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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A data-driven multiscale model for reactive wetting simulations

Here, we describe a data-driven, multiscale technique to model reactive wetting of a silver–aluminum alloy on a Kovar™ (Fe-Ni-Co alloy) surface. We employ molecular dynamics simulations to elucidate the dependence of surface tension and wetting angle on the drop’s composition and temperature. A design of computational experiments is used to efficiently generate training data of surface tension and wetting angle from a limited number of molecular dynamics simulations. The simulation results are used to parameterize models of the material’s wetting properties and compute the uncertainty in the models due to limited data. The data-driven models are incorporated into an engineering-scale (continuum) model of a silver–aluminum sessile drop on a Kovar™ substrate. Model predictions of the wetting angle are compared with experiments of pure silver spreading on Kovar™ to quantify the model-form errors introduced by the limited training data versus the simplifications inherent in the molecular dynamics simulations. The paper presents innovations in the determination of “convergence” of noisy MD simulations before they are used to extract the wetting angle and surface tension, and the construction of their models which approximate physio-chemical processes that are left unresolved by the engineering-scale model. Together, these constitute a multiscale approach that integrates molecular-scale information into continuum scale models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Validation of Fault Displacements from Dynamic Rupture Simulations against the Observations from the 1992 Landers Earthquake

ABSTRACT Coseismic fault displacements in large earthquakes have caused significant damage to structures and lifelines on and near fault lines. Coseismic displacements represent a real threat, especially to distributed infrastructure systems. For infrastructure systems that can not avoid active faults, engineering displacement demands are defined using probabilistic fault-displacement hazard analyses (PFDHA). However, PFDHA models are sparse and poorly constrained partly due to the scarcity of detailed fault-displacement observations. Advancements in dynamic rupture simulation methods make them an attractive approach to address this important issue. Because fault displacements can be simulated for various geologic conditions as constrained by current knowledge about earthquake processes, they can be used to supplement the observation datasets. In addition to providing on-fault displacements, when used with appropriate constitutive models for the bulk medium, they can capture off-fault distributed inelastic deformations as well. For viable extrapolation, simulations must first be validated against data. In this article, we summarize the calibration and validation of the dynamic rupture model against the observations of the well-documented 1992 Landers earthquake. We defined a preferred model that reproduces several first-order fault-displacement metrics such as the on-fault partition of the total displacement, the mean fault-zone width, and the location of the peak displacement. Simulated ground motions consistent with the observations ensure that all physics important to modeling have been properly parameterized. For the extrapolation, we generated a suite of dynamic rupture models to quantify expected fault-displacement metrics, their intercorrelations, and magnitude dependencies, which are in part supported by the Landers and other recent earthquakes. Our validation and extrapolation exercise paves the way for using dynamic rupture modeling to quantitatively address fault-displacement hazard on a broader scale. The results are promising and are expected to be useful to inform PFDHA model development.

Geochemistry & Geophysics↗
DOE OSTI2017

Numerical simulation and dynamical response of a moored hydrokinetic turbine operating in the wake of an upstream turbine for control design

Herein numerical simulation of a downstream hydrokinetic turbine operating in the wake of an upstream turbine for feedback control design is presented. Wake effects from an upstream turbine are quantified in terms of wake velocity and amplified turbulence levels. These effects are integrated in an in-stream hydrokinetic turbine numerical simulation that utilizes a Blade Element Momentum approach with a dynamic wake inflow model. Simulations are carried out on a fixed turbine model to simulate operation in river or tidal channels with conventional foundations, as well as on a compliantly moored turbine model such as those designed to operate in open ocean currents.

13 HYDRO ENERGY↗
DOE OSTI2012

Multiscale simulation of thermomechanical processes in irradiated fission-reactor materials

The work funded from this project has been published in six papers, with two more in draft form, with submission planned for the near future. The papers are: (1) Kinetically-Evolving Irradiation-Induced Point-Defect Clusters in UO 2 by Molecular-Dynamics Simulation; (2) Kinetically driven point-defect clustering in irradiated MgO by molecular-dynamics simulation; (3) Grain-Boundary Source/Sink Behavior for Point Defect: An Atomistic Simulation Study; (4) Energetics of intrinsic point defects in uranium dioxide from electronic structure calculations; (5) Thermodynamics of fission products in UO 2 ±x; and (6) Atomistic study of grain boundary sink strength under prolonged electron irradiation. The other two pieces of work that are currently being written-up for publication are: (1) Effect of Pores and He Bubbles on the Thermal Transport Properties of UO 2 by Molecular Dynamics Simulation; and (2) Segregation of Ruthenium to Edge Dislocations in Uranium Dioxide.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

