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NASA NTRS1992

Estimation of the viscosities of silicate liquids at high pressure from measurements of oxygen diffusivity

The dynamics and evolution of a magma ocean depend significantly on the structure and physical properties of silicate liquids at high pressure. Viscosity is particularly important because of its effect on the dynamics of convection and crystal setting. Traditionally, the viscosities of silicate liquids have been measured at high pressure by falling sphere viscometry but, due to some limitations of this technique, few measurements have been made at pressures exceeding 2.5 GPa. An alternative approach, which has previously been proven up to 2 GPa, is to use high pressure measurements of oxygen self-diffusivity (D) to estimate viscosity (eta) from the Eyring relationship eta = kT/D lambda (where k is the Boltzmann constant, T is absolute temperature, and lambda is the diffusive jump distance). We have performed preliminary experiments on Na2Si4O9 liquid in order to explore the feasibility of this method up to pressures in excess of 10 GPa. Diffusion couples were prepared from glass starting materials with one half of the sample enriched in O-18 and the other half containing the natural abundance (0.2 wt percent). Diffusion experiments were performed at 1600 to 1800 C at pressures in the range of 2.5 to 10 GPa for times up to 6 minutes using a 1200 ton multianvil apparatus. Oxygen diffusivities were derived from the resulting O-18 concentration profiles, which were analyzed using an ion microprobe. At 1800 C, oxygen diffusivities increase continuously from 1 x 10(exp -10) m(exp -2) s(exp -1) at 2.5 Gpa to 5 x 10(exp -10) m(exp -2) s(exp -1) at 10 GPa. From the Eyring relationship, the viscosity of Na2SiO9 liquid is predicted to decrease by approx. 0.7 log units over this pressure range at 1800 C. These trends, which can be related to changes in the structure of the liquid at high pressure, are in agreement with results of molecular dynamics calculations. These results suggest that it should be possible to estimate the viscosities of silicate liquids up to at least 15 GPa and 2200 C by this method.

Rubie, D. C.↗

NASA NTRS1982

Molecular dynamics simulation of propagating cracks

Steady state crack propagation is investigated numerically using a model consisting of 236 free atoms in two (010) planes of bcc alpha iron. The continuum region is modeled using the finite element method with 175 nodes and 288 elements. The model shows clear (010) plane fracture to the edge of the discrete region at moderate loads. Analysis of the results obtained indicates that models of this type can provide realistic simulation of steady state crack propagation.

Mullins, M.↗

NASA NTRS2015

Effects of Atomic-Scale Structure on the Fracture Properties of Amorphous Carbon - Carbon Nanotube Composites

The fracture of carbon materials is a complex process, the understanding of which is critical to the development of next generation high performance materials. While quantum mechanical (QM) calculations are the most accurate way to model fracture, the fracture behavior of many carbon-based composite engineering materials, such as carbon nanotube (CNT) composites, is a multi-scale process that occurs on time and length scales beyond the practical limitations of QM methods. The Reax Force Field (ReaxFF) is capable of predicting mechanical properties involving strong deformation, bond breaking and bond formation in the classical molecular dynamics framework. This has been achieved by adding to the potential energy function a bond-order term that varies continuously with distance. The use of an empirical bond order potential, such as ReaxFF, enables the simulation of failure in molecular systems that are several orders of magnitude larger than would be possible in QM techniques. In this work, the fracture behavior of an amorphous carbon (AC) matrix reinforced with CNTs was modeled using molecular dynamics with the ReaxFF reactive forcefield. Care was taken to select the appropriate simulation parameters, which can be different from those required when using traditional fixed-bond force fields. The effect of CNT arrangement was investigated with three systems: a single-wall nanotube (SWNT) array, a multi-wall nanotube (MWNT) array, and a SWNT bundle system. For each arrangement, covalent bonds are added between the CNTs and AC, with crosslink fractions ranging from 0-25% of the interfacial CNT atoms. The SWNT and MWNT array systems represent ideal cases with evenly spaced CNTs; the SWNT bundle system represents a more realistic case because, in practice, van der Waals interactions lead to the agglomeration of CNTs into bundles. The simulation results will serve as guidance in setting experimental processing conditions to optimize the mechanical properties of CNT composites.

