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At least 1,459 records · Page 81

Structural properties of Y 2 O 3 –Al 2 O 3 liquids and glasses: An overview

Liquids in the system Y 2 O 3 –Al 2 O 3 have been the subject of considerable study because of the reported occurrence of a first-order density and entropy-driven liquid-liquid phase transition (LLPT) in the supercooled liquid state. The observations have become controversial because of the presence of crystalline material that can be formed simultaneously and that can mask the nucleation and growth of the lower density liquid. The previous work is summarized here along with arguments for and against the different viewpoints. Also two studies have been undertaken to investigate the LLPT in this refractory system with emphasis on determining the structure of unequivocally amorphous materials. These include the in situ high energy X-ray diffraction (HEXRD) of supercooled Y 2 O 3 –Al 2 O 3 liquids and the low frequency vibrational dynamics of recovered glasses. Manybody molecular dynamics simulations are also used to interpret the results of both studies. The HEXRD measurements, combined with aerodynamic levitation and rapid data acquisition techniques, show that for the 20 mol% Y 2 O 3 (i.e. AlY20) liquid there is a shift in the position of the first peak in the diffraction pattern over a narrow temperature range (2100-1800 K) prior to crystallization. Microbeam Raman spectroscopy measurements made on AlY20 glasses clearly show contrasting spectra in the low frequency part of the spectrum for low(LDA) and high-density (HDA) glassy regions. The molecular dynamics simulations identify contrasting coordination environments around oxygen anions for the high- (HDL) and low-density (LDL) liquids. (C) 2014 Elsevier B.V. All rights reserved.

36 MATERIALS SCIENCE↗

Coupling LAMMPS and the vl3 Framework for Co-Visualization of Atomistic Simulations

In this work we perform in-situ visualization of molecular dynamics simulations, which can help scientists to visualize simulation output on-the-fly, without incurring storage overheads. We present a case study to couple LAMMPS, the large-scale molecular dynamics simulation code with vl3, our parallel framework for large-scale visualization and analysis. Our motivation is to identify effective approaches for covisualization and exploration of large-scale atomistic simulations at interactive frame rates.We propose a system of coupled libraries and describe its architecture, with an implementation that runs on GPU-based clusters. We present the results of strong and weak scalability experiments, as well as future research avenues based on our results.

co-visualization↗

Data-assisted combustion simulations with dynamic submodel assignment using random forests

This investigation outlines a data-assisted approach that employs random forest classifiers for local and dynamic submodel assignment in turbulent-combustion simulations. This method is demonstrated in simulations of a single-element GOX/GCH4 rocket combustor; a priori as well as a posteriori assessments are conducted to (i) evaluate the accuracy and adjustability of the classifier for targeting different quantities of interest (QoIs), and (ii) assess improvements, resulting from the data-assisted combustion model assignment, in predicting target QoIs during simulation runtime. Results from the a priori study show that random forests, trained with local flow properties as input variables and combustion model errors as training labels, assign three different combustion models – finite-rate chemistry (FRC), flamelet progress variable (FPV) model, and inert mixing (IM) – with reasonable classification performance even when targeting multiple QoIs. Applications in a posteriori studies demonstrate improved predictions from data-assisted simulations, in temperature and CO mass fraction, when compared with monolithic FPV calculations. An additional a posteriori data-assisted simulation of a modified configuration demonstrates that the present approach can be successfully applied to different configurations, as long as thermophysical behavior can be represented by the training data. Furthermore, these results demonstrate that this data-driven framework holds promise for dynamic combustion submodel assignments in reacting flow simulations.

