Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “dynamics simulation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

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↗
DOE OSTI2014

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↗
DOE OSTI2026

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↗
DOE OSTI2018

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↗
DOE OSTI2014

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↗
NASA NTRS1995

Simulated dynamic response of a multi-stage compressor with variable molecular weight flow medium

A mathematical model of a multi-stage compressor with variable molecular weight flow medium is derived. The modeled system consists of a five stage, six cylinder, double acting, piston type compressor. Each stage is followed by a water cooled heat exchanger which serves to transfer the heat of compression from the gas. A high molecular weight gas (CFC-12) mixed with air in varying proportions is introduced to the suction of the compressor. Condensation of the heavy gas may occur in the upper stage heat exchangers. The state equations for the system are integrated using the Advanced Continuous Simulation Language (ACSL) for determining the system's dynamic and steady state characteristics under varying operating conditions.

Babcock, Dale A.↗
DOE OSTI2022

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↗
DOE OSTI2023

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↗
DOE OSTI2018

Density of States Broadening in CH 3 NH 3 PbI 3 Hybrid Perovskites Understood from ab Initio Molecular Dynamics Simulations

Lead-halide perovskites are promising materials in optoelectronic devices for their unique properties including direct band gap, strong light absorption, high carrier mobility, and low fabrication cost. Here, by using ab inito molecular dynamics and electronic structure calculations, we report a systematic study on the broadening density of states (DOS) deep in the valence bands that has been experimentally observed but absent in static calculations. We quantify the broadening DOS reduction from the cubic phase to lower-temperature tetragonal and orthorhombic phases and attribute observed effects to the molecular vibrations and the anharmonicity of iodine atoms motion. Specifically, the MA cations’ vibrations are strongly linked to the moderate C–N stretch and CH 3 bend, as well as the strong CH 3 and NH 3 + stretches. Furthermore, these results present a theoretical perspective on the structural dynamics in lead-halide perovskites which may be valuable for future studies toward desired functionalities in perovskite-based optoelectronic devices.

36 MATERIALS SCIENCE↗
NASA NTRS2024

Experimental Validation of Charged Lunar Dust Dynamics Simulants

The goal of this work is to experimentally verify the electrostatic interaction physics that have been incorporated into the discrete element method (DEM) modeling software package during the FY20 CIF project titled “Charged Particle Dynamics in the Lunar Environment.” Current state-of-the-art (SOA) granular gas dynamics models used to explain rocket plume impingement physics have not taken into account the natural or induced electrostatic environment of the lunar surface, nor the effect of charged regolith grains being present in the plume plasma. This work improved upon the SOA by adding long-range and contact inter-particle electrostatic interactions to a granular mechanics DEM modeling software package. Tribocharging mechanics between spherical particles has been experimentally examined along with the natural electrostatic plasma environments produced via emission from an electron gun and ultraviolet lamp.

Jay Phillips↗
DOE OSTI2021

Validation of Computational Fluid Dynamics Simulations for Biological Performance Assessment in Hydropower units (Final Report)

The biological performance assessment (BioPA) toolset developed by Pacific Northwest National Laboratory (PNNL) estimates the relative biological performance of fish passage at a hydroelectric power turbine unit. The tool is based on the use of computational fluid dynamics (CFD) and fish biological response relationships. The recent release, BioPA-v3, is based on directly computed trajectory and collision of material Lagrangian particles using CFD simulation codes rather than the prior version that relies on Tecplot to compute streamtrace trajectories. Before modifying the toolset, a series of validation tests were performed at the various steps of modification in the toolset. Validation is a critical step of any numerical investigation that reflects the accuracy and reliability of the predicted results. It raises the confidence level of the user to use the modified version of the BioPA toolset. Several test cases were simulated and compared, where available, to observed data. The trajectory and collision of the small spherical and cylindrical particles in a water flume were compared to in-house experiments. The CFD predicted collision rate and flow field compared well with experimental observation for vane array and large cylinder as target bodies. Next, the CFD-predicted flow field and hydraulic performance of a laboratory-scale model of a Francis turbine was also successfully validated. Note that the trajectory of the particles is significantly affected by the flow field in such extreme conditions. In addition to the particle trajectories and flow field, the collision detection method employed in the CFD simulations was also successfully validated. The CFD predicted impact velocity, collision time, velocity, and trajectory of a sphere excellently matched with analytical value for a bouncing ball in the elastic collision. A similar approach was also tested and successfully validated for a collision of sphere with a 45° inclined plane. After successfully validating different cases, the BioPA toolset was modified to use direct output of the CFD prediction and the new version can be used in evaluating biological performance at hydroelectric turbines.