Jensen, Benjamin D.↗

NASA NTRS1995

Fast Multipole Methods for Three-Dimensional N-body Problems

We are developing computational tools for the simulations of three-dimensional flows past bodies undergoing arbitrary motions. High resolution viscous vortex methods have been developed that allow for extended simulations of two-dimensional configurations such as vortex generators. Our objective is to extend this methodology to three dimensions and develop a robust computational scheme for the simulation of such flows. A fundamental issue in the use of vortex methods is the ability of employing efficiently large numbers of computational elements to resolve the large range of scales that exist in complex flows. The traditional cost of the method scales as Omicron (N(sup 2)) as the N computational elements/particles induce velocities at each other, making the method unacceptable for simulations involving more than a few tens of thousands of particles. In the last decade fast methods have been developed that have operation counts of Omicron (N log N) or Omicron (N) (referred to as BH and GR respectively) depending on the details of the algorithm. These methods are based on the observation that the effect of a cluster of particles at a certain distance may be approximated by a finite series expansion. In order to exploit this observation we need to decompose the element population spatially into clusters of particles and build a hierarchy of clusters (a tree data structure) - smaller neighboring clusters combine to form a cluster of the next size up in the hierarchy and so on. This hierarchy of clusters allows one to determine efficiently when the approximation is valid. This algorithm is an N-body solver that appears in many fields of engineering and science. Some examples of its diverse use are in astrophysics, molecular dynamics, micro-magnetics, boundary element simulations of electromagnetic problems, and computer animation. More recently these N-body solvers have been implemented and applied in simulations involving vortex methods. Koumoutsakos and Leonard (1995) implemented the GR scheme in two dimensions for vector computer architectures allowing for simulations of bluff body flows using millions of particles. Winckelmans presented three-dimensional, viscous simulations of interacting vortex rings, using vortons and an implementation of a BH scheme for parallel computer architectures. Bhatt presented a vortex filament method to perform inviscid vortex ring interactions, with an alternative implementation of a BH scheme for a Connection Machine parallel computer architecture.

Koumoutsakos, P.↗

NASA NTRS2009

Infrared Heterodyne Spectroscopy and its Unique Application to Planetary Studies

Since the early 1970's the infrared heterodyne technique has evolved into a powerful tool for the study of molecular constituents, temperatures, and dynamics in planetary atmospheres. Its extremely high spectral resolution (Lambda/(Delta)Lambda/>10(exp 6)) and highly accurate frequency measurement (to 1 part in 10(exp 8)) enabled the detection of nonthermal/natural lasing phenomena on Mars and Venus; direct measurements of winds on Venus, Mars, and Titan; study of mid-infrared aurorae on Jupiter; direct measurement of species abundances on Mars (ozone, isotopic CO2), hydrocarbons on Jupiter, Saturn., Neptune, and Titan, and stratospheric composition in the Earth's stratosphere (O3, CIO, N2O, CO2 ....). Fully resolved emission and absorption line shapes measured by this method enabled the unambiguous retrieval of molecular abundances and local temperatures and thermal structure in regions not probed by other techniques. The mesosphere of Mars and thermosphere of Venus are uniquely probed by infrared heterodyne spectroscopy. Results of these studies tested and constrained photochemical and dynamical theoretical models describing the phenomena measured. The infrared heterodyne technique will be described. Highlights in its evolution to today's instrumentation and resultant discoveries will be presented, including work at Goddard Space Flight Center and the University of Koln. Resultant work will include studies supporting NASA and ESA space missions and collaborations between instrumental and theoretical groups.

