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At least 235 records · Page 13

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DOE OSTI2013

Molecular dynamics simulations of swift heavy ion induced defect recovery in SiC

Swift heavy ions induce a high density of electronic excitations that can cause the formation of amorphous ion tracks in insulators. No ion tracks have been observed in the semiconductor SiC, but recent experimental work suggests that irradiation damaged SiC can undergo defect recovery under swift heavy ion irradiation. It is believed that local heating of the lattice due to the electronic energy deposition can anneal, and thereby recover, some of the disordered structure. We simulate the local heating due to the ions by the inelastic thermal spike model and perform molecular dynamics simulations of dierent model damage states to study the defect recovery on an atomistic level. We find significant recovery of point defects and a disordered layer, as well as recrystallization at the amorphous-to-crystalline interface of an amorphous layer. The simulation results support the swift heavy ion annealing hypothesis.Swift heavy ions induce a high density of electronic excitations that can cause the formation of amorphous ion tracks in insulators. No ion tracks have been observed in the semiconductor SiC, but recent experimental work suggests that irradiation damaged SiC can undergo defect recovery under swift heavy ion irradiation. It is believed that local heating of the lattice due to the electronic energy deposition can anneal, and thereby recover, some of the disordered structure. We simulate the local heating due to the ions by the inelastic thermal spike model and perform molecular dynamics simulations of dierent model damage states to study the defect recovery on an atomistic level. We find significant recovery of point defects and a disordered layer, as well as recrystallization at the amorphous-to-crystalline interface of an amorphous layer. The simulation results support the swift heavy ion annealing hypothesis.

Defect recovery↗

DOE OSTI2016

Molecular dynamics simulation of the structural, elastic, and thermal properties of pyrochlores

We present a comprehensive simulation study of the effect of composition on the structural, elastic and thermal properties of 25 different compounds from the pyrochlore family. We joined a repulsive potential to an existing interatomic potential to enable molecular dynamics simulations of conditions away from equilibrium. We systematically varied the chemistry of the pyrochlore by substituting different cations in the A and B sites of the A2B2O7 formula unit. The A cations varied from Lu3+ to La3+, and the B cations from Ti4+ to Ce4+. The lattice parameter increased steadily with increasing the radius of A or B cations, but the bulk modulus showed a decreasing trend with increasing cation radius. However, the specific heat capacity and thermal expansion coefficient remained almost unchanged with increasing the radii of A and B cations. It is of interest to note that Ce on the B site significantly reduces the specific heat capacity and thermal expansion coefficient, which could have implications for annealing of radiation damage in cerate pyrochlores. The present results are consistent with the experimental measurements, which validates these potentials for simulation of dynamical processes, such as radiation damage, in pyrochlores.

computer simulation↗

DOE OSTI2015

Molecular dynamic simulation of Ar-Kr mixture across a rough walled nanochannel: Velocity and temperature profiles

This paper presents the results from a molecular dynamics simulation of mixture of argon and krypton in the Poiseuille flow across a rough walled nanochannel. The roughness effect on liquid nanoflows has recently drawn attention The computational software used for carrying out the molecular dynamics simulations is LAMMPS. The fluid flow takes place between two parallel plates and is bounded by horizontal rough walls in one direction and periodic boundary conditions are imposed in the other two directions. Each fluid atom interacts with other fluid atoms and wall atoms through Leenard-Jones (LJ) potential with a cut off distance of 5.0. To derive the flow a constant force is applied whose value is varied from 0.1 to 0.3 and velocity profiles and temperature profiles are noted for these values of forces. The velocity profile and temperature profiles are also looked at different channel widths of nanochannel and at different densities of mixture. The velocity profile and temperature profile of rough walled nanochannel are compared with that of smooth walled nanochannel and it is concluded that mean velocity increases with increase in channel width, force applied and decrease in density also with introduction of roughness in the walls of nanochannel mean velocity again increases and results also agree with the analytical solution of a Poiseuille flow.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2011

Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I

Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G} for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the research team's expertise in algorithm-to-architecture mappings, the high-cost kernels were transformed, parallelized, and implemented on Nvidia Fermi GPUs. Measured speedups (GPU with respect to single-core CPU) were approximately 20-32X for realistic model parameters, without final optimization. Error analysis showed no loss of computational accuracy. Commercial Applications and Other Benefits - The proposed research will constitute a breakthrough in solution of problems related to efficient parallel computation of particle and fluid dynamics simulations. These problems occur throughout DOE, military and commercial sectors: the potential payoff is high. We plan to license or sell the solution to contractors for military and domestic applications such as disaster simulation (aerodynamic and hydrodynamic), Government agencies (hydrological and environmental simulations), and medical applications (e.g., in tomographic image reconstruction). Keywords - High-performance Computing, Graphic Processing Unit, Fluid/Particle Simulation. Summary for Members of Congress - Department of Energy has many simulation codes that must compute faster, to be effective. The Phase I research parallelized particle/fluid simulations for rocket combustion, for high-performance computing systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Optimizing the performance of reactive molecular dynamics simulations for many-core architectures

Reactive molecular dynamics simulations are computationally demanding. Reaching spatial and temporal scales where interesting scientific phenomena can be observed requires efficient and scalable implementations on modern hardware. In this article, we focus on optimizing the performance of the widely used LAMMPS/ReaxC package for many-core architectures. As hybrid parallelism allows better leverage of the increasing on-node parallelism, we adopt thread parallelism in the construction of bonded and nonbonded lists and in the computation of complex ReaxFF interactions. To mitigate the I/O overheads due to large volumes of trajectory data produced and to save users the burden of post-processing, we also develop a novel in situ tool for molecular species analysis. We analyze the performance of the resulting ReaxC-OMP package on two different architectures: (i) Mira, an IBM Blue Gene/Q system and (ii) Cori-II, a Cray XC-40 sytem with Knights Landing processors. For Pentaerythritol tetranitrate (PETN) systems of sizes ranging from 32 thousand to 16.6 million particles, we observe speedups in the range of 1.5-4.5x. We observe sustained performance improvements for up to 262,144 cores (1,048,576 processes) of Mira and a weak scaling efficiency of 91.5% in large simulations containing 16.6 million particles. Finally, the in situ molecular species analysis tool incurs only insignificant overheads across various system sizes and runs configurations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Photodynamics of oxybenzone sunscreen: Nonadiabatic dynamics simulations

Herein we have used combined static electronic structure calculations and “on-the-fly” global-switching trajectory surface-hopping dynamics simulations to explore the photochemical mechanism of oxybenzone sunscreen. We have first employed the multi-configurational CASSCF method to optimize minima, conical intersections, and minimum-energy reaction paths related to excited-state intramolecular proton transfer (ESIPT) and excited-state decays in the {sup 1}ππ{sup ∗}, {sup 1}nπ{sup ∗}, and S{sub 0} states (energies are refined at the higher MS-CASPT2 level). According to the mapped potential energy profiles, we have identified two ultrafast excited-state deactivation pathways for the initially populated {sup 1}ππ{sup ∗} system. The first is the diabatic ESIPT process along the {sup 1}ππ{sup ∗} potential energy profile. The generated {sup 1}ππ{sup ∗} keto species then decays to the S{sub 0} state via the keto {sup 1}ππ{sup ∗}/gs conical intersection. The second is internal conversion to the dark {sup 1}nπ{sup ∗} state near the {sup 1}ππ{sup ∗} /{sup 1}nπ{sup ∗} crossing point in the course of the diabatic {sup 1}ππ{sup ∗} ESIPT process. Our following dynamics simulations have shown that the ESIPT and {sup 1}ππ{sup ∗} → S{sub 0} internal conversion times are 104 and 286 fs, respectively. Finally, our present work demonstrates that in addition to the ESIPT process and the {sup 1}ππ{sup ∗} → S{sub 0} internal conversion in the keto region, the {sup 1}ππ{sup ∗} → {sup 1}nπ{sup ∗} internal conversion in the enol region plays as well an important role for the excited-state relaxation dynamics of oxybenzone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Integration of Dynamic Simulation for Infrastructure and Full Hardware Testing Capability into SCEPTRE