42 ENGINEERING↗

INCORPORATING DYNAMIC 3D SIMULATION INTO PRA

Through continued advancement in computational resources, development that was previously done by trial and error production is now performed through computer simulation. These virtual physical representations have the potential to provide accurate and valid modeling results and are being used in many different technical fields. Risk assessment now has the opportunity to use 3D simulation to improve analysis results and insights, especially for external event analysis. By using simulations, the modeler only has to determine the likelihood of an event without having to also predict the results of that event. The 3D simulation automatically determines not only the outcome of the event, but when those failures occur. How can we effectively incorporate 3D simulation into traditional PRA? Most PRA plant modeling is made up of components with different failure modes, probabilities, and rates. Typically, these components are grouped into various systems and then are modeled together (in different combinations) as a “system” with logic structures to form fault trees. Applicable fault trees are combined through scenarios, typically represented by event tree models. Though this method gives us failure results for a given model, it has limitations when it comes to time-based dependencies or dependencies that are coupled to physical processes which may themselves be space- or time-dependent. Since, failures from a 3D simulation are naturally time related, they should be used in that manner. In our simulation approach, traditional static models are converted into an equivalent state diagram representation with start states, probabilistic driven movements between states and terminal states. As the state model is run repeatedly, it converges to the same results as the PRA model in cases where time-related factors are not important. In cases where timing considerations are important (e.g., when events are dependent upon each other), then the simulation approach will typically provide superior results and insights. We also couple the state model with the dynamic 3D simulation analysis representing events (such as flooding) to determine which (if any) components fail. Not only does the simulation take into account any failed items from the state model, but any failures caused by the simulation are incorporated back into the state model and factored into the overall results. Using this method we incorporate accurate 3D simulation results, eliminate static-based PRA issues, and have time ordered failure information.

3D Simulation↗

Discussion on molecular dynamics (MD) simulations of the asphalt materials

The application of asphalt materials in pavement engineering has been increasingly widespread and sophisticated over the past several decades. Variations in the properties of asphalt binder during mixing, transportation, and paving can affect the performance of asphalt pavement. However, the asphalt material is a non-homogeneous and complex organic substance, consisting of various molecules with widely various molecular weights, elemental compositions, and structures. This complexity leads to difficulties for researchers to clearly and immediately understand the properties of asphalt materials and their variations. The multi-scale research approach combines macroscopic experimental data and microscopic simulation results from a practical engineering perspective. It helps to improve the understanding of asphalt materials. The molecular dynamics (MD) simulation proposes a corresponding molecular model of asphalt material based on experimental data, and the simulation algorithm is able to derive properties similar to those of real asphalt. Here, this paper provides a comprehensive review of the current studies on MD simulation of asphalt materials, including modeling, properties, and multi-scale analysis. As a key part of the computational simulation, this paper discusses the typical asphalt binder and asphalt-aggregate interface models constructed by different groups, and also presents their differences from real samples and their feasibility based on fundamental properties. After the introduction of molecular models, the extensive work made by researchers based on molecular models is categorically reviewed and discussed. The strengths and weaknesses of MD simulation methods in the study of asphalt materials are also summarized in order to provide the reader with a more comprehensive understanding of the relevant contents and to guide subsequent research.

36 MATERIALS SCIENCE↗

Off-fault deformations and shallow slip deficit from dynamic rupture simulations with fault zone plasticity

Kinematic source inversions of major (M≥7) strike-slip earthquakes show that the slip at depth exceeds surface displacements measured in the field, and it has been suggested that this shallow slip deficit (SSD) is caused by distributed plastic deformation near the surface. We perform dynamic rupture simulations of M 7.2–7.4 earthquakes in elastoplastic media and analyze the sensitivity of SSD and off-fault deformation (OFD) to rock quality parameters. While linear simulations clearly underpredict observed SSD and OFDs, nonlinear simulations for a moderately fractured fault damage zone predict a SSD of 44–53% and OFDs of 39–48%, consistent with the 30–60% SSD and 46 ± 10% (1σ) OFD reported for the 1992 M 7.3 Landers earthquake. Finally, both SSD and OFDs are sensitive to the quality of the fractured rock mass inside the fault damage zone, and surface rupture is almost entirely suppressed in poor quality material.

