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Results for “Dynamical Simulations”

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.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Advanced time integration algorithms for dislocation dynamics simulations of work hardening

Efficient time integration is a necessity for dislocation dynamics simulations of work hardening to achieve experimentally relevant strains. In this work, an efficient time integration scheme using a high order explicit method with time step subcycling and a newly-developed collision detection algorithm are evaluated. First, time integrator performance is examined for an annihilating Frank–Read source, showing the effects of dislocation line collision. The integrator with subcycling is found to significantly out-perform other integration schemes. The performance of the time integration and collision detection algorithms is then tested in a work hardening simulation. The new algorithms show a 100-fold speed-up relative to traditional schemes. As a result, subcycling is shown to improve efficiency significantly while maintaining an accurate solution, and the new collision algorithm allows an arbitrarily large time step size without missing collisions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Effects of Surface Orientation and Termination Plane on Glass‐to‐Crystal Transformation of Lithium Disilicate by Molecular Dynamics Simulations

Glass‐to‐crystal transformation of lithium disilicate is studied using molecular dynamics simulations using an effective partial charge potential. The structural evolution of the interface between glassy and crystalline lithium disilicate is analyzed to simulate crystallization of glass on pre‐existing crystal seeds. Besides previously used atomic number density, the distribution of Q n species (Si tetrahedra with n bridging oxygen) is shown to be an effective parameter for following this transformation quantitatively. The early stages of crystal growth are significantly affected by the orientation and termination of the surface of adjacent crystal, as indicated by calculated atomic density, partial ordering, atomic segregation, and an increase in Q 3 concentration. In particular, under‐coordinated Si within the outer crystal layer is found to be most effective in transforming the amorphous structure toward crystallinity. The increase in Q 3 in the glass close to interface region most clearly shows the initial stage of lithium disilicate crystal growth.

Sun, Wei↗
DOE OSTI2018

Model Evaluation Report for LNG Dispersion on Fire Dynamics Simulator Version 6.5.3

This report is an assessment of the computational fluid dynamics (CFD) code Fire Dynamics Simulator (FDS), version 6.5.3, using the Model Evaluation Protocol (MEP) for Liquefied Natural Gas (LNG). The MEP consists of model validation and a scientific assessment that encompasses model information and model verification activities. Model validation entails comparison against various field and wind-tunnel trials for LNG and other dense gases with and without obstructions. The results indicate that FDS is generally over-predictive for most of the field scale dense gas releases and cases involving obstructions without requiring a safety factor of 2, however, since there are uncertainties in extrapolating to accident scales a safety factor of 2 (1/2 LFL criteria) may be appropriate. The results of this scientific assessment and prior verification efforts demonstrate the soundness of the numerical techniques and robustness of FDS. The validation results indicate that FDS is suitable for modeling dense gas dispersion with and without obstructions.

03 NATURAL GAS↗
NASA NTRS1983

A large-signal dynamic simulation for the series resonant converter

A simple nonlinear discrete-time dynamic model for the series resonant dc-dc converter is derived using approximations appropriate to most power converters. This model is useful for the dynamic simulation of a series resonant converter using only a desktop calculator. The model is compared with a laboratory converter for a large transient event.

King, R. J.↗
NASA NTRS1995

Program For Simulating Dynamics Of Aerospace Vehicles

SORT (Simulation and Optimization of Rocket Trajectories) is general-purpose three-degree-of-freedom with three axis static moment balance simulation of flight dynamics of arbitrary aerospace vehicle. Modular structure facilitates application to variety of trajectory-analysis problems. Contains math model of aerodynamics completely generalized. Computes both longitudinal and lateral forces and moments. In addition to fore-body coefficients, computes longitudinal base effect aerodynamic forces and moments. Simplified ballistic-coefficient model also available for analysis of ballistic entry. Written using ANSI FORTRAN 77.