PB-AM: An open-source, fully analytical linear poisson-boltzmann solver

Here, we present the open source distributed software package Poisson-Boltzmann Analytical Method (PB-AM), a fully analytical solution to the linearized PB equation, for molecules represented as non-overlapping spherical cavities. The PB-AM software package includes the generation of outputs files appropriate for visualization using visual molecular dynamics, a Brownian dynamics scheme that uses periodic boundary conditions to simulate dynamics, the ability to specify docking criteria, and offers two different kinetics schemes to evaluate biomolecular association rate constants. Given that PB-AM defines mutual polarization completely and accurately, it can be refactored as a many-body expansion to explore 2- and 3-body polarization. Additionally, the software has been integrated into the Adaptive Poisson-Boltzmann Solver (APBS) software package to make it more accessible to a larger group of scientists, educators, and students that are more familiar with the APBS framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

AVESTAR Center for Operational Excellence of Electricity Generation Plants

To address industry challenges in attaining operational excellence for electricity generation plants, the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) has launched a world-class facility for Advanced Virtual Energy Simulation Training and Research (AVESTARTM). This presentation will highlight the AVESTARTM Center simulators, facilities, and comprehensive training, education, and research programs focused on the operation and control of high-efficiency, near-zero-emission electricity generation plants. The AVESTAR Center brings together state-of-the-art, real-time, high-fidelity dynamic simulators with full-scope operator training systems (OTSs) and 3D virtual immersive training systems (ITSs) into an integrated energy plant and control room environment. AVESTAR’s initial offering combines--for the first time--a “gasification with CO2 capture” process simulator with a “combined-cycle” power simulator together in a single OTS/ITS solution for an integrated gasification combined cycle (IGCC) power plant with carbon dioxide (CO2) capture. IGCC systems are an attractive technology option for power generation, especially when capturing and storing CO2 is necessary to satisfy emission targets. The AVESTAR training program offers a variety of courses that merge classroom learning, simulator-based OTS learning in a control-room operations environment, and immersive learning in the interactive 3D virtual plant environment or ITS. All of the courses introduce trainees to base-load plant operation, control, startups, and shutdowns. Advanced courses require participants to become familiar with coordinated control, fuel switching, power-demand load shedding, and load following, as well as to problem solve equipment and process malfunctions. Designed to ensure work force development, training is offered for control room and plant field operators, as well as engineers and managers. Such comprehensive simulator-based instruction allows for realistic training without compromising worker, equipment, and environmental safety. It also better prepares operators and engineers to manage the plant closer to economic constraints while minimizing or avoiding the impact of any potentially harmful, wasteful, or inefficient events. The AVESTAR Center is also used to augment graduate and undergraduate engineering education in the areas of process simulation, dynamics, control, and safety. Students and researchers gain hands-on simulator-based training experience and learn how the commercial-scale power plants respond dynamically to changes in manipulated inputs, such as coal feed flow rate and power demand. Students also analyze how the regulatory control system impacts power plant performance and stability. In addition, students practice start-up, shutdown, and malfunction scenarios. The 3D virtual ITSs are used for plant familiarization, walk-through, equipment animations, and safety scenarios. To further leverage the AVESTAR facilities and simulators, NETL and its university partners are pursuing an innovative and collaborative R&D program. In the area of process control, AVESTAR researchers are developing enhanced strategies for regulatory control and coordinated plant-wide control, including gasifier and gas turbine lead, as well as advanced process control using model predictive control (MPC) techniques. Other AVESTAR R&D focus areas include high-fidelity equipment modeling using partial differential equations, dynamic reduced order modeling, optimal sensor placement, 3D virtual plant simulation, and modern grid. NETL and its partners plan to continue building the AVESTAR portfolio of dynamic simulators, immersive training systems, and advanced research capabilities to satisfy industry’s growing need for training and experience with the operation and control of clean energy plants. Future dynamic simulators under development include natural gas combined cycle (NGCC) and supercritical pulverized coal (SCPC) plants with post-combustion CO2 capture. These dynamic simulators are targeted for use in establishing a Virtual Carbon Capture Center (VCCC), similar in concept to the DOE’s National Carbon Capture Center for slipstream testing. The VCCC will enable developers of CO2 capture technologies to integrate, test, and optimize the operation of their dynamic capture models within the context of baseline power plant dynamic models. The objective is to provide hands-on, simulator-based “learn-by-operating” test platforms to accelerate the scale-up and deployment of CO2 capture technologies. Future AVESTAR plans also include pursuing R&D on the dynamics, operation, and control of integrated electricity generation and storage systems for the modern grid era. Special emphasis will be given to combining load-following energy plants with renewable and distributed generating supplies and fast-ramping energy storage systems to provide near constant baseload power.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Developing a Reduced 240-Bus WECC Dynamic Model for Frequency Response Study of High Renewable Integration

