-cluster calculations of the energy interval between valence and Rydberg excitations.

74 ATOMIC AND MOLECULAR PHYSICS↗

Predicting the Slowing of Stellar Differential Rotation by Instability-driven Turbulence

Abstract Differentially rotating stars and planets transport angular momentum (AM) internally due to turbulence at rates that have long been a challenge to predict reliably. We develop a self-consistent saturation theory, using a statistical closure approximation, for hydrodynamic turbulence driven by the axisymmetric Goldreich–Schubert–Fricke instability at the stellar equator with radial differential rotation. This instability arises when fast thermal diffusion eliminates the stabilizing effects of buoyancy forces in a system where a stabilizing entropy gradient dominates over the destabilizing AM gradient. Our turbulence closure invokes a dominant three-wave coupling between pairs of linearly unstable eigenmodes and a near-zero frequency, viscously damped eigenmode that features latitudinal jets. We derive turbulent transport rates of momentum and heat and provide them in analytic forms. Such formulae, free of tunable model parameters, are tested against direct numerical simulations; the comparison shows good agreement. They improve upon prior quasi-linear or “parasitic saturation” models containing a free parameter. Given model correspondences, we also extend this theory to heat and compositional transport for axisymmetric thermohaline-instability-driven turbulence in certain regimes.

Astronomy & Astrophysics↗

The role of high-order electron correlation effects in a model system for non-valence correlation-bound anions

The diffusion Monte Carlo (DMC), auxiliary field quantum Monte Carlo (AFQMC), and equation-of-motion coupled cluster (EOM-CC) methods are used to calculate the electron binding energy (EBE) of the non-valence anion state of a model (H2O)4 cluster. Two geometries are considered, one at which the anion is unbound and the other at which it is bound in the Hartree–Fock (HF) approximation. It is demonstrated that DMC calculations can recover from the use of a HF trial wave function that has collapsed onto a discretized continuum solution, although larger EBEs are obtained when using a trial wave function for the anion that provides a more realistic description of the charge distribution and, hence, of the nodal surface. For the geometry at which the cluster has a non-valence correlation-bound anion, both the inclusion of triples in the EOM-CC method and the inclusion of supplemental diffuse d functions in the basis set are important. DMC calculations with suitable trial wave functions give EBE values in good agreement with our best estimate EOM-CC result. AFQMC using a trial wave function for the anion with a realistic electron density gives a value of the EBE nearly identical to the EOM-CC result when using the same basis set. For the geometry at which the anion is bound in the HF approximation, the inclusion of triple excitations in the EOM-CC calculations is much less important. The best estimate EOM-CC EBE value is in good agreement with the results of DMC calculations with appropriate trial wave functions.

Upadhyay, Shiv (ORCID:0000000285010501)↗

Spatiotemporal Crossover between Low- and High-Temperature Dynamical Regimes in the Quantum Heisenberg Magnet

The stranglehold of low temperatures on fascinating quantum phenomena in one-dimensional quantum magnets has been challenged recently by the discovery of anomalous spin transport at high temperatures. Whereas both regimes have been investigated separately, no study has attempted to reconcile them. For instance, the paradigmatic quantum Heisenberg spin-$1/2$ chain falls at low-temperature within the Tomonaga-Luttinger liquid framework, while its high-temperature dynamics is superdiffusive and relates to the Kardar-Parisi-Zhang universality class in $1+1$ dimensions. This work aims at reconciling the two regimes. Building on large-scale matrix product state simulations, we find that they are connected by a temperature-dependent spatiotemporal crossover. In this work, as the temperature $T$ is reduced, we show that the onset of superdiffusion takes place at longer length and time scales $\propto 1/T$. This prediction has direct consequences for experiments including nuclear magnetic resonance: it is consistent with earlier measurements on the nearly ideal Heisenberg $S=1/2$ chain compound Sr$_2$CuO$_3$ yet calls for new and dedicated experiments.