13 HYDRO ENERGY↗
DOE OSTI2013

Molecular dynamics simulation of self-rotation effects on ultra-precision polishing of single-crystal copper

Understanding the behaviors of the material removal mechanism of ultra-precision polishing process has been a critical issue of generating well-formed surface. In order to make clear the abrasive self-rotation effects on material removal at the atomic level, a three-dimensional molecular dynamics (MD) model is conducted to study the mechanics of ultra-precision polishing on single-crystal copper with a diamond abrasive and the effects of abrasive self-rotation velocity and direction. Morse potential energy function and EAM potential energy function are applied to model the copper/diamond and copper/copper interactions, respectively. The simulation results show that the deformation mechanism of single-crystal copper is due to the formation and movement of dislocations in the specimen. In addition, with the increasing of abrasive self-rotation velocity, the deformation mechanism falls from cutting to plowing regimes. The abrasive self-rotation velocity and direction have effects on the morphology and quality of the specimen surface, distribution and evolution of defects under the surface of the specimen. Also, the interatomic force between abrasive and specimen is studied to account for the effects of different polishing conditions.

36 MATERIALS SCIENCE↗
NASA NTRS2019

AladynPi – Adaptive Neural Network Molecular Dynamics Simulation Code with Physically Informed Potential: Computational Materials Mini-Application

This report provides an overview and description of commands used in the Computational Materials mini-application, AladynPi. AladynPi is an extension of a previously released mini-application, Aladyn (https://github.com/nasa/aladyn; Yamakov, V.I., and Glaessgen, E.H., NASA/TM-2018-220104). Aladyn and AladynPi are basic molecular dynamics codes written in FORTRAN 2003, which are designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory method. An input for the ANN is a set of structure coefficients, characterizing the local atomic environment of each atom, for which the atomic energy is obtained in the ANN inference process. In Aladyn, the ANN gives directly the energy of interatomic interactions. In AladynPi, the ANN gives optimized parameters for a predefined empirical function, known as bond-order-potential (BOP). The parameterized BOP function is then used to calculate the energy. AladynPi code is being released to serve as a training testbed for students and professors in academia to explore possible optimization algorithms for parallel computing on multicore central processing unit (CPU) computers or computers utilizing manycore architectures based on graphic processing units (GPUs). The effort is supported by the High Performance Computing incubator (HPCi) project at NASA Langley Research Center.

Yamakov, Vesselin I.↗
DOE OSTI2019

Modeling Electron Injection at Semiconductor–Molecule Interfaces using First-Principles Dynamics Simulation: Effects of Nonadiabatic Coupling, Self-energy, and Surface Models

Excited electron transfer across semiconductor–molecule heterogeneous interfaces is central to various future electronic and optoelectronic devices. At the same time, first-principles modeling of such dynamical processes remains as a great challenge in theoretical chemistry and condensed matter physics for developing better understanding at the molecular scale. Excited electron transfer from a molecule to semiconductor surface is a particularly difficult case to model accurately, because the initial state of such an electron injection process often lies deep within the dense manifold of the conduction band states in the semiconductor. Nonadiabatic couplings and energy level alignments at such interfaces as well as the finite size error of the surface model all play important roles in numerical modeling of electron injection via first-principles theory. Here, using representative interfaces between a well-defined hydrogen-terminated Si(111) surface and series of covalently adsorbed conjugated molecules, we investigate the extent to which these theoretical and numerical considerations influence the description of electron injection at the semiconductor–molecule interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

MRI Measurements and Granular Dynamics Simulation of Segregation of Granular Mixture

