Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Dynamics Simulations”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Cluster dynamics simulation of xenon diffusion during irradiation in UO 2

Diffusion of fission gas in UO 2 nuclear fuel impacts several important performance metrics, such as fission gas release, swelling, and thermal conductivity. Current empirical models of fission gas release have significant uncertainty, some of which derives from the bulk diffusion rate and its dependence on, for example, fuel chemistry and irradiation. In this work, we have applied the previously-developed Free Energy Cluster Dynamics (FECD) methodology in the code Centipede to calculate xenon cluster concentrations in UO 2 under intrinsic (high temperature) and irradiation-enhanced (intermediate temperature) conditions in order to develop a model of the xenon diffusion coefficient based on the atomic scale mechanisms responsible for transport. While the diffusion mechanism for xenon in UO 2 is adequately described by the Xe + U 2 O vacancy cluster for intrinsic conditions, a similar process is not capable of capturing measured in-pile fission gas diffusivity at intermediate temperatures. Therefore, a different diffusion mechanism must dominate under this regime. Using calculated atomistic data, we have shown that irradiation-enhanced diffusion at intermediate temperatures occurs via the larger Xe + U 4 O y vacancy clusters, which have lower migration barriers and increase in concentration by several orders of magnitude compared to intrinsic conditions. This mechanism is enabled by the increased uranium vacancy concentration under irradiation due to Frenkel pair production. In addition, the fast migration of uranium interstitials with two attached oxygen interstitials lowers the total uranium interstitial concentration through reactions with sinks. This allows the extended defects, such as Xe + U 4 O y vacancy clusters, to maintain high concentrations by limiting annihilation with attached vacancies. Furthermore, predictions using the Xe + U 4 O y diffusion mechanism are in good agreement with experiment, albeit with some differences in the Arrhenius slope, which we believe may be related to either experimental or model parameter uncertainty. Lastly, an analytical expression suitable for application in fuel performance simulations was derived to capture the predictions of the Centipede simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Origin of short- and medium-range order in supercooled liquid Ge 3 Sb 2 Te 6 from ab initio molecular dynamics simulations

Phase-change materials such as Ge–Sb–Te compounds have attracted much attention due to their potential value in electrical data storage. In contrast to the amorphous and crystalline phases, supercooled liquids are far from being deeply understood despite their inevitable role in both amorphization and crystallization processes. To this end, we have studied the dynamics properties and structural characteristics of liquid and supercooled liquid Ge 3 Sb 2 Te 6 during the fast cooling process. As the temperature decreases, chemical bonds become more homogeneous, but coordination numbers of Ge, Sb and Te atoms change very little. Meanwhile, the structural order of short-range configuration is obviously enhanced. Further studies suggest that Ge-centered, Sb-centered and Te-centered configurations change to the more ordered defective octahedrons mainly by adjusting the bond-angle relationship and bond length, rather than just by changing the coordination environment. It is the more ordered octahedrons that promote the formation of medium-range order. Our findings provide a deep insight into the origin of local structural order in supercooled liquid Ge 3 Sb 2 Te 6 , which is of great importance for the comprehensive understanding of amorphization and crystallization processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Elucidating Lithium Transport Mechanisms in Disordered LiF from Machine-Learning Molecular Dynamics Simulations

Lithium fluoride (LiF) is a ubiquitous component of solid- and cathode–electrolyte interphases, yet its functional role remains unclear under the structural and chemical heterogeneity typical of cycling batteries. Here, we systematically quantify how structural disorder, off-stoichiometry, and strain govern Li-ion transport in LiF. Using a machine-learning potential to enable extensive molecular-dynamics sampling, we compare crystalline and amorphous LiF, Li 0.95 F, and LiF 0.95 , and evaluate the impact of small homogeneous deformations. Defect-free crystalline LiF is effectively ion-blocking at 300−500 K, whereas amorphization generates free-volume–assisted percolation pathways that facilitates Li-ion diffusion. At elevated temperatures, thermodynamically driven crystallization disrupts these pathways, leading to non-Arrhenius behavior. In crystalline phases, Li deficiency activates vacancy-mediated diffusion, while in amorphous LiF, transport is governed primarily by network connectivity. Strain is found to have only a marginal effect on Li mobility in both crystalline and amorphous structures.

