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Results for “ensemble 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.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Molecular polarizability in open ensemble simulations of aqueous nanoconfinements under electric field

Molecular polarization at aqueous interfaces involves fast degrees of freedom that are often averaged-out in atomistic-modeling approaches. The resulting effective interactions depend on a specific environment, making explicit account of molecular polarizability particularly important in solutions with pronounced anisotropic perturbations, including solid/liquid interfaces and external fields. Our work concerns polarizability effects in nanoscale confinements under electric field, open to an unperturbed bulk environment. We model aqueous molecules and ions in hydrophobic pores using the Gaussian-charge-on-spring BK3-AH representation. This involves nontrivial methodology developments in expanded ensemble Monte Carlo simulations for open systems with long-ranged multibody interactions and necessitates further improvements for efficient modeling of polarizable ions. Structural differences between fixed-charge and polarizable models were captured in molecular dynamics simulations for a set of closed systems. Our open ensemble results with the BK3 model in neat-aqueous systems capture the ∼10% reduction of molecular dipoles within the surface layer near the hydrophobic pore walls in analogy to reported quantum mechanical calculations at water/vapor interfaces. The polarizability affects the interfacial dielectric behavior and weakens the electric-field dependence of water absorption at pragmatically relevant porosities. We observe moderate changes in thermodynamic properties and atom and charged-site spatial distributions; the Gaussian distribution of mobile charges on water and ions in the polarizable model shifts the density amplitudes and blurs the charge-layering effects associated with increased ion absorption. The use of polarizable force field indicates an enhanced response of interfacial ion distributions to applied electric field, a feature potentially important for in silico modeling of electric double layer capacitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Reduced Models for Chemical Kinetics derived from Parallel Ensemble Simulations of Stirred Reactors

Detailed chemical kinetic models are essential to improve the predictive capability of computational fluid dynamics (CFD) simulations and to impact the development of next generation combustion technologies. However, such detailed kinetic models are beyond the reach of CFD codes due to the computational cost of transporting additional chemical degrees of freedom. Reduced order models for combustion kinetics exploit the presence of lower dimensional manifolds in the state space and require far fewer number of scalars to be transported as part of CFD simulations. In this paper, we describe the software infrastructure developed to allow large ensembles of stirred reactor configurations with detailed chemical kinetics. The canonical reactor simulations are incorporated in a workflow with sparse grid and data reduction methodologies aimed at development of reduced order models. We present results from analyzing the results of the stirred reactor calculations for syngas mixture using principal component analysis (PCA) and neural network methodologies. The results show that nonlinear autoencoder model can surpass PCA in representing the original dataset with far fewer degrees of freedom.

Zhang, Pei↗
DOE OSTI2021

Advancing the Predictability of Water Cycle Phenomena via the Application of AI to Model Ensemble Simulations and Observations

AI has the power to identify new pathways to extended predictability of the water cycle via its application to model ensembles together with accompanying observations. We discuss both scientific and technological aspects of this challenge, and address the parts of the MODEX approach involving “Model simulations, evaluation, analysis, and benchmarking” and “Identification of key knowledge gaps”. The widespread incorporation of AI into model analysis will significantly advance Earth system predictability and our predictive capabilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ensemble Simulations on Leadership Computing Systems

Scientific productivity can be enhanced through workflow management tools, relieving large High Performance Computing (HPC) system users from the tedious tasks of scheduling and designing the complex computational execution of scientific applications. This paper presents a study on the usage of ensemble workflow tools to accelerate science using the Summit and Frontier supercomputing systems. The research aims to connect science domain simulations using Oak Ridge Leadership Computing Facility (OLCF) supercomputing platforms with ensemble workflow methods in order to accelerate HPC-enabled discovery and boost scientific impact. We present the coupling, porting and optimization of Radical-Cybertools on three applications: Chroma, NAMD and LAMMPS. The tools augment traditional HPC monolithic runs with a pilot scheduler. Lessons-learned are discussed for physics, biology and materials science applications. We discuss intrinsic limitations of coupling and porting ensemble workflow tools to applications that run on large HPC systems. The origins of technical challenges and their solutions developed during the implementation process are discussed. Data management strategies, OLCF’s policies for ensembles, and natively supported workflow tools are also summarized.