A counter intuitive axial segregation phenomenon in a rotating horizontal cylinder has recently captured attention of many researchers in different disciplines. There is a growing consensus that the interplay between the particle dynamics and the evolution of the internal structure during the segregation process must be carefully investigated. Magnetic resonance imaging (MRI) has been used to non-invasively obtain much needed dynamic/static information such as velocity and concentration profiles, and it has proven to be capable of depicting the evolution of segregation processes. Segregation in a rotating cylinder involves two processes: the first is to transport small particles in the radial direction to form a radial core, and the second is to transform the radial core into axially segregated bands. Percolation and/or "stopping" have been proposed as mechanisms for the radial segregation. As to mechanisms for axial band formation, much less is known. The difference in the dynamic angle of repose has been proposed to segregate different components in the axial direction. Recently, Hill and Kakalios have reported that particles mix or demix depending upon the competition between diffusion and preferential drift whose order can be determined by the dynamic angle of repose through the adjustment of the rotation rate. We claim that the dynamic angle of repose could be one of the causes, however, it fails to offer reasonable explanations for certain aspects of the axial migration. For example, we always observe that the radial segregation precedes the axial segregation and small particles migrate in the radial direction to form an axially extended radial core. It then transforms into axially segregated bands. By definition, the effects of the dynamic angle of repose are restricted near the free surface where the flowing layer is present. However, during the process of transforming from the radially segregated core to axially segregated bands, small particles located in the deep core region, which is untouched by the flowing layer, also completely disappear. Usually, the dynamics angle of repose are uniquely defined for individual species to characterize particle properties, and the dynamic angle of repose thus defined provides little information for the dynamic angle of repose of the mixture since the concentration ratio and the internal packing structure do not remain the same during the segregation processes. Under microgravity environment, the dynamics angle of repose argument does not hold since there is simply no flowing layer to influence/determine the preferred directions of segregation. We have thus designed an experiment so that the effects of the dynamic angle of repose can be minimized by filling the cylinder almost completely full. Small particles still formed a radial core and also migrated to form axial bands. As ground based experiments we have designed and conducted both 2D and 3D segregation experiments. The 2D experiments are performed using a thin cylinder (the gap between two end caps is about 5 mm) filled with different combinations of particles. The 3D experiments are conducted with a long cylinder of its length and diameter of 27cm and 7cm, respectively. Results of 2D experiments indicate that different mechanisms govern particle motion in regions near and far from the axis of rotation. Results of 3D experiments indicate that a series of collapses of microstructures of particle packing (micro-collapses) may be responsible for the creation of voids for small particles to migrate through in the axial direction. We have successfully eliminated the dynamic angle of repose as a cause for segregation, however, by almost completely filling the cylinder with the particles, we have lost an opportunity to investigate a possibility of particle "mobility" being a cause for segregation which requires a flowing surface but not the difference in the angle of repose. This is currently being investigated.

Nakagawa, M.↗
DOE OSTI2014

Molecular dynamics simulations of the amino acid-ZnO (10-10) interface: A comparison between density functional theory and density functional tight binding results

We investigate the adsorption behavior of four different amino acids (glutamine, glutamate, serine, cysteine) on the zinc oxide (101{sup ¯}0) surface, comparing the geometry and energy associated with a number of different adsorption configurations. In doing this, we highlight the benefits and limits of using density-functional tight-binding (DFTB) with respect to standard density functional theory (DFT). The DFTB method is found to reliably reproduce the DFT adsorption geometries. Analysis of the adsorption configurations emphasizes the fundamental role of the first hydration layer in mediating the interactions between the amino acids and the surface. Direct surface-molecule bonds are found to form predominantly via the carboxylate groups of the studied amino acids. No surface-mediated chemical reactions are observed, with the notable exception of a proton transfer from the thiol group of cysteine to a hydroxyl group of the surface hydration layer. The adsorption energies are found to be dominated both by the formation of direct or indirect surface-molecule hydrogen bonds, but also by the rearrangement of the hydrogen-bond network in surface proximity in a non-intuitive way. Energetic comparisons between DFTB and DFT are made difficult on one side by the long time necessary to achieve convergence of potential energy values in MD simulations and on the other side by the necessity of including higher-order corrections to DFTB to obtain a good description of the hydrogen bond energetics. Overall, our results suggest that DFTB is a good reference method to set the correct chemical states and the initial geometries of hybrid biomolecule/ZnO systems to be simulated with non-reactive force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