1-dimensional spin chains↗

Capturing membrane structure and function in lattice Boltzmann models

Here, we develop a mesoscopic approach to model the nonequilibrium behavior of membranes at the cellular scale. Relying on lattice Boltzmann methods, we develop a solution procedure to recover the Nernst-Planck equations and Gauss's law. A general closure rule is developed to describe mass transport across the membrane, which is able to account for protein-mediated diffusion based on a coarse-grained representation. We demonstrate that our model is able to recover the Goldman equation from first principles and show that hyperpolarization occurs when membrane charging dynamics are controlled by multiple relaxation timescales. The approach provides a promising way to characterize non-equilibrium behaviors that arise due to the role of membranes in mediating transport based on realistic three-dimensional cell geometries.

59 BASIC BIOLOGICAL SCIENCES↗

Kinetic Monte Carlo simulations of aging in δ -Pu

We have developed a first-passage kinetic Monte Carlo approach for materials aging to investigate the sensitivity of void swelling to model parameters, including helium bubble density and size distribution. In addition to explicitly accounting for the spatial distribution of individual point defects, bubbles, and voids, our approach can simulate total doses equivalent to 100 years of natural aging on statistically representative volumes of materials. This technique enables us to study the effects on swelling and radiation damage evolution due to temperature and dose rate (as altered in artificially aged experiments), differences in effective interaction radii between vacancies and interstitials, and varying defect diffusion activation energies, while providing more detailed information than previous rate-equation based approaches. In conclusion, our results indicate that spatial effects that are not modeled in mean-field rate theories could play a significant role in void swelling initiation and growth for certain regimes of model parameters.

Actinides↗

Hydro-chemo-mechanical phase field formulation for corrosion induced cracking in reinforced concrete

Steel corrosion induced cracking in reinforced concrete structures is often caused by volumetric straining at the steel-concrete interface. This volumetric strain is mainly controlled by the rate of generation of corrosion product, which depends on the diffusion of Cl{sup −} and dissolved O{sub 2} as well as the chemical reaction at the steel-concrete interface. While many numerical modeling techniques have been proposed to tackle this complex phenomenon, most have been limited to using staggered solution schemes, where the diffusion, chemical reaction, mechanical strain, and crack fields are solved for separately. Unfortunately, such approaches introduce numerical errors that can lead to unrealistic predictions. Therefore, a coupled solution, is needed to remove the formulation induced errors and understand this complex phenomenon. To provide a unifying solution framework for corrosion induced cracking in reinforced concrete, a phase field formulation is presented and implemented with FEM algorithms. The governing equations are derived from the system's free energy and Fick's law of diffusion. The proposed formulation was first validated in 1D by comparing the modeling results with the semi-analytical solution approximated via Laurent series to avoid singularities in the complex domain. 2D plane strain solutions to the embedded rebar undergoing corrosion induced cracking with pre-cracks are also presented and compared with the approximated solutions from linear elastic fracture mechanics theory (LEFM). The modeling of crack propagation enabled by the proposed formulation is also presented along with parametric studies to reveal the roles of the fracture toughness and permeability of the concrete on the corrosion induced cracking. A case study was also conducted on H-pile steel with concrete jackets to demonstrate the feasibility of modeling corrosion induced fracture in reinforced concrete structures with complex steel-concrete interfaces.

36 MATERIALS SCIENCE↗

Efficient quadrature rules for finite element discretizations of nonlocal equations

Here, in this paper, we design efficient quadrature rules for finite element (FE) discretizations of nonlocal diffusion problems with compactly supported kernel functions. Two of the main challenges in nonlocal modeling and simulations are the prohibitive computational cost and the nontrivial implementation of discretization schemes, especially in three-dimensional settings. In this work, we circumvent both challenges by introducing a parametrized mollifying function that improves the regularity of the integrand, utilizing an adaptive integration technique, and exploiting parallelization. We first show that the “mollified” solution converges to the exact one as the mollifying parameter vanishes, then we illustrate the consistency and accuracy of the proposed method on several two- and three-dimensional test cases. Furthermore, we demonstrate the good scaling properties of the parallel implementation of the adaptive algorithm and we compare the proposed method with recently developed techniques for efficient FE assembly.