Berning, M. J.↗
DOE OSTI2015

Direct molecular dynamics simulation of Ge deposition on amorphous SiO 2 at experimentally relevant conditions

Molecular dynamics simulations were used to study Ge island nucleation and growth on amorphous SiO 2 substrates. This process is relevant in selective epitaxial growth of Ge on Si, for which SiO 2 is often used as a template mask. The islanding process was studied over a wide range of temperatures and fluxes, using a recently proposed empirical potential model for the Si–SiO 2 –Ge system. The simulations provide an excellent quantitative picture of the Ge islanding and compare well with detailed experimental measurements. These quantitative comparisons were enabled by an analytical rate model as a bridge between simulations and experiments despite the fact that deposition fluxes accessible in simulations and experiments are necessarily different by many orders of magnitude. In particular, the simulations led to accurate predictions of the critical island size and the scaling of island density as a function of temperature. Lastly, the overall approach used here should be useful not just for future studies in this particular system, but also for molecular simulations of deposition in other materials.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Diffusion of Selective Penetrants in Interfacially Modified Block Copolymers from Molecular Dynamics Simulations

In order to show the influence of the interface on structure and dynamics of microphase separated polymer systems, we study interfacially modified AB block copolymers with small molecule penetrants. The polymers have a random midblock or tapered midblock whose composition varies from pure A to pure B (or from pure B to pure A for an inverse taper) between two pure blocks of A and B. We perform simple coarse-grained molecular dynamics simulations of symmetric polymers that form lamellae. With normal tapering, both polymer and penetrant diffusion parallel to the lamellae increases as taper length increases. Inverse tapered polymers exist in different conformational states (e.g. stretched versus folded back and forth across the interface) with different dynamic behavior, leading to non-monotonic trends in their diffusion. However, the local mixing of monomers (rather than polymer conformation) appears to be the most important factor in determining penetrant diffusion.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Semi-Empirical Interatomic Potential for Large-Scale Molecular Dynamics Simulation of Metal-Oxide Systems

Classical molecular dynamics (MD) simulation can be applied to systems containing billions of atoms during times up to microseconds. However, utilization of a large-scale MD simulation requires reliable but computationally cheap interatomic potentials. In the case of metallic systems, embedded atom method (EAM) and Finnis-Sinclair (FS) potentials are the reasonable choices, but their development for multicomponent alloys is a challenge. Addition of oxygen atoms makes the problem of developing semi-empirical potentials even more difficult because the long-range Coulomb interaction cannot be neglected, and different atoms have different charges which vary during MD relaxation such that a charge equilibration procedure should be applied every MD step. As results researchers tend to avoid simulating metal-oxide systems. In this talk, a new Finnis-Sinclair (FS) Ni-Co-Cr potential will be presented. Special attention will be paid to reproducing of the element melting temperatures and clustering. Next, a charge transfer ionic potential (CTIP) developed to simulate the NiO properties will be presented. This potential utilizes the Ni FS potential and accounts for the Coulomb interaction in the vicinity of oxygen atoms. Fitting of the CTIP parameters and FS potential functions describing the interaction with oxygen atoms to the available experimental and ab initio data will be discussed. Results of MD simulation of interaction of NiO particles with dislocations in Ni will be shown.

molecular dynamics simulation↗
NASA NTRS1985

Software life cycle dynamic simulation model: The organizational performance submodel

The submodel structure of a software life cycle dynamic simulation model is described. The software process is divided into seven phases, each with product, staff, and funding flows. The model is subdivided into an organizational response submodel, a management submodel, a management influence interface, and a model analyst interface. The concentration here is on the organizational response model, which simulates the performance characteristics of a software development subject to external and internal influences. These influences emanate from two sources: the model analyst interface, which configures the model to simulate the response of an implementing organization subject to its own internal influences, and the management submodel that exerts external dynamic control over the production process. A complete characterization is given of the organizational response submodel in the form of parameterized differential equations governing product, staffing, and funding levels. The parameter values and functions are allocated to the two interfaces.