Sandia National Laboratories has an existing capability for hybrid control systems testing called SCEPTRE. This article proposes an architecture to add dynamic simulation capability for the underlying physical process (e.g. the power grid). Dynamic simulation for SCEPTRE will enable very accurate simulation, and allow the full integration of analog control systems hardware.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Molecular dynamics simulation of hydrodynamic transport coefficients in plasmas

Molecular dynamics simulations are used to calculate transport coefficients in a two-component plasma interacting through a repulsive Coulomb potential. The thermal conductivity, electrical conductivity, electrothermal coefficient, thermoelectric coefficient, and shear viscosity are computed using the Green–Kubo formalism over a broad range of Coulomb coupling strength, 0.01 ≤ Γ ≤ 140. Emphasis is placed on testing standard results of the Chapman–Enskog solution in the weakly coupled regime (Γ ≪ 1) using these first-principles simulations. As expected, the results show good agreement for Γ ≲ 0.1. However, this agreement is only possible if careful attention is paid to the definitions of linear constitutive relations in each of the theoretical models, a point that is often overlooked. For example, the standard Green–Kubo expression for thermal conductivity is a linear combination of thermal conductivity, electrothermal, and thermoelectric coefficients computed in the Chapman–Enskog formalism. Meaningful results for electrical conductivity are obtained over the full range of coupling strengths explored, but it is shown that potential and virial components of the other transport coefficients diverge in the strongly coupled regime (Γ ≫ 1). In this regime, only the kinetic components of the transport coefficients are meaningful for a classical plasma.

Electrical conductivity↗

DOE OSTI2011

ParaDiS-FEM dislocation dynamics simulation code primer

The ParaDiS code is developed to study bulk systems with periodic boundary conditions. When we try to perform discrete dislocation dynamics simulations for finite systems such as thin films or cylinders, the ParaDiS code must be extended. First, dislocations need to be contained inside the finite simulation box; Second, dislocations inside the finite box experience image stresses due to the free surfaces. We have developed in-house FEM subroutines to couple with the ParaDiS code to deal with free surface related issues in the dislocation dynamics simulations. This primer explains how the coupled code was developed, the main changes from the ParaDiS code, and the functions of the new FEM subroutines.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

Modeling of Protection in Dynamic Simulation Using Generic Relay Models and Settings

This paper shows how generic protection relay models available in planning tools can be augmented with settings that are based on NERC standards or best engineering practice. Selected generic relay models in Siemens PSS®E have been used in dynamic simulations in the proposed approach. Undervoltage, overvoltage, underfrequency, and overfrequency relays have been modeled for each generating unit. Distance-relay protection was modeled for transmission system protection. Two types of load-shedding schemes were modeled: underfrequency (frequency-responsive non-firm load shedding) and underfrequency and undervoltage firm load shedding. Several case studies are given to show the impact of protection devices on dynamic simulations. This is useful for simulating cascading outages.

cascading failures↗

DOE OSTI2015

Characterizing Dynamics of Anion/Pi Interactions through Molecular Dynamics Simulations