97 MATHEMATICS AND COMPUTING↗

Flame acceleration and transition to detonation in a pre-/main-chamber combustion system

Numerical simulations are performed to study the mechanism of deflagration to detonation transition (DDT) in a pre-/main-chamber combustion system with a stoichiometric ethylene–oxygen mixture. A Godunov algorithm, fifth-order in space, and third-order in time, is used to solve the fully compressible Navier–Stokes equations on a dynamically adapting mesh. A single-step, calibrated chemical diffusive model described by Arrhenius kinetics is used for energy release and conservation between the fuel and the product. The two-dimensional simulation shows that a laminar flame grows in the pre-chamber and then develops into a jet flame as it passes through the orifice. A strong shock forms immediately ahead of the flame, reflecting off the walls and interacting with the flame front. The shock–flame interactions are crucial for the development of flame instabilities, which trigger the subsequent flame development. The DDT arises due to a shock-focusing mechanism, where multiple shocks collide at the flame front. A chemical explosive mode analysis (CEMA) criterion is developed to study the DDT ignition mode. Preliminary one-dimensional computations for a laminar propagating flame, a fast flame deflagration, and a Chapman–Jouguet detonation are conducted to demonstrate the validity of CEMA on the chemical-diffusive model, as well as to determine the proper conditioning value for CEMA diagnostic. The two-dimensional analysis with CEMA indicates that the DDT initiated by the shock-focusing mechanism can form a strong thermal expansion region at the flame front that features large positive eigenvalues for the chemical explosive mode and dominance of the local autoignition mode. Thus, the CEMA criterion proposed in this study provides a robust diagnostic for identifying autoignition-supported DDT, of which the emergence of excessive local autoignition mode is found to be a precursor. The effect of grid size, initial temperature, and orifice size are then evaluated, and results show that although the close-chamber DDT is highly stochastic, the detonation initiation mechanism remains robust.

42 ENGINEERING↗

Stable Solid Molecular Hydrogen above 900 K from a Machine-Learned Potential Trained with Diffusion Quantum Monte Carlo

Here, we survey the phase diagram of high-pressure molecular hydrogen with path integral molecular dynamics using a machine-learned interatomic potential trained with quantum Monte Carlo forces and energies. Besides the HCP and C2/c–24 phases, we find two new stable phases both with molecular centers in the Fmmm–4 structure, separated by a molecular orientation transition with temperature. The high temperature isotropic Fmmm–4 phase has a reentrant melting line with a maximum at higher temperature (1450 K at 150 GPa) than previously estimated and crosses the liquid-liquid transition line around 1200 K and 200 GPa.

08 HYDROGEN↗

Shot noise and universal Fano factor as a characterization of strongly correlated metals

Shot noise measures out-of-equilibrium current fluctuations and is a powerful tool to probe the nature of current-carrying excitations in quantum systems. Recent shot-noise measurements in the heavy-fermion strange metal YbRh 2 Si 2 exhibit a strong suppression of the Fano factor ( F )—the ratio of the current noise to the average current in the dc limit. This system is representative of metals in which electron correlations are extremely strong. Here we carry out the first theoretical study on the shot noise of diffusive metals in the regime of strong correlations. A Boltzmann-Langevin equation formulation is constructed in a quasiparticle description in the presence of strong correlations. We find that F = 3 / 4 in such a correlation regime. Thus, we establish the aforementioned Fano factor as universal to Fermi liquids, and we show that the Fano factor suppression observed in experiments on YbRh 2 Si 2 necessitates a loss of the quasiparticles. Our work opens the door to systematic theoretical studies of shot noise as a means of characterizing strongly correlated metallic phases and materials. Published by the American Physical Society 2024

