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At least 793 records · Page 44

Accelerating structural dynamics simulations with localised phenomena through matrix compression and projection‐based model order reduction

In this work, a novel approach is introduced for accelerating the solution of structural dynamics problems in the presence of localised phenomena, such as cracks. For this category of problems, conventional projection-based Model Order Reduction (MOR) methods are either limited with respect to the range of system configurations that can be represented or require frequent solutions of the Full Order Model (FOM) to update the low-dimensional spaces, in which solutions are represented. In the proposed approach, low-dimensional spaces, constructed for the healthy structure, are enriched with appropriately selected columns of the flexibility matrix of the system. It can be shown that these spaces contain the solution to the original problem for the static case, while their dimension is much smaller. In order to allow their online construction for arbitrary localised features, the full flexibility matrix of the system should be available. To this end, a hierarchical representation is used for the matrices involved, allowing to compute the flexibility matrix efficiently and with reduced memory requirements. The resulting method offers significant speedups, without sacrificing the flexibility and accuracy of the full order model. The performance and limitations of the approach are studied through a series of examples in structural dynamics.

fracture mechanics↗

Ab initio molecular dynamics simulation of Na-doped aluminosilicate glasses and glass-water interaction

The structure and properties of sodium aluminosilicate (NAS) glasses are investigated using ab initio molecular dynamics and density functional calculations. Four NAS glass models of about 700 atoms with composition (SiO 2 ) 0.6 (Al 2 O 3 ) 0.4-x (Na 2 O) x with Na/Al ratio R = 0.0, 0.5, 1.0 and 1.5 are constructed corresponding to x = 0, 0.135, 0.20 and 0.24. Detailed information on network coordination, electronic structure, interatomic bonding and partial charge distribution, mechanical and optical properties of these models are presented and fully analyzed. The structural details for each R are discussed in terms of short- and intermediate-range order manifested in the coordination number, atomic pair and bond angle distributions. It is shown that the mechanical strength of NAS glasses decreases with increasing Na content, indicating that pure aluminosilicate glass is stronger than the alkali-doped glasses. We use the novel concept of total bond order density to characterize the internal cohesion of the NAS glasses. In the case of R = 1 NAS model, 12 water molecules are added to investigate the solvation effect and hydrolysis in NAS glass.

36 MATERIALS SCIENCE↗

Multi-scaled normal mode analysis method for dynamics simulation of protein-membrane complexes: A case study of potassium channel gating motion correlations

Membrane proteins play critically important roles in many cellular activities such as ions and small molecule transportation, signal recognition, and transduction. In order to fulfill their functions, these proteins must be placed in different membrane environments and a variety of protein-lipid interactions may affect the behavior of these proteins. One of the key effects of protein-lipid interactions is their ability to change the dynamics status of membrane proteins, thus adjusting their functions. Here, we present a multi-scaled normal mode analysis (mNMA) method to study the dynamics perturbation to the membrane proteins imposed by lipid bi-layer membrane fluctuations. In mNMA, channel proteins are simulated at all-atom level while the membrane is described with a coarse-grained model. mNMA calculations clearly show that channel gating motion can tightly couple with a variety of membrane deformations, including bending and twisting. We then examined bi-channel systems where two channels were separated with different distances. From mNMA calculations, we observed both positive and negative gating correlations between two neighboring channels, and the correlation has a maximum as the channel center-to-center distance is close to 2.5 times of their diameter. This distance is larger than recently found maximum attraction distance between two proteins embedded in membrane which is 1.5 times of the protein size, indicating that membrane fluctuation might impose collective motions among proteins within a larger area. The hybrid resolution feature in mNMA provides atomic dynamics information for key components in the system without costing much computer resource. We expect it to be a conventional simulation tool for ordinary laboratories to study the dynamics of very complicated biological assemblies. The source code is available upon request to the authors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Alternative Frictional Boundary Condition for Computational Fluid Dynamics Simulation of Friction Stir Welding

For better application of numerical simulation in optimization and design of friction stir welding (FSW), this paper presents a new frictional boundary condition at the tool/workpiece interface for computational fluid dynamics (CFD) modeling of FSW. The proposed boundary condition is based on an implementation of the Coulomb friction model. Using the new boundary condition, the CFD simulation yields non-uniform distribution of contact state over the tool/workpiece interface, as validated by the experimental weld macrostructure. It is found that interfacial sticking state is present over large area at the tool-workpiece interface, while significant interfacial sliding occurs at the shoulder periphery, the lower part of pin side, and the periphery of pin bottom. Due to the interfacial sticking, a rotating flow zone is found under the shoulder, in which fast circular motion occurs. The diameter of the rotating flow zone is smaller than the shoulder diameter, which is attributed to the presence of the interfacial sliding at the shoulder periphery. For the simulated welding condition, the heat generation due to friction and plastic deformation makes up 54.4 and 45.6% of the total heat generation rate, respectively. In conclusion, the simulated temperature field is validated by the good agreement to the experimental measurements.