Batteries↗
DOE OSTI2025

Quasiclassical sampling and Wigner sampling of initial vibrational coordinates and momenta for polyatomic molecules in Monte Carlo molecular dynamics simulations

In a quasiclassical trajectory simulation, the vibrational modes are initialised with quantised vibrational energies, but vibrational phases are sampled by Monte Carlo. This requires an algorithm to assign coordinates and momenta to the various atoms. In this work, we present two methods for implementing this for nonrotating polyatomic molecules, namely, fixed-energy vibrational-state-selected initial conditions and thermal initial conditions. We also present a method for initiating classical trajectories with a ground-state Wigner distribution. These vibrational treatments are sufficient to initialise trajectories for unimolecular processes, and we also show how they can be applied to simulate bimolecular collision processes. The treatments of unimolecular and bimolecular collision processes are available in two Python codes called wigner_state_selected.py and bimolecular_collision.py, respectively, which will generate initial condition files that are recognisable by the SHARC and SHARC-MN computer programs for dynamics calculations. Both codes are available as standalone programs, as well as being included in SHARC-MN, and they will be included in future versions of SHARC. Here, the methods implemented in these codes are mostly also available in the ANT computer program, and those that are not available in ANT will be incorporated in future versions of ANT.

Wigner distribution↗
DOE OSTI2024

Material Model Parameters Optimization in Liquid Mercury Target Dynamics Simulation With Machine Learning Surrogates

A pulsed spallation target is subjected to very short (∼0.7μs) but intense loads (23.3 kJ) from repeated proton pulses, which knock away neutrons from the mercury atoms’ nuclei for a wide range application in physics, engineering, medicine, petroleum exploration, biology, chemistry, etc. The effect of this pulsed loading on the stainless-steel target module which contains the flowing mercury target material is difficult to predict not only due to its short but intense explosive-like physical reaction, but also the nonlinear material behavior of the liquid mercury in the structure. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at high power level stage. However, prediction of the resultant loading on the target is more difficult when helium gas is intentionally injected into the mercury. A 2-phase material model that incorporates the Rayleigh-Plesset (R-P) model is expected to address this complex multi-physics dynamics problem by including the bubble dynamics in the liquid mercury. A parameter sensitivity study was firstly employed to understand their impact on the simulation strains. The investigated parameters included E, μ, γ, σ, n, VFgas, and gas cumulative volume curve control parameters a and b. Verification and validation results from sparse polynomial expansions (SPE) method and directional Gaussian smoothing (DGS) optimization show that the surrogate model had training error of ∼7% and validation error of ∼15%, indicating that machine learning methods and surrogate models can help optimize the uncertain parameters in the complex 2-phase material model. This approach is expected to fill the knowledge gap between unknown liquid-gas mixture material model and measured vessel strain responses.

Lin, Lianshan↗
DOE OSTI2024

Evaluation of δ-Phase ZrH1.4 to ZrH1.7 Thermal Neutron Scattering Laws Using Ab Initio Molecular Dynamics Simulations

Zirconium hydride is commonly used for next-generation reactor designs due to its excellent hydrogen retention capacity at temperatures below 1000 K. These types of reactors operate at thermal neutron energies and require accurate representation of thermal scattering laws (TSLs) to optimize moderator performance and evaluate the safety indicators for reactor design. In this work, we present an atomic-scale representation of sub-stoichiometric ZrH2−x(0.3≤x≤0.6), which relies on ab initio molecular dynamics (AIMD) in tandem with velocity auto-correlation (VAC) analysis to generate phonon density of states (DOS) for TSL development. The novel NJOY+NCrystal tool, developed by the European Spallation Source community, was utilized to generate the TSL formulations in the A Compact ENDF (ACE) format for its utility in neutron transport software. First, stoichiometric zirconium hydride cross sections were benchmarked with experiments. Then sub-stoichiometric zirconium hydride TSLs were developed. Significant deviations were observed between the new δ-phase ZrH2−x TSLs and the TSLs in the current ENDF release. It was also observed that varying the hydrogen vacancy defect concentration and sites did not cause as significant a change in the TSLs (e.g., ZrH1.4 vs. ZrH1.7) as was caused by the lattice transformation from ϵ- to δ-phase.