Kostiuk, Theodore↗

NASA NTRSDate not supplied

Solid-state Precipitation in Molecular Dynamics: KMC-MD Hybrid Simulations

A critical drawback of molecular dynamics (MD) simulations when modeling physical properties is the limitation to short timescales. Solid state precipitation is one behavior that is not significantly observable at timescales accessible to MD, and thus has been difficult to simulate at an MD scale. Taking inspiration from Kinetic Monte-Carlo (KMC) methods for simulating diffusion on a rigid lattice, we have developed a hybrid KMC-MD approach to enable simulation of solid-state precipitation during MD simulation implemented in LAMMPS. This method incorporates the atomic neighbor hopping behavior utilized by KMC simulations into a MD simulation with a variable local lattice configuration. By accelerating nearest-neighbor atomic hopping with this technique, solid-state precipitation can be observed at an MD timescale. Utilizing theory based on persistent-embryo methods for liquid-solid precipitation in MD we demonstrate the calculation of critical nucleus size for the gamma’ precipitation out of gamma phase in the Ni-Al system.

Molecular Dynamics↗

NASA NTRSDate not supplied

Solid-state Precipitation in Molecular Dynamics: kMC-MD Hybrid Simulations

Molecular Dynamics↗

NASA NTRS1978

Laser-enhanced dynamics in molecular rate processes

The present discussion deals with some theoretical aspects associated with the description of molecular rate processes in the presence of intense laser radiation, where the radiation actually interacts with the molecular dynamics. Whereas for weak and even moderately intense radiation, the absorption and stimulated emission of photons by a molecular system can be described by perturbative methods, for intense radiation, perturbation theory is usually not adequate. Limiting the analysis to the gas phase, an attempt is made to describe nonperturbative approaches applicable to the description of such processes (in the presence of intense laser radiation) as electronic energy transfer in molecular (in particular atom-atom) collisions; collision-induced ionization and emission; and unimolecular dissociation.

George, T. F.↗

NASA NTRSDate not supplied

Machine-Learned Committor Functions for Reactive Molecular Dynamics

Reactive molecular dynamics (MD) is a powerful tool for atomistic-scale modeling of a diverse range of chemical processes. However, scaling these simulations to large systems and long times scales remains a challenge because of the complexity of the potential energy function required. The authors previously developed a heuristic approach, called REACTER, that incorporates reactivity in MD simulations in a less general but much more computationally efficient manner. REACTER uses standard, fixed valence force fields as the underlying potentialenergy surface for describing all interatomic interactions but adds a procedure for enforcing user-defined reactions that occur when certain geometric constraints on relative atomic positions are satisfied. Further, these bonding changes can be accepted or rejected with a probability related tothe local thermal energy. This work seeks to generalize this approach by replacing the set of user defined geometric constraints and energetic criteria with a committor function that specifies the probability of a reaction occurring on the basis of the local atomic configuration. The committor function is a useful mathematical tool for modeling rare events but, unfortunately, is very difficult to compute for realistic systems in a general way. This work describes a method for approximating the committor function using a machine learning approach, specifically a deep neural network trained with data from reactive MD and DFT-based dynamics simulations. This network is coupled to the existing REACTER protocol, as implemented in the LAMMPS MD package, and used to make on-the-fly predictions of reaction probabilities without the more extensive user input previously required. The new method is demonstrated using the polymerization of polystyrene as a case study. Although very dependent on the quality and quantity of training data, machine-learned committor functions show promise as a method for incorporating reaction probability from higher level calculations into highly scalable MD simulations.

polymer simulations↗

NASA NTRSDate not supplied

REACTER: A Versatile Tool for Large-Scale Reactive Molecular Dynamics

Accurately describing reactive events over long length and time scales remains a grand challenge of computational materials science. REACTER is a general protocol for modeling chemical reactions using classical force fields, and is implemented in the popular molecular dynamics software LAMMPS. REACTER has a growing user base and has been used as a model-building tool for a variety of materials, including thermoplastics, thermosets, glassy materials and composites. The method has also been applied to accelerated modeling of reversible chemical reactions, such as the formation of electrochemical components for batteries. Recently, the REACTER protocol has received some major upgrades to enhance its ability to predict when reactions occur and to make it easier to use. Force field parameters can now be automatically assigned to newly created bonds, angles and other interactions. Advanced reaction constraints have also been added, including an Arrhenius constraint to enforce an effective activation energy, a root-mean-square-deviation option for complex geometrical constraints, and a constraint based on the total potential energy of the atoms involved in a reactive site. This potential energy constraint allows for the accurate reproduction of DFT-based tight-binding (DFTB3) predicted bond dissociation curves for mechanically induced bond breaking.