36 MATERIALS SCIENCE↗

Molecular Dynamics Simulation of Complex Reactivity with the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) Software Package

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. Ab initio methods are unable to currently access these time scales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system’s bonding topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer time scale reactive simulation data with statistical precision. RAPTOR may also be interfaced with enhanced sampling methods to drive simulations toward the analysis of reactive rare events, and a number of collective variables (CVs) have been developed to facilitate this. Key advances to this methodology, including GPU acceleration efforts and novel CVs to model water wire formation are reviewed, along with recent applications of the method which demonstrate its versatility and robustness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Examining the Effect of Exchange-Correlation Approximations in First-Principles Dynamics Simulation of Interfacial Charge Transfer

We examine the extent to which the exchange-correlation (XC) approximation influences modeling interfacial charge transfer using fewest-switches surface hopping (FSSH) simulations within the single-particle description. A heterogeneous interface between a lithium ion and an extended boron-nitride sheet was considered here, being an extreme case in which wave function localization and energy level alignments are highly sensitive to the XC approximation. The PBE0 hybrid XC approximation yields nonadiabatic couplings (NACs) that are significantly smaller than the values obtained from the PBE-GGA approximation by an order of magnitude for localized electronic states. This difference between the two XC functionals for the calculated NACs was found to derive mainly from the wave function characteristics rather than from the lattice movement although first-principles molecular dynamics trajectories, along which NACs are obtained, differ noticeably between the two XC functionals. Using the NACs and single-particle energy level alignments at different levels of theory, FSSH simulations were performed to model the electron transfer dynamics at the interface. Here, the electron transfer time scale was found to vary as much as, but not more than, 1 order of magnitude. The time scale was found to be quite sensitive to both NACs and energy level alignments. While the order of magnitude consistency for the charge transfer rate is encouraging even for this rather extreme model of heterojunction interface, continued advancement in electronic structure methods is required for quantitatively accurate determination of the transfer rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular dynamics simulation of water in and around carbon nanotubes: A coarse-grained description

In the present study, we intend to investigate behaviour of water in and around hydrophobic open ended carbon nanotubes (CNTs) using a coarse-grained, core-softened model potential for water. The model potential considered here for water has recently been shown to successfully reproduce dynamic, thermodynamic and structural anomalies of water. The epitome of the study is to understand the incarceration of this coarse-grained water in a single-file carbon nanotube. In order to examine the effect of fluid-water van der Waals interaction on the structure of fluid in and around the nanotube, we have simulated three different CNT-water systems with varying degree of solute-water dispersion interaction. The analyses of the radial one-particle density profiles reveal varying degree of permeation and wetting of the CNT interior depending on the degree of fluid-solute attractive van der Waals interaction. A peak in the radial density profile slightly off the nanotube axis signifies a zigzag chain of water molecule around the CNT axis. The average numbers of water molecules inside the CNT have been shown to increase with the increase in fluid-water attractive dispersion interaction.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Molecular Dynamics Simulations of Helium Bubble Formation in Palladium Tritides [Slides]

Pd readily absorbs hydrogen and its isotopes, and can be used to purify gas mixtures involving tritium. Tritium decays to He, forming He bubbles. Bubbles causes possible PCT effects swelling, He release, all leading to failures. Radioactive decay experiments take many years. Molecular dynamics (MD) studies can be quickly done. No previous MD methods can simulate He bubble nucleation and growth.

74 ATOMIC AND MOLECULAR PHYSICS↗

Molecular Dynamics Simulations of Helium Bubble Formation in Palladium Tritides [Slides]

Pd readily absorbs hydrogen and its isotopes, and can be used to purify gas mixtures involving tritium. Tritium decays to He, forming He bubbles. Bubbles causes possible PCT effects swelling, He release, all leading to failures. Radioactive decay experiments take many years. Molecular dynamics (MD) studies can be quickly done. No previous MD methods can simulate He bubble nucleation and growth.