42 ENGINEERING↗
DOE OSTI2021

Computational Fluid Dynamic Simulation for Electrolyte Flow in Horizontal EP of Nb SRF Elliptical Cavities

An electrolyte flow velocity on an electropolishingsurface affects a material removal rate where higherremoval is observed with a higher velocity of theelectrolyte. In horizontal EP (HEP) of an ellipticalcavity, an electrolyte flow near the equator positionmight remain slow and responsible for a lowerremoval compared to that on the iris and beam pipepositions. In order to understand the flow dynamicon an elliptical cavity surface in the horizontal EPprocess, a computational fluid dynamic simulationwas conducted. This study was conducted on 1.3GHz cavity with different cathodes and acid flowrates. Final aim of the study is to improve the flowuniformity to attain uniform removal especially inmulticell cavities.

Chouhan, V.↗
DOE OSTI2020

A comparative study of the effectiveness of empirical potentials for molecular dynamics simulations of borosilicate glasses

Despite their practical importance, atomistic modeling of B 2 O 3 containing glasses have been challenging due to the lack of reliable empirical potentials. Fortunately, a few recent developments have shown promises to simulate these glasses where the boron coordination has complex and non-linear dependence on glass composition. This work aims to provide an evaluation of the effectiveness of three recently developed potentials by a systematic study of a series (~20) of sodium borosilicate glasses with constant K (ratio of [SiO 2 ]/[B 2 O 3 ]) =2 and varying R (ratio of [Na 2 O]/[B 2 O 3 ] ranging from 0.1 to 4) values and several sodium boroaluminosilicate glasses. A comparative assessment was established on the basis of the short- and medium-range structure features, such as boron N 4 values, total correlation functions, bond angle distribution, oxygen speciation, and mechanical properties using experimental or well-established models as criteria. Furthermore, this work provides insights on the choices of empirical potentials for MD simulations of borosilicate glasses and gives directions of future potential development and refining.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Horizons of modern molecular dynamics simulation in digitalized solid freeform fabrication with advanced materials

Our ability to shape and finish a component by combined methods of fabrication including (but not limited to) subtractive, additive and/or no theoretical mass-loss/addition during the fabrication is now popularly known as solid free form fabrication. Fabrication of a telescope mirror is a typical example where grinding and polishing processes are first applied to shape the mirror and thereafter an optical coating is usually applied to enhance its optical performance. The area of nanomanufacturing cannot grow without a deep knowledge of the fundamentals of materials and consequently, the use of computer simulations is becoming ubiquitous. This article is intended to introduce the most recent advances in the computation benefit specific to the area of solid free form fabrication as these systems are traversing through the journey of digitalisation and Industry-4.0. Specifically, this article demonstrates that the application of the latest materials modelling approaches, based on techniques such as molecular dynamics, are enabling breakthroughs in applied precision manufacturing techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multimode turbulent flow measurements using magnetic resonance imaging- and laser-based techniques and computational fluid dynamics simulations