Georgiadou, Antigoni [ORNL] (ORCID:000000020977631↗
DOE OSTI2016

The free energy of the metastable supersaturated vapor via restricted ensemble simulations. III. An extension to the Corti and Debenedetti subcell constraint algorithm

In order to improve the sampling of restricted microstates in our previous work [C. Nie, J. Geng, and W. H. Marlow, J. Chem. Phys. 127, 154505 (2007); 128, 234310 (2008)] and quantitatively predict thermal properties of supersaturated vapors, an extension is made to the Corti and Debenedetti subcell constraint algorithm [D. S. Corti and P. Debenedetti, Chem. Eng. Sci. 49, 2717 (1994)], which restricts the maximum allowed local density at any point in a simulation box. The maximum allowed local density at a point in a simulation box is defined by the maximum number of particles N{sub m} allowed to appear inside a sphere of radius R, with this point as the center of the sphere. Both N{sub m} and R serve as extra thermodynamic variables for maintaining a certain degree of spatial homogeneity in a supersaturated system. In a restricted canonical ensemble, at a given temperature and an overall density, series of local minima on the Helmholtz free energy surface F(N{sub m}, R) are found subject to different (N{sub m}, R) pairs. The true equilibrium metastable state is identified through the analysis of the formation free energies of Stillinger clusters of various sizes obtained from these restricted states. The simulation results of a supersaturated Lennard-Jones vapor at reduced temperature 0.7 including the vapor pressure isotherm, formation free energies of critical nuclei, and chemical potential differences are presented and analyzed. In addition, with slight modifications, the current algorithm can be applied to computing thermal properties of superheated liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Simulating ensembles of nonlinear continuous time dynamical systems via active ultra wideband wireless network

The paper deals with a new multi-element processor platform assigned for modelling the behaviour of interacting dynamical systems, i.e., active wireless network. Experimentally, this ensemble is implemented in an active network, the active nodes of which include direct chaotic transceivers and special actuator boards containing microcontrollers for modelling the dynamical systems and an information display unit (colored LEDs). The modelling technique and experimental results are described and analyzed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Ensemble simulations of inertial confinement fusion implosions

The achievement of inertial confinement fusion ignition on the National Ignition Facility relies on the collection and interpretation of a limited (and expensive) set of experimental data. These data are therefore supplemented with state-of-the-art multi-dimensional radiation-hydrodynamic simulations to provide a better understanding of implosion dynamics and behavior. We present a relatively large number (~4000) of systematically perturbed 2D simulations to probe our understanding of low-mode fuel and ablator asymmetries seeded by asymmetric illumination. We find that Gaussian process surrogate models are able to predict both the total neutron yield and the degradation in performance due to asymmetries. Furthermore, the surrogates are then applied to simulations containing new sources of degradation to quantify the impact of the new source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Ensemble Simulations and Experimental Free Energy Distributions: Evaluation and Characterization of Isoxazole Amides as SMYD3 Inhibitors

Optimization of binding affinities for ligands to their target protein is a primary objective in rational drug discovery. Herein, we report on a collaborative study that evaluates various compounds designed to bind to the SET and MYND domain-containing protein 3 (SMYD3). SMYD3 is a histone methyltransferase and plays an important role in transcriptional regulation in cell proliferation, cell cycle, and human carcinogenesis. Experimental measurements using the scintillation proximity assay show that the distributions of binding free energies from a large number of independent measurements exhibit non-normal properties. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to predict the binding free energies and to provide a detailed chemical insight into the nature of ligand-protein binding. Our results show that the 1-trajectory ESMACS protocol works well for the set of ligands studied here. Although one unexplained outlier exists, we obtain excellent statistical ranking across the set of compounds from the ESMACS protocol and good agreement between calculations and experiments for the relative binding free energies from the TIES protocol. ESMACS and TIES are again found to be powerful protocols for the accurate comparison of the binding free energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