Proteins are not static structures, but undergo dynamical variations at room temperature that can lead to changes in the number and strength of different non-covalent interactions. The negatively charged (Asp/Glu) and aromatic (Phe/Trp/Tyr) amino acid groups in proteins can form anion/pi interactions, that have been shown to have a distance and angle dependency. This study characterizes the dynamic stability of these interactions in RmlC (PDB-1EP0), a homodimeric epimerase showing a cluster of six anion/pi pairs in crystal structure, as a function of time using Molecular Dynamics (MD) simulations. The dynamic variations found in these interactions correspond to a potential of mean force (PMF) that exhibits a relatively wide range of distances (~4.5 to~8.5Å) and angles (0 to~45deg) sampled by these anion/pi pairs. The corresponding PMF indicates an associated free energy change that can be more stabilizing (up to -5kcal/mol) than the ab initio-calculated interaction energy for the pairs in the crystal structure (-2.2kcal/mol). Possible anion/pi pairs and triplets (anion/anion/pi or anion/pi/pi) not seen in the crystal structure are also observed in other conformations sampled by the protein- both at the dimer interface and active site of the protein, forming an extensive network of anion/pi interactions covering most of the protein structure. Initial site-directed mutagenesis (SDM) experiments targeting one of these pairs, Asp84-Phe112, show that the single Phe/Met mutation decreases the stability of the protein compared to the wild type. Together these results suggest that anion-pi interactions can play an important role in maintaining both the structural stability and function of the proteins.

Kapoor, Karan↗

DOE OSTI2014

Interplay between the structure and dynamics in liquid and undercooled boron: An ab initio molecular dynamics simulation study

In the present work, the structural and dynamic properties of liquid and undercooled boron are investigated by means of ab initio molecular dynamics simulation. Our results show that both liquid and undercooled states present a well pronounced short-range order (SRO) mainly due to the formation of inverted umbrella structural units. Moreover, we observe the development of a medium-range order (MRO) in the undercooling regime related to the increase of inverted umbrella structural units and of their interconnection as the temperature decreases. We also evidence that this MRO leads to a partial crystallization in the β-rhombohedral crystal below T = 1900 K. Finally, we discuss the role played by the SRO and MRO in the nearly Arrhenius evolution of the diffusion and the non-Arrhenius temperature dependence of the shear viscosity, in agreement with the experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Bringing Molecular Dynamics Simulation Data into View

Molecular Dynamics (MD) simulations monitor time-resolved motions of macromolecules. While visualization of MD trajectories allows an instant and intuitive understanding of dynamics and function, so far mainly static representations are provided in published literature. Recent advances in browser technology may allow for the sharing of trajectories through interactive visualization on the web. We believe that by providing intuitive and interactive visualization along with related protocols and analysis data promotes understanding, reliability, and re-usability of MD simulations. Existing barriers for sharing MD simulations are discussed and emerging solutions are highlighted. We predict that interactive visualization of MD trajectories will quickly be adopted by researchers, research consortiums, journals, and funding agencies to gather and distribute results from MD simulations via the web.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Learning effective SDEs from Brownian dynamic simulations of colloidal particles

We construct a reduced, data-driven, parameter dependent effective stochastic differential equation (eSDE) for electric-field mediated colloidal crystallization using data obtained from Brownian dynamics simulations. We use diffusion maps (a manifold learning algorithm) to identify a set of useful latent observables. In this latent space we identify an eSDE using a deep learning architecture inspired by numerical stochastic integrators and compare it with the traditional Kramers–Moyal expansion estimation. We show that the obtained variables and the learned dynamics accurately encode the physics of the Brownian dynamic simulations. We further illustrate that our reduced model captures the dynamics of corresponding experimental data. Further, our dimension reduction/reduced model identification approach can be easily ported to a broad class of particle systems dynamics experiments/models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

High Fidelity Dynamic Simulation of Cycling in a Natural Gas Combined Cycle Power Plant

The CRADA objective is to use a high-fidelity natural gas combined cycle (NGCC) dynamic simulator deployed at the National Energy Technology Laboratory (NETL) to produce practical engineering ideas that would either reduce the impact on equipment resulting from cycling, or improve certain plant operational modes. The goal is to demonstrate to National Rural Electric Cooperative Association (NRECA) that a high-fidelity dynamic simulator offers a relatively low-cost option for investigation and testing without direct plant experimentation. Initial operation of the simulator revealed the potential for saturation conditions in the final high pressure superheater as the attemperator tried to control temperature at the superheater outlet during gas turbine loading and unloading. Subsequent plant operational data confirmed simulation results. Thus, this particular area was chosen for further investigation. Multiple simulations were performed during loading and unloading of the gas turbine in order to determine operational strategies that prevented saturation and increased the approach to saturation temperature. The results of these simulations are presented in this report. The summary at the end of this report suggests trials that could be performed at the plant to confirm the benefits seen by simulator investigations, such as changes to the attemperator temperature control setpoints and strategic control of the steam turbine inlet pressure control valve.