58 GEOSCIENCES↗

Data-driven material models for atomistic simulation

The central approximation made in classical molecular dynamics simulation of materials is the interatomic potential used to calculate the forces on the atoms. Great effort and ingenuity is required to construct viable functional forms and find accurate parametrizations for potentials using traditional approaches. Machine learning has emerged as an effective alternative approach to develop accurate and robust interatomic potentials. Beginning with a very general model form, the potential is learned directly from a database of electronic structure calculations and therefore can be viewed as a multiscale link between quantum and classical atomistic simulations. Risk of inaccurate extrapolation exists outside the narrow range of time and length scales where the two methods can be directly compared. Here, we use the spectral neighbor analysis potential (SNAP) and show how a fit can be produced with minimal interpolation errors which is also robust in extrapolating beyond training. To demonstrate the approach, we have developed a tungsten-beryllium potential suitable for the full range of binary compositions. Subsequently, large-scale molecular dynamics simulations were performed of high energy Be atom implantation onto the (001) surface of solid tungsten. The machine learned W-Be potential generates a population of implantation structures consistent with quantum calculations of defect formation energies. A very shallow ( < 2 nm ) average Be implantation depth is predicted which may explain ITER diverter degradation in the presence of beryllium.

36 MATERIALS SCIENCE↗

A Comparative Study of Interface Techniques for Transmission and Distribution Dynamic Co-Simulation

Transmission and distribution (T&D) dynamic co-simulation is a practical and effective approach to leverage existing simulation tools for transmission and distribution systems to simulate dynamic stability and performance of T&D systems in a systematic manner. Given that these tools are developed as stand-alone programs and there are inherent differences between them, interface techniques become critical to “bridge” them. Two important unsolved questions are: 1) which interface technique is better and should be used, and 2) how the modeling and simulation capabilities in these tools that are available and can be exploited for co-simulation should be considered when selecting an interface technique. This paper presents a comprehensive study for different interface techniques that can be employed for T&D dynamic co-simulation. The study provided insights to the pros and cons of each interface technique, and helped researchers make informed decisions on choosing a proper interface technique.

Huang, Qiuhua↗

Characterization of swift heavy ion irradiation damage in ceria

We have examined microstructural evolution in irradiated ceria (CeO2) using swift heavy ion irradiation, electron microscopy, and atomistic simulation. CeO2, a UO2 fuel surrogate, was irradiated with gold ions at an energy of 1 GeV to fluences up to 1x1014 ions/cm2. Transmission electron microscopy accompanied by electron energy loss spectroscopy showed that the ion tracks were of similar size at all fluences, and that there was no chemical change in the ion track core. Classical molecular dynamics simulations of thermal spikes in CeO2 with energy deposition of 12 and 36 keV/nm show damage consisting of isolated point defects at the lower energy and defect clusters at 36 keV/nm, with no amorphization at either energy. Inferences are drawn from modeling about density changes in the ion track and the formation of interstitial loops that shed light on features observed by electron microscopy of swift heavy ion irradiated ceria.

Yablinsky, Clarissa↗

pnnl/mol_dgnn

Molecular dynamics simulations often rely on parameterized atomistic potentials, which can be inaccurate compared to ab initio simulation methods. However, dynamic ab initio simulations come with high computational cost. Deep learning techniques offer a method to obtain both high accuracy and low cost predictions of dynamics. Our method gives a prediction of the structural dynamics of a molecule accounting for the prior dynamics, giving high-accuracy predictions at low computational cost

Ashby, Michael↗

Advanced EMT and Phasor-Domain Hybrid Simulation With Simulation Mode Switching Capability for Transmission and Distribution Systems

Conventional electromagnetic transient (EMT) and phasor do-main hybrid simulation approaches presently exist for transmission system level studies and their simulation efficiency is generally constrained by the EMT simulation. With an increasing number of distributed energy resources and non-conventional loads being installed in the distribution systems, it is imperative to ex-tend the hybrid simulation application to include distribution systems and integrated transmission and distribution systems. Meanwhile, it is equally important to improve the simulation efficiency as the modeling scope and complexity of the detailed system in the EMT simulation increases. To meet both requirements, this paper introduces an advanced electromagnetic transient (EMT) and phasor domain hybrid simulation approach. This approach has two outstanding features: 1) a comprehensive phasor domain modeling framework which supports positive-sequence, three-sequence, three-phase and mixed three-sequence/three-phase representations; 2) a robust and flexible simulation mode switching scheme which enables simulation switching from hybrid simulation mode back to pure phasor domain dynamic simulation mode to achieve significantly improved simulation efficiency. The proposed method has been tested on integrated transmission and distribution systems, and the results show that with the developed simulation switching feature, the total computational time is significantly reduced compared to running the hybrid simulation for the whole simulation period, while good accuracy is maintained.