Tausworthe, Robert C.↗
DOE OSTI2015

Extracting the diffusion tensor from molecular dynamics simulation with Milestoning

We propose an algorithm to extract the diffusion tensor from Molecular Dynamics simulations with Milestoning. A Kramers-Moyal expansion of a discrete master equation, which is the Markovian limit of the Milestoning theory, determines the diffusion tensor. To test the algorithm, we analyze overdamped Langevin trajectories and recover a multidimensional Fokker-Planck equation. The recovery process determines the flux through a mesh and estimates local kinetic parameters. Rate coefficients are converted to the derivatives of the potential of mean force and to coordinate dependent diffusion tensor. We illustrate the computation on simple models and on an atomically detailed system—the diffusion along the backbone torsions of a solvated alanine dipeptide.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Scalable Reactive Molecular Dynamics Simulations for Computational Synthesis

Reactive molecular dynamics (MD) simulation is a powerful research tool for describing chemical reactions. We eliminate the speed-limiting charge iteration in MD with a novel extended-Lagrangian scheme. The extended-Lagrangian reactive MD (XRMD) code drastically improves energy conservation while substantially reducing time-to-solution. Furthermore, we introduce a new polarizable charge equilibration (PQEq) model to accurately predict atomic charges and polarization. The XRMD code based on hybrid message passing+multithreading achieves a weak-scaling parallel efficiency of 0.977 on 786 432 IBM Blue Gene/Q cores for a 67.6 billion-atom system. The performance is portable to the second-generation Intel Xeon Phi, Knights Landing. Blue Gene/Q simulations for the computational synthesis of materials via novel exfoliation mechanisms for synthesizing atomically thin transition metal dichalcogenide layers will dominate nanomaterials science in this century.

Simulation, Modeling, Performance, and Visualizati↗
DOE OSTI2025

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗
DOE OSTI2025

Acceleration of Power System Dynamic Simulations Using a Deep Equilibrium Layer and Neural ODE Surrogate

The dominant paradigm for power system dynamic simulation is to build system-level simulations by combining physics-based models of individual components. The sheer size of the system along with the rapid integration of inverter-based resources exacerbates the computational burden of running time domain simulations. Here, in this paper, we propose a data-driven surrogate model based on implicit machine learningspecifically deep equilibrium layers and neural ordinary differential equationsto learn a reduced order model of a portion of the full underlying system. The data-driven surrogate achieves similar accuracy and reduction in simulation time compared to a physics-based surrogate, without the constraint of requiring detailed knowledge of the underlying dynamic models. This work also establishes key requirements needed to integrate the surrogate into existing simulation workflows; the proposed surrogate is initialized to a steady state operating point that matches the power flow solution by design.

Neural ordinary differential equations↗
DOE OSTI2015

Molecular dynamics simulation of radiation damage cascades in diamond

Radiation damage cascades in diamond are studied by molecular dynamics simulations employing the Environment Dependent Interaction Potential for carbon. Primary knock-on atom (PKA) energies up to 2.5 keV are considered and a uniformly distributed set of 25 initial PKA directions provide robust statistics. The simulations reveal the atomistic origins of radiation-resistance in diamond and provide a comprehensive computational analysis of cascade evolution and dynamics. As for the case of graphite, the atomic trajectories are found to have a fractal-like character, thermal spikes are absent and only isolated point defects are generated. Quantitative analysis shows that the instantaneous maximum kinetic energy decays exponentially with time, and that the timescale of the ballistic phase has a power-law dependence on PKA energy. Defect recombination is efficient and independent of PKA energy, with only 50% of displacements resulting in defects, superior to graphite where the same quantity is nearly 75%.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Accelerating dissipative particle dynamics simulations on GPUs: Algorithms, numerics and applications

