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At least 1,369 records · Page 76

High-temperature active oxidation of nanocrystalline silicon-carbide: A reactive force-field molecular dynamics study

Flexible woven SiC ceramics are prone to accelerated fiber embrittlement under high temperature oxidation in dynamic oxygen environments. The nanocrystalline structure of the constituent fibers impacts the reaction kinetics and phase transformations during active oxidation. However, fundamental understanding and quantification of grain boundary effects on oxidation behavior in nanocrystalline SiC remain elusive when temperatures exceed 1500 K. This study deploys large-scale molecular dynamics simulations with a reactive force-field to elucidate the complex roles of atomic oxygen reservoir conditions and grain size on oxidation kinetics and the nature of oxides produced in both monocrystalline and nanocrystalline 3C-SiC between 1100 K and 2000 K. The simulations with dynamically replenished oxygen provide good agreement with oxidation kinetics and activation energies for the monocrystalline Si(100) and C(100) orientations published in the available literature. This study reveals that, by contrast, nanocrystalline SiC samples exhibit two distinct oxidation kinetics with a transition point at 1500 K due to surface melting, which is supported by experimental evidence. The introduction of a grain-boundary network produces a two-fold decrease in oxidation activation energies compared to monocrystalline SiC below 1500 K. Above 1500 K, however, the activation energies rise substantially due to the formation of a liquid Si phase at the SiC/Si oxide interface. Further, it is shown that the stability of the interfacial liquid phase is promoted by incoherent grain boundaries in the crystalline SiC. These findings are important for the deployment of nanocrystalline SiC fibers in advanced thermal protection systems for high-temperature applications.

36 MATERIALS SCIENCE↗

Molecular Insight into the Effects of Clustering on the Dynamics of Ionomers in Solutions

Ionizable groups tethered to polymers enable their many current and potential applications. However, these functionalities drive the formation of physical networks through clustering of the ionic groups, resulting in constrained dynamics of the macromolecules. Understanding the molecular origin of this hindrance remains a critical fundamental question, whose solution will directly impact the processing of ionizable polymers from molecules to viable materials. Here, in this work, using quasielastic neutron scattering accompanied by molecular dynamics simulations, segmental dynamics of slightly sulfonated polystyrene is studied in solutions as the cohesion of the ionic assemblies is tuned. We find that in cyclohexane the ionic assemblies act as centers of confinement, affecting dynamics both on macroscopic lengths and in the vicinity of the ionic assemblies. Addition of a small amount of ethanol affects the packing of the ionizable groups within the assemblies, which in turn enhances the chain dynamics.

36 MATERIALS SCIENCE↗

Learning-Based Load Control to Support Resilient Networked Microgrid Operations

Microgrids have proven to be an effective option for increasing the resiliency of critical end-use loads during extreme events. Building on past operational experiences, some microgrid operators are examining the potential to network microgrids to further improve resiliency. However, the frequency deviations experienced on isolated microgrids during transient events, such as switching operations, step increases in load, and loss of generation, are significantly larger than those typically seen on bulk transmission systems. The larger frequency deviations can cause a loss of inverter-connected assets, resulting in a loss of power to critical end-use loads. This paper presents a method of mitigating the impact of transient events by engaging end-use loads using Grid-Friendly Appliance TM (GFA) controllers. An online, i.e., real-time, device-level algorithm is presented, which adjusts individual GFA controller frequency set-points based on the operational characteristics of each end-use load, and on the changing grid dynamic characteristics. The presented method improves the dynamic stability of the networked microgrid operations while minimizing the interruptions to end-use loads. The presented work is validated with dynamic simulations using a modified version of the IEEE 123-node test system with three microgrids, using the GridLAB-D TM simulation environment.