Huang, Qiuhua (ORCID:0000000184577429)↗

Thermally induced mimicry of quantum cluster excitations and implications for the magnetic transition in FePSe 3

In two dimensional magnets, the interplay of thermal fluctuations and spin anisotropy control the existence of long-range magnetic order. In the van der Waals antiferromagnets FePX 3 , orbital degeneracy in the 𝑡 2⁢𝑔 levels of the Fe 2+ ions in octahedral coordination yields strong uniaxial anisotropy, which stabilizes magnetic order up to 𝑇 ≈ 100 K. Recent inelastic neutron scattering measurements around the magnetic ordering transition have shown the existence of a broad spectrum of magnetic fluctuations with nontrivial momentum dependence, which has been interpreted as evidence for localized entangled cluster excitations. In this paper, we offer an alternative interpretation using classical nonlinear spin dynamics simulations. We present stochastic Landau Lifshitz dynamics simulations that reproduce the neutron scattering measurements of Chen et al. [npj Quantum Mater. 9, 40 (2024)] on FePSe 3 . These calculations faithfully explain the dynamical structure factor's momentum and energy dependence and point to a classical origin for the excitations observed in neutron spectroscopy and that the order-disorder transition can be understood in terms of thermal fluctuations overcoming the anisotropy energy.

Landau-Lifschitz-Gilbert equation↗

Scientific Data Compression for Large Scale Computational Fluid Dynamics (CFD) Simulations

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and General Electric (GE) investigated methods for reducing the size of large computational fluid dynamics (CFD) simulation datasets using scientific data compression techniques. The work focused on adapting the MultiGrid Adaptive Reduction of Data (MGARD) compression framework and integrating it with high-performance I/O and visualization tools used in CFD workflows. MGARD uses hierarchical multilevel decomposition to enable error-controlled compression of floating-point scientific data while preserving quantities of interest. During the project, MGARD compression was integrated with the ADIOS I/O framework and visualization tools such as ParaView to enable efficient storage, transfer, and analysis of simulation data. The collaboration also explored approaches for improving compression performance for CFD data defined on unstructured meshes. Results demonstrate that scientific data compression can significantly reduce storage requirements and improve data management for large-scale CFD simulations.

97 MATHEMATICS AND COMPUTING↗

Coarse-grained computer simulation of dynamics in thylakoid membranes: methods and opportunities

Coarse-grained simulation is a powerful and well-established suite of computational methods for studying structure and dynamics in nanoscale biophysical systems. As our understanding of the plant photosynthetic apparatus has become increasingly nuanced, opportunities have arisen for coarse-grained simulation to complement experiment by testing hypotheses and making predictions. Here, we give an overview of best practices in coarse-grained simulation, with a focus on techniques and results that are applicable to the plant thylakoid membrane–protein system. We also discuss current research topics for which coarse-grained simulation has the potential to play a key role in advancing the field.