We studied the flow field characteristics of a turbulent flow over a regularized cube array with a perpendicular injection flow through the floor between the second and third cubical elements, representing the complex flow interactions of a 3D jet and the wake flows behind cubical obstacles. Four different experimental measurements were performed: two magnetic resonance imaging-based measurements for three-dimensional three-component velocity (MRV) and concentration (MRC) and two laser-based techniques, particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF), for two-dimensional two-component velocity and concentration measurement, respectively. The mainstream Reynolds number is Re = 15 000⁠, based on the primary inlet velocity U m and channel height D H ⁠, whereas the injector Reynolds number is Re j = 3400⁠, based on the injector velocity U j and the injector's exit width D j ⁠. Numerical simulations were performed for the studied flow configuration of turbulent flow over a regularized cube array using Reynolds-averaged Navier–Stokes (RANS) and large-eddy simulation (LES) approaches. Results obtained from experimental measurements—including MRV, MRC, PIV, and PLIF—as well as RANS and LES simulations are discussed and compared along several horizontal and vertical planes of the studied configuration. In addition, 3D turbulent flow structures, such as leading-edge vortex, horseshoe vortex, and jet shear-layer vortex, and the isosurfaces of scalar concentration successfully revealed by MRV and MRC techniques were found to be in very good agreement with those 3D features extracted from RANS and LES simulations. In conclusion, the high-resolution experimental and numerical database obtained from this study could be useful for validation and verification of numerical codes.

Computational fluid dynamics↗
DOE OSTI2022

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials: case study of thorium dioxide

Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for the design of nuclear reactors. However, they are not easy to measure, because the target temperature range is too high to perform various standard experiments safely and accurately. Moreover, theoretical methods such as first-principles calculations also suffer from the computational limitations in calculating thermodynamical properties due to their high calculation-costs and complicated electronic structures stemming from f-orbital occupations of valence electrons in actinide elements. Here, we demonstrate, for the first time, machine-learning molecular-dynamics to theoretically explore high-temperature thermodynamical properties of a nuclear fuel material, thorium dioxide. The target compound satisfies first-principles calculation accuracy because f-electron occupation coincidentally diminishes and the scheme meets sampling sufficiency because it works at the computational cost of classical molecular-dynamics levels. We prepare a set of training data using first-principles molecular dynamics with small number of atoms, which cannot directly evaluate thermodynamical properties but captures essential atomistic dynamics at the high temperature range. Then, we construct a machine-learning molecular-dynamics potential and carry out large-scale molecular-dynamics calculations. Consequently, we successfully access two kinds of thermodynamic phase transitions, namely the melting and the anomalous λ transition induced by large diffusions of oxygen atoms. Furthermore, we quantitatively reproduce various experimental data in the best agreement manner by selecting a density functional scheme known as SCAN. Our results suggest that the present scale-up simulation-scheme using machine-learning techniques opens up a new pathway on theoretical studies of not only nuclear fuel compounds, but also a variety of similar materials that contain both heavy and light elements, like thorium dioxide.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Molecular dynamics simulations of reflection and sputtering behavior of boron under deuterium ion irradiation

Boronization is a commonly used method of wall conditioning in fusion reactors. The application of boron films to the plasma-facing materials results in enhanced plasma performance due to the reduction of intrinsic impurities. This is primarily driven by a reduction in oxygen content that is chemically trapped in the boron film. The reactive nature of these boron films also raises questions concerning interactions with hydrogen isotopes. In this work, boron-deuterium interactions were studied using molecular dynamics (MD). Reactive force field potentials were used to model the chemical interactions between B and D. An amorphous boron substrate was irradiated by D atoms at varying incident energies, 10 eV < E i < 150 eV and angles, 0° < α < 85°. The reflection probability was calculated and compared to results from the commonly-used binary collision approximation (BCA) method. This comparison found that the BCA underestimated the reflection probability at E i < 35 eV and α > 45 ∘ . The source of this discrepancy was found to be the surface binding energy model. The BCA calculation with an isotropic surface binding energy model was more closely aligned to the MD result. This, in combination with a correction function based on the MD results allows for corrections to the reflection probability of deuterium impinging on boron surfaces. The sputtering of the substrate material was also studied. While this study did not contain sufficient events to quantitatively describe the sputtering behavior, some qualitative results emerged: namely, chemical sputtering of B and D-containing molecules (BD, BD 2 , BD 3 ) at low ( < 20 eV) incident deuterium energies. This result suggests that chemical sputtering could be a significant factor in limiting boron coating lifetime when exposed to lower ion energies, such as those in detached plasmas. The results show that chemical interactions should be taken into account when modeling the interactions between D ions and B surfaces.

Boron↗