The ongoing changes in the generation resource mix, driven by the rapid adoption of inverter-based resources (IBR) as well as the early retirement of synchronous generators, are bringing new challenges to the planning and operation of bulk electric power systems. Consequently, there is an increasing need to understand, design, and quantify the reliability service provision from IBRs by performing integrated scheduling and dynamic simulations. However, test systems that have consistent scheduling and dynamic models rarely exist largely because of the decoupled nature of the two simulations on a synchronous generator-dominated system. This paper develops the dynamic model of a reduced Western Electricity Coordinating Council (WECC) system. In conjunction with the existing scheduling model, it is suitable for integrating scheduling and dynamic simulations. The reduced 240-bus WECC model reflects the generation resource mix of the Western Interconnection as of 2018. Moreover, the developed dynamic model is validated against field frequency events measured by FNET/GridEye and preserves the dominant inter-area oscillation mode in WECC.

dynamic simulation↗
DOE OSTI2018

Validation of Deterministic Broadband Ground Motion and Variability from Dynamic Rupture Simulations of Buried Thrust Earthquakes

According to the article, we numerically model broadband ground motion (up to 5–7.5 Hz⁠) from blind‐thrust scenario earthquakes matching the fault geometry of the 1994 Mw 6.7 Northridge earthquake. Several realizations are modeled (by varying the hypocenter location in the dynamic rupture simulation) in a 1D‐layered velocity profile. In addition, we include Q(f )⁠, nonlinear effects from Drucker–Prager plasticity, and superimpose small‐scale medium complexity in both a 1D‐layered and 3D velocity model within the subsequent wave propagation. We investigate characteristics of the ground motion and its variability up to 50 km from the fault by comparing them with ground‐motion prediction equations (GMPEs), simple proxy metrics, as well as strong ground motion records from the Northridge event. We find that median ground motion closely follows the trend predicted by GMPEs and that the intraevent standard deviation, although varying with hypocenter location, lies near that of GMPE models. Plasticity affects ground‐motion amplitudes in regions near the source, reducing intraevent variability above ∼0.5 Hz⁠. Heterogeneity in the velocity structure on both the regional and small scales is needed for the simulated data to match two proxy metrics: the period‐to‐period correlation of spectral acceleration (SA) and the ratio of maximum‐to‐median SA. Although small‐scale heterogeneity has a negligible effect on median SA for this style of rupture, it serves to significantly increase the cumulative absolute velocity, better agreeing with observations. When compared with strong‐motion data, we find that long‐wavelength velocity structure within our deterministic simulations reduces bias at both short and long periods. Finally, synthetic ground motion at both footwall and hanging‐wall sites has no clear dependence on the distance to rupture (at both short and long periods); directivity is likely overpowering any hanging‐wall effect.

Geochemistry & Geophysics↗
DOE OSTI2016

Insight into the Li{sub 2}CO{sub 3}–K{sub 2}CO{sub 3} eutectic mixture from classical molecular dynamics: Thermodynamics, structure, and dynamics

We use molecular dynamics simulations to study the thermodynamics, structure, and dynamics of the Li{sub 2}CO{sub 3}–K{sub 2}CO{sub 3} (62:38 mol. %) eutectic mixture. We present a new classical non-polarizable force field for this molten salt mixture, optimized using experimental and first principles molecular dynamics simulations data as reference. This simple force field allows efficient molecular simulations of phenomena at long time scales. We use this optimized force field to describe the behavior of the eutectic mixture in the 900–1100 K temperature range, at pressures between 0 and 5 GPa. After studying the equation of state in these thermodynamic conditions, we present molecular insight into the structure and dynamics of the melt. In particular, we present an analysis of the temperature and pressure dependence of the eutectic mixture’s self-diffusion coefficients, viscosity, and ionic conductivity.