Radhakrishnan, Nikitha↗

Coherent dynamic structure factors of strongly coupled plasmas: A generalized hydrodynamic approach

A generalized hydrodynamic fluctuation model is proposed to simplify the calculation of the dynamic structure factor S(ω, k) of non-ideal plasmas using the fluctuation-dissipation theorem. In this model, the kinetic and correlation effects are both included in hydrodynamic coefficients, which are considered as functions of the coupling strength (Γ) and collision parameter (kλ{sub ei}), where λ{sub ei} is the electron-ion mean free path. A particle-particle particle-mesh molecular dynamics simulation code is also developed to simulate the dynamic structure factors, which are used to benchmark the calculation of our model. A good agreement between the two different approaches confirms the reliability of our model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dynamical Structure Factor of the Three-Dimensional Quantum Spin Liquid Candidate NaCaNi 2 F 7

We study the dynamical structure factor of the spin-1 pyrochlore material NaCaN 2 F 7 , which is well described by a weakly perturbed nearest-neighbour Heisenberg Hamiltonian, Our three approaches—molecular dynamics simulations, stochastic dynamical theory, and linear spin wave theory—reproduce remarkably well the momentum dependence of the experimental inelastic neutron scattering intensity as well as its energy dependence with the exception of the lowest energies. Here, we discuss two surprising aspects and their implications for quantum spin liquids in general: the complete lack of sharp quasiparticle excitations in momentum space and the success of the linear spin wave theory in a regime where it would be expected to fail for several reasons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Computing Free Energies with Fluctuation Relations on Quantum Computers

As a central thermodynamic property, free energy enables the calculation of virtually any equilibrium property of a physical system, allowing for the construction of phase diagrams and predictions about transport, chemical reactions, and biological processes. Thus, methods for efficiently computing free energies, which in general is a difficult problem, are of great interest to broad areas of physics and the natural sciences. The majority of techniques for computing free energies target classical systems, leaving the computation of free energies in quantum systems less explored. Recently developed fluctuation relations enable the computation of free energy differences in quantum systems from an ensemble of dynamic simulations. While performing such simulations is exponentially hard on classical computers, quantum computers can efficiently simulate the dynamics of quantum systems. Here, we present an algorithm utilizing a fluctuation relation known as the Jarzynski equality to approximate free energy differences of quantum systems on a quantum computer. In this work we discuss under which conditions our approximation becomes exact, and under which conditions it serves as a strict upper bound. Furthermore, we successfully demonstrate a proof of concept of our algorithm using the transverse field Ising model on a real quantum processor. As quantum hardware continues to improve, we anticipate that our algorithm will enable computation of free energy differences for a wide range of quantum systems useful across the natural sciences.

97 MATHEMATICS AND COMPUTING↗

Load Margin Constrained Moving Target Defense against False Data Injection Attacks

Cyber physical security of power systems with high penetration of renewable generation has attracted attention from researchers. One critical issue is that cyber-physical attacks, disguised as uncertain renewable generation, can target conventional power system state estimation (SE). Moving target defense (MTD) is a promising defense strategy to detect stealthy false data injection (FDI) attacks against SE. However, all existing studies myopically perturb the reactance of transmission lines equipped with distributed flexible AC transmission system (D-FACTS) devices without adequately considering the system voltage stability. Exacerbated by the renewable generation uncertainty, existing MTD may cause voltage instability when the power grid is under stress. To address this issue, we propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow. We utilize the sensitivity matrix of power injection to line impedance, on which an optimization problem for maximizing load margin is formulated. This framework is validated on the IEEE 14-bus system and the IEEE 118-bus system, in which net load redistribution attacks are launched by sophisticated attackers. Steady-state simulations and dynamic simulations on PSS/E show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. The impact of the proposed method on attack detection effectiveness is also revealed.

Zhang, Hang↗

Capturing Dynamics in the Power Grid: Formulation of Dynamic State Estimation through Data Assimilation

With the increasing complexity resulting from uncertainties and stochastic variations introduced by intermittent renewable energy sources, responsive loads, mobile consumption of plug-in vehicles, and new market designs, more and more dynamic behaviors are observed in everyday power system operation. To operate a power system efficiently and reliably, it is critical to adopt a dynamic paradigm so that effective control actions can be taken in time. The dynamic paradigm needs to include three fundamental components: dynamic state estimation; look-ahead dynamic simulation; and dynamic contingency analysis (Figure 1). These three components answer three basic questions: where the system is; where the system is going; and how secure the system is against accidents. The dynamic state estimation provides a solid cornerstone to support the other 2 components and is the focus of this study.