74 ATOMIC AND MOLECULAR PHYSICS↗

Computational Fluid Dynamics Simulations to Assess Spatial Variability and Optimal Ventilation Scenarios for Biological Laboratory Exposures

A significant amount of uncertainty exists regarding potential human exposure to laboratory biomaterials and organisms in Biosafety Level 2 (BSL-2) research laboratories. Computational fluid dynamics (CFD) modeling is proposed as a way to better understand potential impacts of different combinations of biomaterials, laboratory manipulations, and exposure routes on risks to laboratory workers. Here, in this study, we use CFD models to simulate airborne concentrations of contaminants in an actual BSL-2 laboratory under different configurations. Results show that ventilation configuration, sampling location, and contaminant source location can significantly impact airborne concentrations and exposures. Depending on the source location and airflow patterns, the transient and time-integrated concentrations varied by several orders of magnitude. Contaminant plumes from sources located near a return vent (or exhaust like a fume hood or ventilated biosafety cabinet) are likely to be more contained than sources that are further from the exhaust. Having a direct flow between the source and the exhaust (through-flow condition) may reduce potential exposures to individuals outside the air flow path. Designing a BSL-2 room with ventilation and airflow patterns that maximize through-flow conditions to the return/exhaust vents and minimize dispersion and mixing throughout the room is, therefore, recommended. CFD simulations can also be used to assist in characterizing the impacts of supply and return vent locations, room layout, and source locations on spatial and temporal contaminant concentrations. In addition, proper placement of particle sensors can also be informed by CFD simulations to provide additional characterization and monitoring of potential exposures in BSL-2 facilities.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Striped gold nanoparticles: New insights from molecular dynamics simulations

Recent simulations have improved our knowledge of the molecular-level structure and hydration properties of mixed self-assembled monolayers (SAMs) with equal and unequal alkyl thiols at three different arrangements, namely, random, patchy, and Janus. In our previous work [V. Vasumathi et al., J. Phys. Chem. C 119, 3199–3209 (2015)], we showed that the bending of longer thiols over shorter ones clearly depends on the thiols’ arrangements and chemical nature of their terminal groups. In addition, such a thiol bending revealed to have a strong impact on the structural and hydration properties of SAMs coated on gold nanoparticles (AuNPs). In this paper, we extend our previous atomistic simulation study to investigate the bending of longer thiols by increasing the stripe thickness of mixed SAMs of equal and unequal lengths coated on AuNPs. We study also the effect of stripe thickness on the structural morphology and hydration of the coated SAMs. Our results show that the structural and hydration properties of SAMs are affected by the stripe thickness for mixtures of alkyl thiols with unequal chain length but not for equal length. Hence, the stability of the stripe configuration depends on the alkyl’s chain length, the length difference between the thiol mixtures, and solvent properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Partial molar enthalpies and reaction enthalpies from equilibrium molecular dynamics simulation

We present a new molecular simulation technique for determining partial molar enthalpies in mixtures of gases and liquids from single simulations, without relying on particle insertions, deletions, or identity changes. The method can also be applied to systems with chemical reactions. We demonstrate our method for binary mixtures of Weeks-Chandler-Anderson particles by comparing with conventional simulation techniques, as well as for a simple model that mimics a chemical reaction. The method considers small subsystems inside a large reservoir (i.e., the simulation box), and uses the construction of Hill to compute properties in the thermodynamic limit from small-scale fluctuations. Results obtained with the new method are in excellent agreement with those from previous methods. Especially for modeling chemical reactions, our method can be a valuable tool for determining reaction enthalpies directly from a single MD simulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine-learning force-field models for dynamical simulations of metallic magnets

We review recent advances in machine-learning (ML) force-field methods for Landau–Lifshitz–Gilbert simulations of itinerant electron magnets, focusing on their scalability and transferability. Built on the principle of locality, a deep neural-network model is developed to efficiently and accurately predict electron-mediated forces governing spin dynamics. Symmetry-aware descriptors constructed through a group-theoretical approach ensure rigorous incorporation of both lattice and spin-rotation symmetries. The framework is demonstrated using the prototypical s-d exchange model widely employed in spintronics. ML-enabled large-scale simulations reveal novel nonequilibrium phenomena, including anomalous coarsening of tetrahedral spin order on the triangular lattice and the freezing of phase-separation dynamics in lightly hole-doped, strong-coupling square-lattice systems. These results establish ML force-field frameworks as scalable, accurate, and versatile tools for modeling nonequilibrium spin dynamics in itinerant magnets.