polymer simulations, molecular dynamics↗

NASA NTRSDate not supplied

Determination of Interfacial Energy for Solid-State Precipitation

Precipitation of strengthening phases from solid state is a critical process for many materials. For example, the high-temperature creep resistance of Ni-based superalloys is governed by ’ precipitates. However, the interfacial energy which controls the precipitation is expensive to determine experimentally. For simulations, the atomic nature of precipitation events necessitates using Molecular Dynamics (MD) so relying on fitting to a-priori experimental behavior is not required. However, the solid-state precipitation takes orders of magnitude longer time than is accessible for traditional MD simulation. Taking inspiration from Kinetic Monte-Carlo (KMC) methods for simulating diffusion on a rigid lattice, we have developed a hybrid KMC-MD approach to enable simulation of solid-state precipitation (and determination of the interfacial energy). Implementing these methods in LAMMPS, we calculated the interfacial energy for the ’ precipitation out of a super-saturated  phase in Ni-based superalloys. The resulting interfacial energy value for the Ni-Al system is well within the accuracy of experimental values, demonstrating the capability of this method. Enabling the calculation of the interfacial energy without a-priori experimental knowledge of the precipitation unlocks a more efficient ICME-based approach for guiding annealing protocols in Ni-based superalloys and other solid-state precipitation systems.

Precipitation↗

NASA NTRS1976

Environmental dynamics at orbital altitudes

The work reported involved the improvement of aerodynamic theory for free molecular and transition flow regimes. The improved theory was applied to interpretation of the dynamic response of objects traveling through the atmosphere. Satellite drag analysis includes analysis methods, atmospheric super rotation effects, and satellite lift effects on orbital dynamics. Transition flow regimes were studied with falling sphere data and errors resulting in inferred atmospheric parameters from falling sphere techniques. Improved drag coefficients reveal considerable error in previous falling sphere data. The drag coefficient has been studied for the entire spectrum of Knudsen Number and speed ratio, with particular emphasis on the theory of the very low-speed ratio regime.

Karr, G. R.↗

NASA NTRS2003

Atomic-scale Modeling of the Structure and Dynamics of Dislocations in Complex Alloys at High Temperatures

We report on the progress made during the first year of the project. Most of the progress at this point has been on the theoretical and computational side. Here are the highlights: (1) A new code, tailored for high-end desktop computing, now combines modern Accelerated Dynamics (AD) with the well-tested Embedded Atom Method (EAM); (2) The new Accelerated Dynamics allows the study of relatively slow, thermally-activated processes, such as diffusion, which are much too slow for traditional Molecular Dynamics; (3) We have benchmarked the new AD code on a rather simple and well-known process: vacancy diffusion in copper; and (4) We have begun application of the AD code to the diffusion of vacancies in ordered intermetallics.

Daw, Murray S.↗

NASA NTRSDate not supplied

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗

NASA NTRS2021

Analysis of Nonlinear Shrinkage for the Bound Metal Deposition Manufacturing using Multi-scale Approach

We consider problem of nonlinear shrinkage of the metal part during bound metal deposition manufacturing on the ground and in zero-G. To analyze this problem we developed multi-scale physics-based approach that spans atomistic dynamics at the scale of nanoseconds and the full part shrinkage at the time scale of hours. Using this approach we estimated the key parameters of the problem including grain boundary width, coefficient of surface diffusion, initial redistribution of particles during debinding stage, micro-structure evolution from round particles to densely packed grains and corresponding change of the total and chemical free energy, and sintering stress. The introduced method was used to predict shrinkage at the level of two particles, filament cross-section, sub-model, and the whole green, brown, and metal parts. To further improve accuracy and reliability of the shrinkage predictions we propose concept of intelligent additive manufacturing of metal powders in space that combines the strengths of both physics-based and data-driven methods of analysis of AM.

bound metal deposition↗

NASA NTRS1991

Molecular Dynamics study of Pb overlayer on Cu(100)

Isothermal-isobaric Molecular Dynamics (MD) simulation of a submonolayer Pb film in c(2x2) ordered structure adsorbed on a Cu(100) substrate showed retention of order to high T. The Embedded Atom Method (EAM) calculated the energy of atoms of overlayer and substrate. The time-averaged squared modulus of the two dimensional structure factor for the Pb overlayer measured the order of the overlayer. The results are for increasing T only, and require verification by simulated cooling.