97 MATHEMATICS AND COMPUTING↗

Development of Large Scale Extrusion Deposition for Structural Applications

Large Scale Extrusion Deposition (LSED) is an evolving additive manufacturing (AM) technology that research, such as that taking place at Oak Ridge National Laboratory (ORNL) and companies like Local Motors, are continuing to utilize and develop new applications. A major LSED application of interest has been molds and tooling as it allows for much shorter production time and lower cost. However, interest has been expanding into using LSED for more structural applications due to more frequent use of high performing polymer composites as feedstock. The use of LSED for structural applications is of particular interest to Local Motors as it is currently being used to create commercially viable, energy efficient electric vehicles. LSED offers a unique opportunity when compared to traditional manufacturing methods as it can significantly reduce the number of components necessary, while decreasing embodied energy and carbon emissions. Even with these benefits however, it is important that LSED is properly understood from a structural aspect as this field has not been as heavily researched as tooling. To ensure a high level of safety and repeatability is an essential responsibility of a manufacturer whose products are structural in nature. As such it is important to understand the materials and LSED process to make structural objects that the manufacturer can be confident in. The main goals of this project were to: develop and investigate materials that are of interest for structural LSED applications, further develop and understand the current machines used in LSED and develop simulations tools of LSED and the mechanical properties of the created structure. Material development focused on composite materials that have high mechanical properties and are stable in a variety of environments. The materials were tested to determine their as printed mechanical and thermal properties as these are necessary for simulations. Once the materials were investigated thoroughly, it allowed for simulations to be performed to compare to experimental data with simulations. Materials were also vetted to determine candidates for multi-material printing. The machine development focused around the areas of process monitoring, non-destructive evaluation, and quality control. Finally, the goal of the simulations was to develop a realistic model of printed structures, including in-process simulation and dynamic simulation. The routes to get to some of these goals and the depth in which they were investigated changed throughout the project due to personnel changes and the COVID-19 pandemic. This project resulted in many valuable results such as the development of an nondestructive evaluation (NDE) technique for interlayer defects, proof of simulation for warpage in simple parts, the development and utilization of a profilometer to monitor a print for defects or inconsistencies, thorough investigation of a material used commercially for structural LSED applications and valuable experimental data on the applicability and advantages of multi-material crush structures versus their neat counterparts by creation and testing of samples.

36 MATERIALS SCIENCE↗

Extended Lagrangian Born-Oppenheimer molecular dynamics in the limit of vanishing self-consistent field optimization

We present an efficient general approach to first principles molecular dynamics simulations based on extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] in the limit of vanishing self-consistent field optimization. The reduction of the optimization requirement reduces the computational cost to a minimum, but without causing any significant loss of accuracy or long-term energy drift. The optimization-free first principles molecular dynamics requires only one single diagonalization per time step, but is still able to provide trajectories at the same level of accuracy as “exact,” fully converged, Born-Oppenheimer molecular dynamics simulations. The optimization-free limit of extended Lagrangian Born-Oppenheimer molecular dynamics therefore represents an ideal starting point for robust and efficient first principles quantum mechanical molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phonon thermal transport through tilt grain boundaries in strontium titanate

In this work, we perform nonequilibrium molecular dynamics simulations to study phonon scattering at two tilt grain boundaries (GBs) in SrTiO{sub 3}. Mode-wise energy transmission coefficients are obtained based on phonon wave-packet dynamics simulations. The Kapitza conductance is then quantified using a lattice dynamics approach. The obtained results of the Kapitza conductance of both GBs compare well with those obtained by the direct method, except for the temperature dependence. Contrary to common belief, the results of this work show that the optical modes in SrTiO{sub 3} contribute significantly to phonon thermal transport, accounting for over 50% of the Kapitza conductance. To understand the effect of the GB structural disorder on phonon transport, we compare the local phonon density of states of the atoms in the GB region with that in the single crystalline grain region. Our results show that the excess vibrational modes introduced by the structural disorder do not have a significant effect on phonon scattering at the GBs, but the absence of certain modes in the GB region appears to be responsible for phonon reflections at GBs. This work has also demonstrated phonon mode conversion and simultaneous generation of new modes. Some of the new modes have the same frequency as the initial wave packet, while some have the same wave vector but lower frequencies.