A Framework to Analyze the Performance of Load Balancing Schemes for Ensembles of Stochastic Simulations

Ensembles of simulations are employed to estimate the statistics of possible future states of a system, and are widely used in important applications such as climate change and biological modeling. Ensembles of runs can naturally be executed in parallel. However, when the CPU times of individual simulations vary considerably, a simple strategy of assigning an equal number of tasks per processor can lead to serious work imbalances and low parallel efficiency. This paper presents a new probabilistic framework to analyze the performance of dynamic load balancing algorithms for ensembles of simulations where many tasks are mapped onto each processor, and where the individual compute times vary considerably among tasks. Four load balancing strategies are discussed: most-dividing, all-redistribution, random-polling, and neighbor-redistribution. Simulation results with a stochastic budding yeast cell cycle model are consistent with the theoretical analysis. It is especially significant that there is a provable global decrease in load imbalance for the local rebalancing algorithms due to scalability concerns for the global rebalancing algorithms. The overall simulation time is reduced by up to 25 %, and the total processor idle time by 85 %.

ALGORITHMS↗
DOE OSTI2018

Mechanochemical formation of heterogeneous diamond structures during rapid uniaxial compression in graphite

We predict mechanochemical formation of heterogeneous diamond structures from rapid uniaxial compression in graphite using quantum molecular dynamics simulations. Ensembles of simulations reveal the formation of different diamondlike products starting from thermal graphite crystal configurations. Here in this paper, we identify distinct classes of final products with characteristic probabilities of formation, stress states, and electrical properties and show through simulations of rapid quenching that these products are nominally stable and can be recovered at room temperature and pressure. Some of the diamond products exhibit significant disorder and partial closure of the energy gap between the highest-occupied and lowest-unoccupied molecular orbitals (i.e., the HOMO-LUMO gap). Seeding atomic vacancies in graphite significantly biases toward forming products with small HOMO-LUMO gap. We show that a strong correlation between the HOMO-LUMO gap and disorder in tetrahedral bonding configurations informs which kinds of structural defects are associated with gap closure. The rapid diffusionless transformation of graphite is found to lock vacancy defects into the final diamond structure, resulting in configurations that prevent sp 3 bonding and lead to localized HOMO and LUMO states with a small gap.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Sensitivity Analysis of Wind and Turbulence Predictions With Mesoscale‐Coupled Large Eddy Simulations Using Ensemble Machine Learning

Abstract Coupling between mesoscale models and large‐eddy simulation (LES) models is increasingly used to more realistically represent the wide range of scales of atmospheric motions affecting boundary layer winds and turbulence that need to be simulated accurately for applications such as wind energy. However, such mesoscale‐to‐microscale coupled modeling frameworks are potentially affected by a large number of uncertain closure parameters. Here, we investigate the sensitivity associated with six closure parameters related to a 1.5‐order subgrid‐scale turbulence closure for an ensemble of mesoscale‐coupled LES. The simulations are performed using the Weather Research and Forecasting model nested from horizontal resolutions of greater than a kilometer down to tens of meters. Closure parameters are varied to generate perturbed parameter ensembles for two case studies of highly sheared, convective boundary layers observed in the Columbia Basin of Oregon and Washington during the Second Wind Forecast Improvement Project. Machine learning algorithms are used to explore the sensitivity of LES predictions, considering the effects of the perturbed physical parameters alongside categorical factors such as the case study identity, measurement location, and LES resolution. For the conditions we examine, a single parameter, the eddy viscosity coefficient, is the dominant source of parametric sensitivity and its importance is comparable to the categorical factors for several of the simulation response variables we examine.

54 ENVIRONMENTAL SCIENCES↗