03 NATURAL GAS↗

DOE OSTI2020

Identification of preferred multimodal ligand‐binding regions on IgG1 F C using nuclear magnetic resonance and molecular dynamics simulations

Abstract In this study, the binding of multimodal chromatographic ligands to the IgG1 F C domain were studied using nuclear magnetic resonance and molecular dynamics simulations. Nuclear magnetic resonance experiments carried out with chromatographic ligands and a perdeuterated 15 N‐labeled F C domain indicated that while single‐mode ion exchange ligands interacted very weakly throughout the F C surface, multimodal ligands containing negatively charged and aromatic moieties interacted with specific clusters of residues with relatively high affinity, forming distinct binding regions on the F C . The multimodal ligand‐binding sites on the F C were concentrated in the hinge region and near the interface of the C H 2 and C H 3 domains. Furthermore, the multimodal binding sites were primarily composed of positively charged, polar, and aliphatic residues in these regions, with histidine residues exhibiting some of the strongest binding affinities with the multimodal ligand. Interestingly, comparison of protein surface property data with ligand interaction sites indicated that the patch analysis on F C corroborated molecular‐level binding information obtained from the nuclear magnetic resonance experiments. Finally, molecular dynamics simulation results were shown to be qualitatively consistent with the nuclear magnetic resonance results and to provide further insights into the binding mechanisms. An important contribution to multimodal ligand‐F C binding in these preferred regions was shown to be electrostatic interactions and π–π stacking of surface‐exposed histidines with the ligands. This combined biophysical and simulation approach has provided a deeper molecular‐level understanding of multimodal ligand–F C interactions and sets the stage for future analyses of even more complex biotherapeutics.

Gudhka, Ronak B.↗

DOE OSTI2024

Extended dynamic mode decomposition for model reduction in fluid dynamics simulations

High computational cost and storage/memory requirements of fluid dynamics simulations constrain their usefulness as a predictive tool. Reduced-order models (ROMs) provide a viable solution to this challenge by extracting the key underlying dynamics of a complex system directly from data. We investigate the efficacy and robustness of an extended dynamic mode decomposition (xDMD) algorithm in constructing ROMs of three-dimensional cardiovascular computations. Focusing on the ROMs' accuracy in representation and interpolation, we relate these metrics to the truncation rank of singular value decomposition, which underpins xDMD and other approaches to ROM construction. Our key innovation is to relate the truncation rank to the singular values of the original flow problem. This result establishes a priori guidelines for the xDMD deployment and its likely success as a means of data compression and reconstruction of the system's dynamics from dominant spatiotemporal structures present in the data.

Mechanics↗

DOE OSTI2023

Molecular dynamics simulation of Fe-Si alloys using a neural network machine learning potential

Interatomic potential development using machine learning (ML) approaches has attracted a lot of attention in recent years because these potentials can effectively describe the structural and dynamical properties of complex materials at the atomistic level. Here, in this work, we present the development of a neural network (NN) deep ML interatomic potential for Fe-Si alloys, and we demonstrate the effectiveness of the NN-ML potential in predicting the structures and energies of liquid and crystalline phases of Fe-Si alloys in comparison with the results from ab initio molecular dynamics simulations or experimental data. The developed NN-ML potential is also used to perform molecular dynamics simulations to study the structures of Fe-Si alloys with various compositions under rapid solidification conditions. The short-ranged orders in the rapidly solidified Fe-Si alloys are also analyzed by a cluster alignment method.

36 MATERIALS SCIENCE↗