36 MATERIALS SCIENCE↗

Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. Furthermore, these techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗

Quantifying Power Distribution System Resiliency Using Code-Based Metric

It is essential to improve the resiliency of power distribution systems (PDS) with the increase in extreme weather events, number of malicious threats and consumers’ need for higher reliability. Here, this paper provides a formal approach to evaluate the operational resiliency of PDS, and quantify the resiliency of a system using a code-based metric. A combination of steady state and dynamic simulation tools is used to determine the resiliency metric. Dynamic simulation tools help with analyzing impact of short-term events, which might affect operational resiliency in long term. A dynamic optimization algorithm for changing operating criteria to increase the sustainability of the most critical loads has been proposed. The proposed theoretical approach is validated using a simple power distribution system model and simulation results demonstrate the ability to quantify the resiliency using the proposed code-based metric. The time-dependent quantification of resiliency has been demonstrated on a test system of two connected CERTS microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Open-source framework for power system transmission and distribution dynamics co-simulation

The promise of the smart grid entails more interactions between the transmission and distribution networks, and there is an immediate need for tools to provide the comprehensive modelling and simulation required to integrate operations at both transmission and distribution levels. Existing electromagnetic transient simulators can perform simulations with integration of transmission and distribution systems, but the computational burden is high for large-scale system analysis. For transient stability analysis, currently there are only separate tools for simulating transient dynamics of the transmission and distribution systems. In this paper, we introduce an open source co-simulation framework “Framework for Network Co-Simulation” (FNCS), together with the decoupled simulation approach that links existing transmission and distribution dynamic simulators through FNCS. FNCS is a middleware interface and framework that manages the interaction and synchronization of the transmission and distribution simulators. Preliminary testing results show the validity and capability of the proposed open-source co-simulation framework and the decoupled co-simulation methodology.

Huang, Renke↗

Extensions to Dynamic System Simulation of Fissile Solution Systems

Previous reports have documented the results of applying dynamic system simulation (DSS) techniques to model a variety of fissile solution systems. The SUPO (Super Power) aqueous homogeneous reactor (AHR) was chosen as the benchmark for comparison of model results to experimental data for steadystate operation.1 Subsequently, DSS was applied to additional AHR to verify results obtained for SUPO and extend modeling to prompt critical excursions, ramp reactivity insertions of various magnitudes and rate, and boiling operations in SILENE and KEWB (Kinetic Experiment Water Boiler).2 Additional models for pressurized cores (HRE: Homogeneous Reactor Experiment), annular core geometries, and accelerator-driven subcritical systems (ADAHR) were developed and results reported.3 The focus of each of these models is core dynamics; neutron kinetics, thermal hydraulics, radiolytic gas generation and transport are coupled to examine the time-based evolution of these systems from start-up through transition to steady-state. A common characteristic of these models is the assumption that (a) core cooling system inlet temperature and flow and (b) plenum gas inlet pressure and flow are held constant; no external (to core) component operations that may result in dynamic change to these parameters are considered. This report discusses extension of models to include explicit reference to cooling structures and radiolytic gas handling. The accelerator-driven subcritical generic system model described in References 3 and 4 is used as a basis for this extension.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The effect of classical and quantum dynamics on vibrational frequency shifts of H{sub 2} in clathrate hydrates