Artificial neural networks↗

Molecular-Dynamics Simulation of the Influence of Silicon on the Ordering of Carbon in the Martensite Lattice

The results of computer simulation of the influence of silicon impurities on the degree of tetragonality and on the interaction of carbon atoms in the body-centered cubic (BCC) lattice of iron by the molecular-dynamics method are reported. The influence of silicon on the martensite-lattice parameters has been established, as well as the dependence of the deformation interaction parameter λ{sub 0} determining the critical temperature of the BCC–BCT (body-centered tetragonal) transition on the silicon concentration, is calculated on the basis of the Zener–Khachaturyan theory of ordering. It is found that the λ{sub 0} parameter decreases by 18% from 5.2 to 4.2 eV/atom upon an increase in the silicon content up to 10 at %.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Dissipative particle dynamics simulations of deformation and aggregation of healthy and diseased red blood cells in a tube flow

In this paper, we report simulation results assessing the deformation and aggregation of mixed healthy and malaria-infected red blood cells (RBCs) in a tube flow. A three dimensional particle model based on Dissipative Particle Dynamics (DPD) is developed to predict the tube flow containing interacting cells. The cells are also modelled by DPD, with a Morse potential to characterize the cell-cell interaction. As validation tests, a single RBC in a tube flow and two RBCs in a static flow are simulated to examine the cell deformation and intercellular interaction, respectively. The study of two cells, one healthy and the other malaria-infected RBCs in a tube flow demonstrates that the malaria-infected RBC (in the leading position along flow direction) has different effects on the healthy RBC (in the trailing position) at the different stage of parasite development or at the different capillary number. With parasitic development, the malaria-infected RBC gradually loses its deformability, and in turn the corresponding trailing healthy RBC also deforms less due to the intercellular interaction. With increasing capillary number, both the healthy and malaria-infected RBCs are likely to undergo an axisymmetric motion. The minimum intercellular distance becomes small enough so that rouleaux is easily formed, i.e., the healthy and malaria-infected RBCs are difficultly disaggregated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Atomic-scale mechanism of carbon nucleation from a deep crustal fluid by replica exchange reactive molecular dynamics simulation

Here we present a mechanistic model of carbon nucleation and growth from a fluid at elevated temperature (T) and pressure conditions, typical of those found in the shallow Earth’s lithosphere. Our model uses a replica exchange reactive molecular dynamics framework in which molecular configurations are swapped between adjacent T replica at regular intervals according to underlying statistical mechanics. This framework allows predicting complex molecular structures and thermodynamics while remaining computationally efficient. Here we simulate the reactivity of an unstable mixture of CO 2 and CH 4 at 1000 K and 1 GPa. We find that the path to thermodynamic equilibrium is initially entropy-driven, producing a diversity of short-lived species, including various alcohols with intermediate carbon oxidation states. Cyclic and polycyclic radicals that are sometimes resonance-stabilized form next and set the stage for carbon nucleation. The carbon exsolution process releases abundant water, is exothermic and starts with the nucleation of a large aggregate of hydrogenated graphene flakes from covalently bonded polycyclic units. The carbon backbone of this nucleus subsequently grows into a hydrogen-depleted fullerene-like structure, before evolving toward a partially bilayered graphene layer. Overall, our results show that the mechanism of graphitic C formation is certainly not bimolecular, and that it may involve a combination of key condensation and radical chain reactions. This will help understand the isotopic, and reactive characteristics of carbon-bearing fluids during their upward transit through the Earth’s mantle and crust. Moreover, the mechanistic insights outlined here present intriguing similarities with the process of soot and interstellar dust formation, which suggests that the widespread distribution of abiotic polyaromatic and graphitic material on Earth and beyond may reflect the prevalence of a fundamental chemical pathway.

58 GEOSCIENCES↗

Constructing Neural Network Based Models for Simulating Dynamical Systems

Dynamical systems see widespread use in natural sciences like physics, biology, and chemistry, as well as engineering disciplines such as circuit analysis, computational fluid dynamics, and control. For simple systems, the differential equations governing the dynamics can be derived by applying fundamental physical laws. However, for more complex systems, this approach becomes exceedingly difficult. Data-driven modeling is an alternative paradigm that seeks to learn an approximation of the dynamics of a system using observations of the true system. In recent years, there has been an increased interest in applying data-driven modeling techniques to solve a wide range of problems in physics and engineering. Here this article provides a survey of the different ways to construct models of dynamical systems using neural networks. In addition to the basic overview, we review the related literature and outline the most significant challenges from numerical simulations that this modeling paradigm must overcome. Based on the reviewed literature and identified challenges, we provide a discussion on promising research areas.

97 MATHEMATICS AND COMPUTING↗