Karimi, M.↗

NASA NTRS2004

Stress Distribution During Deformation of Polycrystalline Aluminum by Molecular-Dynamics and Finite-Element Modeling

In this paper, a multiscale modelling strategy is used to study the effect of grain-boundary sliding on stress localization in a polycrystalline microstructure with an uneven distribution of grain size. The development of the molecular dynamics (MD) analysis used to interrogate idealized grain microstructures with various types of grain boundaries and the multiscale modelling strategies for modelling large systems of grains is discussed. Both molecular-dynamics and finite-element (FE) simulations for idealized polycrystalline models of identical geometry are presented with the purpose of demonstrating the effectiveness of the adapted finite-element method using cohesive zone models to reproduce grain-boundary sliding and its effect on the stress distribution in a polycrystalline metal. The yield properties of the grain-boundary interface, used in the FE simulations, are extracted from a MD simulation on a bicrystal. The models allow for the study of the load transfer between adjacent grains of very different size through grain-boundary sliding during deformation. A large-scale FE simulation of 100 grains of a typical microstructure is then presented to reveal that the stress distribution due to grain-boundary sliding during uniform tensile strain can lead to stress localization of two to three times the background stress, thus suggesting a significant effect on the failure properties of the metal.

Yamakov, V.↗

NASA NTRS2019

Considerations for Femtosecond Laser Electronic Excitation Tagging in High-Speed Flows

Femtosecond laser electronic excitation tagging (FLEET) is an unseeded method for molecular tagging which offers valuable opportunities for measurement of high-speed (transonic, supersonic or hypersonic) flows. The unique nature of high-speed testing demands certain performance from FLEET such as satisfactory signal-to-noise ratio (SNR) at depressed static conditions (i.e., low temperatures, pressures and densities), wide dynamic range for velocity determination (especially single-shot), and measurements with acceptable accuracy and precision. This dissertation strives to evaluate FLEET in those regards and provide strategies to maximize the method's capabilities. A zero-dimensional kinetics model in nitrogen explains FLEET signal changes with pressure/density and/or temperature in terms of plasma-chemical reactions. Poorly known rate coefficients are tuned by comparing model output to measurements, with temporal agreement up to several hundred nanoseconds. Modeling reveals that initial signal peaks at reduced density because of slowed temporal evolution (and decay) of excited populations. Low temperatures enhance signal by enlarging cluster ion populations which contribute to excited species via electron-ion dissociative recombination. A purpose-built free jet facility provides experimental validation of the kinetics model and assesses FLEET velocimetry in low temperature and pressure/density conditions. Signal, lifetime, accuracy and precision results are obtained from unheated subsonic through Mach 4.0 operation of the facility, with best results noted. FLEET measurements of a sweeping jet (SWJ) actuator in compressible operation showcase its advantages in a highly unsteady jet containing subsonic through supersonic velocities. FLEET velocimetry is performed in the device's internal and external flow fields, with the latter compared to hot-wire anemometry. Internal measurements reveal the absence of shockwaves theorized to occur at high pressure ratios. Simultaneous qualitative measurements of compressible jet mixing are shown as a proof-of-concept. Overall, the work demonstrates that previous understanding of SWJ incompressible operation readily extends into the compressible realm. Practical aspects of performing FLEET velocimetry are detailed, along with strategies for improving measurement quality. Determination of a fundamental precision in nitrogen and air is attempted. Experiments show that increasing time delay and/or SNR improves velocimetry precision. A comparison of five camera systems indicates sensors with larger pixels capture higher SNR data and produce more precise results.

FLEET↗