Vibrational frequency shifts of H{sub 2} in clathrate hydrates are important to understand the properties and elucidate details of the clathrate structure. Experimental spectra of H{sub 2} in clathrate hydrates have been measured for different clathrate compositions, temperatures, and pressures. In order to establish reliable relationships between the clathrate structure, dynamics, and observed frequencies, calculations of vibrational frequency shifts in different clathrate environments are required. In this study, a combination of classical molecular dynamics simulations, electronic structure calculations, and quantum dynamical simulation is used to calculate relative vibrational frequencies of H{sub 2} in clathrate hydrates. This approach allows us to assess dynamical effects and simulate the change of vibrational frequencies with temperature and pressure. The frequency distributions of the H{sub 2} vibrations in the different clathrate cage types agree favorably with experiment. Also, the simulations demonstrate that H{sub 2} in the 5{sup 12} cage is more sensitive to the details of the environment and to quantum dynamical effects, in particular when the cage is doubly occupied. We show that for the 5{sup 12} cage quantum effects lead to frequency increases and double occupation is unlikely. This is different for the 5{sup 12}6{sup 4} cages for which higher occupation numbers than one H{sub 2} per cage are likely.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure and Hydrolysis of the U(IV), U(V), and U(VI) Aqua Ions from Ab Initio Molecular Simulations

Ab initio molecular dynamics simulations at 300 K based on density functional theory have been used to study the hydration shell geometries, solvent dipole, and first hydrolysis of the Uranium(IV) (U{sup 4+}) and Uranyl(V) (UO{sub 2}{sup +}) ions in aqueous solution. The solvent dipole and first of hydrolysis of aqueous Uranium(VI) (UO{sub 2}{sup 2+}) has also been probed. The first shell of U{sup 4+} is coordinated by 8-9 water ligands with an average U-O distance of 2.42 {angstrom}. The average first shell coordination number and distance are in agreement with experimental estimates of 8-11 and 2.40-2.44 {angstrom} respectively. The simulated EXAFS spectra of U{sup 4+} matched well with recent experimental data. The first shell of UO{sub 2}{sup +} is coordinated by 5 water ligands in the equatorial plane, with the average U=O{sub ax} and U-O distances being 1.85 {angstrom} and 2.54 {angstrom} respectively. Overall, the hydration shell structure of UO{sub 2}{sup +} matches closely with that of UO{sub 2}{sup 2+} except for small expansions in the average U=O{sub ax} and U-O distances. Each ion strongly polarizes their respective first shell water ligands. The computed acidity constant (pK{sub a}) of U{sup 4+} and UO{sub 2}{sup 2+} are 0.93 and 4.95, in good agreement with the experimental values of 0.54 and 5.24 respectively. The predicted pK{sub a} of UO{sub 2}{sup +} is 8.5.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Simulation-Based Dynamic Approach for External Flooding Analysis in Nuclear Power Plants

All nuclear power plants must consider and evaluate external flooding risks such as local intense precipitation, dam failure, and coastal flooding due to storm surge or tsunami. While these events could challenge off-site power and other plant structure integrity, threaten plant safety systems and components, and limit plant access, they are more than often qualitatively regarded as risk insignificant and screened out from detailed evaluation and quantification. The recent lessons learned from the Fukushima seismic/tsunami initiated nuclear accident (2011), the Fort Calhoun (2011), Vermont Yankee (2013), Arkansas Nuclear One (2013), and St. Luice (2014) flooding events showed otherwise. However, developing an external flood model with traditional event tree/fault tree approach as in a static probabilistic risk assessment (PRA) model could be difficult to accurately represent plant system and component behavior and reliability of manual actions during an ever-progressing flood event. The plant response to external flood may be highly spatial- and time- dependent and subject to the hydrological and hydraulic characteristics of the flood event. Such unique challenges prompt the investigation of using the simulation-based dynamic analysis approaches for external flood risk assessment. Simulation methods can better illustrate the performance of structures, systems, and components during an external flooding event. A general framework to perform a simulation-based dynamic flooding analysis is presented in this paper with the sub-tasks of flood hazard analysis, flood fragility analysis, plant response modeling, safety margin analysis or PRA quantification. A new type of State PRA modeling technique is introduced to incorporate time-related interactions such as those from 3D simulations into a traditional PRA model.

99 GENERAL AND MISCELLANEOUS↗