We present a scalable dissipative particle dynamics simulation code, fully implemented on the Graphics Processing Units (GPUs) using a hybrid CUDA/MPI programming model, which achieves 10-30 times speedup on a single GPU over 16 CPU cores and almost linear weak scaling across a thousand nodes. A unified framework is developed within which the efficient generation of the neighbor list and maintaining particle data locality are addressed. Our algorithm generates strictly ordered neighbor lists in parallel, while the construction is deterministic and makes no use of atomic operations or sorting. Such neighbor list leads to optimal data loading efficiency when combined with a two-level particle reordering scheme. A faster in situ generation scheme for Gaussian random numbers is proposed using precomputed binary signatures. We designed custom transcendental functions that are fast and accurate for evaluating the pairwise interaction. The correctness and accuracy of the code is verified through a set of test cases simulating Poiseuille flow and spontaneous vesicle formation. Computer benchmarks demonstrate the speedup of our implementation over the CPU implementation as well as strong and weak scalability. A large-scale simulation of spontaneous vesicle formation consisting of 128 million particles was conducted to further illustrate the practicality of our code in real-world applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Thermodynamic analysis of the Livermore molecular-dynamics simulations of dislocation-mediated plasticity

Results of recent large-scale molecular dynamics simulations of dislocation-mediated solid plasticity are compared with predictions of the statistical thermodynamic theory of these phenomena. These computational and theoretical analyses are in substantial agreement with each other in both their descriptions of strain-rate-dependent steady plastic flows and of transient stress peaks associated with initially small densities of dislocations. Lastly, the comparisons between the numerical simulations and basic theory reveal inconsistencies in some conventional phenomenological descriptions of solid plasticity.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

The data system dynamic simulation /DSDS/

The paper describes the development by NASA of the data system dynamic simulation (DSDS) which provides a data system simulation capability for a broad range of programs, with the capability to model and simulate all or any portion of an end-to-end data system to multiple levels of fidelity. Versatility is achieved by specifying parameters which define the performance characteristics of data system components, and by specifying control and data paths in a data system. DSDS helps reduce overall simulation cost and the time required for obtaining a data systems analysis, and helps provide both early realistic representations of data systems and the flexibility to study design changes and operating strategies.

Hooper, J. W.↗
DOE OSTI2023

Large-scale molecular dynamics simulations of bubble collapse in water: Effects of system size, water model, and nitrogen

Molecular dynamics simulations in the microcanonical ensemble are performed to study the collapse of a bubble in liquid water using the single-site mW and the four-site TIP4P/2005 water models. To study system size effects, simulations for pure water systems are performed using periodically replicated simulation boxes with linear dimensions, L, ranging from 32 to 512 nm with the largest systems containing 8.7 × 10 6 and 4.5 × 10 9 molecules for the TIP4P/2005 and mW water models, respectively. The computationally more efficient mW water model allows us to reach converging behavior when the bubble dynamics results are plotted in reduced units, and the limiting behavior can be obtained through linear extrapolation in L –1 . Qualitative differences are observed between simulations with the mW and TIP4P/2005 water models, but they can be explained by the models’ differences in predicted viscosity and surface tension. Although bubble collapse occurs on time scales of only hundreds of picoseconds, the system sizes used here are sufficiently large to obtain bubble dynamics consistent with the Rayleigh–Plesset equation when using the models’ thermophysical properties as input. For the conditions explored here, extreme heating of the interfacial water molecules near the time of collapse is observed for the larger mW water systems (but the model underpredicts the viscosity), whereas heating is less pronounced for the TIP4P/2005 water systems because its larger viscosity contribution slows the collapse dynamics. The presence of nitrogen within the bubble only starts to affect bubble dynamics near the very end of the initial collapse, leading to an incomplete collapse and strong rebound for the mW water model. Although nitrogen is non-condensable at 300 K, it becomes highly compressed and reaches a liquid-like density near the collapse point. We find that the dissolution of nitrogen is much slower than the movement of the collapsing water front, and the re-expansion of the dense nitrogen droplet gives rise to bubble rebound. The incompatibility of the collapse and dissolution time scales should be considered for continuum-scale modeling of bubble dynamics. Finally, we also confirm that the diffusion coefficient for dissolved nitrogen is insensitive to pressure as the liquid transitions from a compressed to a stretched state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