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

Imogolite in water: Simulating the effects of nanotube curvature on structure and dynamics

Imogolite is a fascinating inorganic nanotube that is found in nature or synthesized in a laboratory. The synthesis process is carried out in liquid media, and leads to the formation of almost monodisperse diameter nanotubes. Here we investigate, employing classical molecular dynamics simulations, the interaction of water and imogolite for nanotubes of several radii. We established that water penetrates the pores of N = 9 and larger nanotubes, and adopts a coaxial arrangement in it. Also, while water molecules can diffuse along the center of the nanotube, the molecules next to the inner imogolite walls have very low mobility. At the outer nanotube wall, an increase of water density is observed, this effect extends up to 1 nm, beyond which water properties are bulk-like. Both phenomena are affected by the imogolite curvature.

58 GEOSCIENCES↗
DOE OSTI2015

At least 10% shorter C–H bonds in cryogenic protein crystal structures than in current AMBER forcefields

High resolution protein crystal structures resolved with X-ray diffraction data at cryogenic temperature are commonly used as experimental data to refine forcefields and evaluate protein folding simulations. However, it has been unclear hitherto whether the C–H bond lengths in cryogenic protein structures are significantly different from those defined in forcefields to affect protein folding simulations. This article reports the finding that the C–H bonds in high resolution cryogenic protein structures are 10–14% shorter than those defined in current AMBER forcefields, according to 3709 C–H bonds in the cryogenic protein structures with resolutions of 0.62–0.79 Å. Also, 20 all-atom, isothermal–isobaric, 0.5-μs molecular dynamics simulations showed that chignolin folded from a fully-extended backbone formation to the native β-hairpin conformation in the simulations using AMBER forcefield FF12SB at 300 K with an aggregated native state population including standard error of 10 ± 4%. However, the aggregated native state population with standard error reduced to 3 ± 2% in the same simulations except that C–H bonds were shortened by 10–14%. Furthermore, the aggregated native state populations with standard errors increased to 35 ± 3% and 26 ± 3% when using FF12MC, which is based on AMBER forcefield FF99, with and without the shortened C–H bonds, respectively. These results show that the 10–14% bond length differences can significantly affect protein folding simulations and suggest that re-parameterization of C–H bonds according to the cryogenic structures could improve the ability of a forcefield to fold proteins in molecular dynamics simulations. - Highlights: • Cryogenic crystal structures are commonly used in computational studies of proteins. • C–H bonds in the cryogenic structures are shorter than those defined in forcefields. • A survey of 3709 C–H bonds shows that the cryogenic bonds are 10–14% shorter. • The 10–14% differences affect molecular dynamics simulations of protein folding. • Shortening C–H bonds by 10–14% can improve protein folding simulations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Data-Driven Security Assessment of Power Grids Based on Machine Learning Approach: Preprint

Data-driven security assessment provides key indicators on power system stability using simulations on scheduling models, as opposed to dynamic simulations that are more time-consuming. This paper investigates data-driven security assessment of power grids based on machine learning. Multivariate random forest regression is used as the machine learning algorithm due to its high robustness to the input data. Three stability issues are analyzed using the proposed machine learning tool, including transient stability, frequency stability and small signal stability. The estimation values from machine learning tool are compared with those from dynamic simulations. Results show that the proposed machine learning tool can effectively predict the stability margins for the three stability metrics.

14 SOLAR ENERGY↗
DOE OSTI2018

Molecular dynamics studies of fundamental bulk properties of palladium hydrides for hydrogen storage

Solid-state hydrogen storage materials undergo complex phase transformations whose behavior are collectively determined by thermodynamic (e.g., Gibbs free energy), mechanical (e.g., lattice and elastic constants), and mass transport (e.g., diffusivity) properties. These properties depend on the reaction conditions and evolve continuously during (de)hydrogenation. Thus, they are difficult to measure in experiments. Because of this, past progress to improve solid-state hydrogen storage materials has been prolonged. Using PdH x as a representative example for interstitial metal hydride, we have recently applied molecular dynamics simulations to quantify hydrogen diffusion in the entire reaction space of temperature and composition. In this paper, we have further applied molecular dynamics simulations to obtain well-converged expressions for lattice constants, Gibbs free energies, and elastic constants of PdH x at various stages of the reaction. Finally, our studies confirm significant dependence of elastic constants on temperature and composition. Specifically, a new dynamic effect of hydrogen diffusion on elastic constants is discovered and discussed.