Wang, Yiming (ORCID:0000000277582921)↗

Smoothed boundary method for simulating incompressible flow in complex geometries

Simulating flow through porous media with explicit considerations of complex microstructures is very challenging using conventional sharp-interface methods because of the difficulties in generating meshes conformal to complex geometries. In this work, a diffuse interface embedded boundary method known as the Smoothed Boundary Method (SBM) is utilized to facilitate simulations of fluid dynamics involving complex geometries. In diffuse-interface methods, the geometry is described by a domain parameter. The SBM allows the straightforward reformulation of the time-dependent Navier-Stokes equations in terms of this domain parameter, using only algebraic identities. Thus, enforcing the appropriate boundary conditions at the irregular embedded boundary is greatly simplified. Adaptive mesh refinement is used to increase the accuracy of the diffuse interface method by allowing thinner interfacial thickness to be used in the domain parameter. Here, the SBM-formulated Navier-Stokes equations are solved with the Finite Difference Method on refined mesh systems. Sharp-interface Finite Element Method simulations using the commercial software COMSOL on body-conforming meshes are also provided for comparison. Favorable agreement between the two methods is observed. Since it is no longer necessary for the mesh to conform to the complex geometry, the grid system for the SBM simulations can be generated rapidly and without additional manual interventions, making the entire simulation process more expedient.

36 MATERIALS SCIENCE↗

Measurement and modeling of methane diffusion in hydrocarbon mixtures

Methane (CH 4 ) dissolution and diffusive mass transfer in liquid hydrocarbon mixtures is of key interest in the context of enhanced oil recovery from tight shales. In this paper, we have studied CH 4 dissolution and diffusion in normal alkane mixtures at a temperature of 50 ⁰C and at pressures of ~8 MPa. For the measurement of CH 4 dissolution/diffusion in bulk liquid hydrocarbon mixtures, we have utilized a high pressure and temperature, constant-volume diffusion (CV-D) setup. Here, we have studied CH 4 diffusion in mixtures with three long-chain normal alkanes: decane (C 10 ), dodecane (C 12 ) and hexadecane (C 16 ). We have measured CH 4 solubility and diffusion in its binary mixtures with each of these three normal alkanes, as well as in ternary and quaternary mixtures. During the experiments, the swelling of the liquid mixture due to CH 4 dissolution was measured in situ via a cathetometer and was subsequently integrated into the data analysis. A key conclusion from this study is that the solubility and transport properties of the multicomponent mixtures can be predicted accurately from binary mixture measurements using an appropriate Equation of State (EOS) and Wilke’s simplification of the classical Maxwell-Stefan (MS) diffusion theory. This observation can facilitate accurate prediction of diffusive mass transfer in more complex liquid hydrocarbon mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pressure-induced phase transition in barium hydride studied with neutron scattering

Barium hydride can undergo a structural phase transition from an orthorhombic phase to a hexagonal phase induced by high temperature or high pressure. This transition causes an immediate increase in the hydrogen diffusion rates by over an order of magnitude, and therefore, understanding the origin and details of such transition is of great interest not only for fundamental reasons but also for improving materials for future applications. In this work, the pressure evolution of the crystal structure was characterized using neutron powder diffraction up to a maximum pressure of 11.3 GPa. The pressure dependence of the unit cell volumes, lattice parameters, atomic sites, and compressibilities were determined for both phases. A structural phase transition occurred over a wide pressure range of P = 1.3 GPa–4.9 GPa. The transition to the higher density hexagonal phase reduced the volume per formula unit of BaD 2 by 13.6%, hence increasing the volumetric storage density. In addition, we investigated the hydrogen diffusion process using high pressure quasi-elastic neutron scattering up to 7.1 GPa. Our results show that the hydrogen mobility increases with pressure in the hexagonal phase. This work sheds light on the structural and dynamical aspects of barium hydride caused by the application of high pressure. Finally, the results may aid in the development of advanced metal hydride systems with increased hydrogen dynamics.

36 MATERIALS SCIENCE↗