Brownian dynamics↗

Nuclear Materials Process Modeling at the Y-12 National Security Complex

The Y-12 National Security Complex (Y-12) has implemented process modeling for various accountable nuclear materials operations that are performed throughout the plant. Using a discrete, event-based dynamic simulation program, key nuclear material streams are modeled, allowing Y-12 to effectively manage numerous points of interest within the plant’s production operations. Integration of the various material processes into a single, interdependent supply and demand model is one of the ongoing focuses within Y-12’s process modeling effort. The primary purpose of using dynamic simulation modeling is to allow for analysis of the nuclear materials inventories and forecasted supplies based on future demands. Analysis of these inventories includes capacity evaluation, bottleneck mitigation, and assessments of individual pieces of equipment to inform future facility investment decisions and associated project schedules. Modeling of the nuclear materials processes throughout the complex also allows for incorporation of changes relevant to production capabilities such as the upcoming transition of specific operations to the new Uranium Processing Facility. Prior to implementation of process modeling, Y-12 forecasted supply and demand of accountable nuclear materials streams using Microsoft Excel. With deterministic models such as Microsoft Excel, the annual forecasts, generated within data input condition parameters, can only provide a fixed point of data. Fixed data cannot simulate integrated material streams and account for the possibility of occurrences and other changes that dynamic simulations take into consideration. Y-12’s dynamic process modeling allows integrated simulations of multiple accountable nuclear materials processes, including supply and demand forecasting and analysis, and is a coordinated effort involving many steps of verification and validation (V&V), site briefings, testing, reporting, data mining, planning, and documentation that spans various programs throughout the Y-12 complex.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Simulation of dynamic crystal plasticity with a Lagrangian discontinuous Galerkin hydrodynamic method

Here we present a new Lagrangian modal discontinuous Galerkin (DG) hydrodynamic method that supports a dynamic dislocation based crystal plasticity model for simulating the mechanical behavior of crystallographic materials, both single crystal and polycrystalline, under dynamic conditions. A modal DG approach is used to evolve fields relevant to conservation laws. These fields are approximated by Taylor series polynomials of varying degree. These polynomials describe macro-scale hydrodynamic behavior while their evolution is determined by evaluating the dynamic crystal plasticity model at material points within the element. The dynamic crystal plasticity model is sensitive to the time increment size, with too large of time increments leading to instability in the model. To mitigate this, the temporal evolution of the dynamic crystal plasticity model is achieved with the combination of a sub-incrementing scheme with Heun’s third-order time integration scheme, which is also used to temporally evolve the governing equations. The implementation of the dynamic crystal plasticity model within the DG framework is tested using a 2D approximation of the Taylor impact test with a single crystal material, using quadratic elements that have faces that can bend. In addition to the standard continuous material modeling, we propose a new simulation method that would represent the heterogeneous behavior of polycrystalline microstructures within an element by varying the position and material properties of the material points within the element. This method is demonstrated using random orientation distributions on materials points that are arranged in both structured and random configurations.

42 ENGINEERING↗

Temperature-dependent mechanical properties of single-layer molybdenum disulphide: Molecular dynamics nanoindentation simulations

The temperature-dependent mechanical properties of single-layer molybdenum disulphide (MoS{sub 2}) are obtained using molecular dynamics (MD) nanoindentation simulations. The Young's moduli, maximum load stress, and maximum loading strain decrease with increasing temperature from 4.2 K to 500 K. The obtained Young's moduli are in good agreement with those using our MD uniaxial tension simulations and the available experimental results. The tendency of maximum loading strain with different temperature is opposite with that of metal materials due to the short range Stillinger-Weber potentials in MoS{sub 2}. Furthermore, the indenter tip radius and fitting strain effect on the mechanical properties are also discussed.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Ultrafast terahertz-field-driven ionic response in ferroelectric BaTiO 3

The dynamical processes associated with electric field manipulation of the polarization in a ferroelectric remain largely unknown but fundamentally determine the speed and functionality of ferroelectric materials and devices. Here in this paper we apply subpicosecond duration, single-cycle terahertz pulses as an ultrafast electric field bias to prototypical BaTiO 3 ferroelectric thin films with the atomic-scale response probed by femtosecond x-ray-scattering techniques. We show that electric fields applied perpendicular to the ferroelectric polarization drive large-amplitude displacements of the titanium atoms along the ferroelectric polarization axis, comparable to that of the built-in displacements associated with the intrinsic polarization and incoherent across unit cells. This effect is associated with a dynamic rotation of the ferroelectric polarization switching on and then off on picosecond time scales. These transient polarization modulations are followed by long-lived vibrational heating effects driven by resonant excitation of the ferroelectric soft mode, as reflected in changes in the c-axis tetragonality. The ultrafast structural characterization described here enables a direct comparison with first-principles-based molecular-dynamics simulations, with good agreement obtained.

36 MATERIALS SCIENCE↗