08 HYDROGEN↗
DOE OSTI2023

Simulation-Based Recovery Action Analysis Using the EMRALD Dynamic Risk Assessment Tool

Recovery human action is defined as the action that prevents deviant conditions from producing unwanted effects. Analyzing recovery actions has been a critical part in human reliability analysis (HRA). However, there are a couple of limitations to treating recovery actions using only the current HRA methods available. Representatively, the existing recovery analysis does not specifically consider recovery actions as they have occurred in actual nuclear power plants (NPPs). To handle the challenges in the existing recovery analyses, this study suggests a way to analyze recovery actions under a dynamic HRA method, the Procedure-based Risk Investigation MEthod-Human Reliability Analysis (PRIME-HRA) method. The PRIME-HRA method suggests a way on how to develop dynamic simulation models using dynamic risk assessment tools such as the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) [1] and the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) [2]. EMRALD and HUNTER are the dynamic probabilistic risk assessment and HRA tools developed at Idaho National Laboratory. In this paper, differences on analyzing recovery actions in the Technique for Human Error-Rate Prediction (THERP), the Cause-Based Decision Tree (CBDT) and the Korean Standard HRA (K-HRA) and challenges of these approaches are introduced. How we have developed the PRIME-HRA is also introduced in this paper. Then, the proposed approach to analyzing recovery human actions in dynamic context is partially discussed with an example.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Quantifying Economic and Environmental Impacts of Transportation Network Disruptions with Dynamic Traffic Simulation

Several transportation network vulnerability models have been proposed. However, most only consider disruptions as a static snapshot in time and the impact on total travel time. These approaches cannot consider the time-varying nature of travel demand nor other undesirable outcomes that follow from transportation network disruptions. This paper proposes an algorithmic approach to assess the vulnerability of a transportation network that considers the time-varying demand with an open source dynamic transportation simulation tool. The open source nature of the tool allows us to systematically consider many disruption scenarios and quantitatively compare their relative criticality. This is far more efficient than traditional approaches which would require days or weeks of a transportation engineers time to manually set up, run, and assess these simulations. In addition to travel time, we also collect statistics on additional fuel consumed and the corresponding carbon dioxide emissions. Our approach, thus provides a more systematic approach that is both time-varying and can consider additional negative consequences of disruptions for decision makers to evaluate.

Shekar, Venkateswaran↗
DOE OSTI2016

Nanocarbon synthesis by high-temperature oxidation of nanoparticles

High-temperature oxidation of silicon-carbide nanoparticles (nSiC) underlies a wide range of technologies from high-power electronic switches for efficient electrical grid and thermal protection of space vehicles to self-healing ceramic nanocomposites. Here, multimillion-atom reactive molecular dynamics simulations validated by ab initio quantum molecular dynamics simulations predict unexpected condensation of large graphene flakes during high-temperature oxidation of nSiC. Initial oxidation produces a molten silica shell that acts as an autocatalytic ‘nanoreactor’ by actively transporting oxygen reactants while protecting the nanocarbon product from harsh oxidizing environment. Percolation transition produces porous nanocarbon with fractal geometry, which consists of mostly sp 2 carbons with pentagonal and heptagonal defects. Furthermore, this work suggests a simple synthetic pathway to high surface-area, low-density nanocarbon with numerous energy, biomedical and mechanical-metamaterial applications, including the reinforcement of self-healing composites.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Implicit integration methods for dislocation dynamics

In dislocation dynamics simulations, strain hardening simulations require integrating stiff systems of ordinary differential equations in time with expensive force calculations, discontinuous topological events, and rapidly changing problem size. Current solvers in use often result in small time steps and long simulation times. Faster solvers may help dislocation dynamics simulations accumulate plastic strains at strain rates comparable to experimental observations. Here, this paper investigates the viability of high order implicit time integrators and robust nonlinear solvers to reduce simulation run times while maintaining the accuracy of the computed solution. In particular, implicit Runge-Kutta time integrators are explored as a way of providing greater accuracy over a larger time step than is typically done with the standard second-order trapezoidal method. In addition, both accelerated fixed point and Newton's method are investigated to provide fast and effective solves for the nonlinear systems that must be resolved within each time step. Results show that integrators of third order are the most effective, while accelerated fixed point and Newton's method both improve solver performance over the standard fixed point method used for the solution of the nonlinear systems.

36 MATERIALS SCIENCE↗