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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Defect cluster and nonequilibrium gas bubble associated growth in irradiated UMo fuels – a cluster dynamics and phase field model

Irradiation examination shows that gas bubble swelling kinetics is much faster after irradiation-induced recrystallization than that prior recrystallization in UMo fuels. It implies that gas bubbles in coarse grains and small recrystallized grains have different growth behavior. In this work, a phase-field model of gas bubble evolution integrating microstructure dependent cluster dynamics has been developed, for the first time, to study the gas bubble swelling behavior in the recrystallization zone of UMo fuels. Generation, diffusion, reaction, sink, emission and clustering of vacancies and interstitials are described by the cluster dynamics model while a phase-field model is used to describe the evolution of non-equilibrium gas bubbles including nucleation and growth. With the coupled model, the effect of defect generation rate, clustering rate, interstitial emission and sink rates on grain boundaries on the gas bubble evolution are systematically simulated. A set of model parameters (defect generation rate, clustering rate, interstitial emission and sink rates) is determined by comparing measured and simulated gas bubble swelling kinetics. The results demonstrate that interstitial clustering is one of the important physical mechanisms which results in a fast gas bubble swelling kinetics in the recrystallization zone. The developed model can also be extended to study the associated growth of defect and second phase precipitates often observed in irradiated materials.

Hu, Shenyang↗
DOE OSTI2015

Cluster expansion modeling and Monte Carlo simulation of alnico 5–7 permanent magnets

The concerns about the supply and resource of rare earth (RE) metals have generated a lot of interests in searching for high performance RE-free permanent magnets. Alnico alloys are traditional non-RE permanent magnets and have received much attention recently due their good performance at high temperature. In this paper, we develop an accurate and efficient cluster expansion energy model for alnico 5–7. Monte Carlo simulations using the cluster expansion method are performed to investigate the structure of alnico 5–7 at atomistic and nano scales. The alnico 5–7 master alloy is found to decompose into FeCo-rich and NiAl-rich phases at low temperature. The boundary between these two phases is quite sharp (∼2 nm) for a wide range of temperature. The compositions of the main constituents in these two phases become higher when the temperature gets lower. Both FeCo-rich and NiAl-rich phases are in B2 ordering with Fe and Al on α-site and Ni and Co on β-site. The degree of order of the NiAl-rich phase is much higher than that of the FeCo-rich phase. A small magnetic moment is also observed in NiAl-rich phase but the moment reduces as the temperature is lowered, implying that the magnetic properties of alnico 5–7 could be improved by lowering annealing temperature to diminish the magnetism in NiAl-rich phase. The results from our Monte Carlo simulations are consistent with available experimental results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Cluster dynamics models of irradiation damage accumulation in ferritic iron. II. Effects of reaction dimensionality

The black dot damage features which develop in iron at low temperatures exhibit significant mobility during in situ irradiation experiments via a series of discrete, intermittent, long range hops. By incorporating this mobility into cluster dynamics models, the temperature dependence of such damage structures can be explained with a surprising degree of accuracy. Such motion, however, is one dimensional in nature. This aspect of the physics has not been fully considered in prior models. This article describes one dimensional reaction kinetics in the context of cluster dynamics and applies them to the black dot problem. This allows both a more detailed description of the mechanisms by which defects execute irradiation-induced hops while allowing a full examination of the importance of kinetic assumptions in accurately assessing the development of this irradiation microstructure. Results are presented to demonstrate whether one dimensional diffusion alters the dependence of the defect population on factors such as temperature and defect hop length. Finally, the size of interstitial loops that develop is shown to depend on the extent of the reaction volumes between interstitial clusters, as well as the dimensionality of these interactions.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Cluster growth modeling of plateau erosion

The pattern of erosion of a plateau along an escarpment may be modeled usng cluster growth techniques, recently popularized in models of drainage network evolution. If erosion on the scarp takes place in discrete events at rates subject to local substrate strength, the whole range of behavior is described by a combination of three cluster growth mechanisms: invasion percolation, Eden growth and diffusion-limited aggregation (DLA). These model the relative importance of preexisting substrate strength, background weathering, and seepage weathering and erosion respectively. The rate of seepage processes is determined by the efflux of groundwater at the plateau margin, which in turn is determined by the pressure field in the plateau aquifer. If this process acted alone, it would produce erosion patterns in the form of Laplacian fractals, with groundwater recharge from a distant source, or Poissionian fractals, with groundwater recharge uniform over the plateau. DLA is used to mimic the Laplacian or Poissonian potential field and the corresponding seepage growth process. The scaling structure of clusters grown by pure DLA, invasion percolation, or Eden growth is well known; this study presents a model which combines all three growth mechanisms for the first time. Mixed growth processes create clusters with different scaling properties and morphologies over distinct length scale ranges, and this is demonstrable in natural examples of plateau erosion.

Stark, Colin P.↗
DOE OSTI2013

Simulating star clusters with the AMUSE software framework. I. Dependence of cluster lifetimes on model assumptions and cluster dissolution modes

We perform a series of simulations of evolving star clusters using the Astrophysical Multipurpose Software Environment (AMUSE), a new community-based multi-physics simulation package, and compare our results to existing work. These simulations model a star cluster beginning with a King model distribution and a selection of power-law initial mass functions and contain a tidal cutoff. They are evolved using collisional stellar dynamics and include mass loss due to stellar evolution. After studying and understanding that the differences between AMUSE results and results from previous studies are understood, we explored the variation in cluster lifetimes due to the random realization noise introduced by transforming a King model to specific initial conditions. This random realization noise can affect the lifetime of a simulated star cluster by up to 30%. Two modes of star cluster dissolution were identified: a mass evolution curve that contains a runaway cluster dissolution with a sudden loss of mass, and a dissolution mode that does not contain this feature. We refer to these dissolution modes as 'dynamical' and 'relaxation' dominated, respectively. For Salpeter-like initial mass functions, we determined the boundary between these two modes in terms of the dynamical and relaxation timescales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

A Parallel EM Algorithm for Model-Based Clustering Applied to the Exploration of Large Spatio-Temporal Data

We develop a parallel EM algorithm for multivariate Gaussian mixture models and use it to perform model-based clustering of a large climate data set. Three variants of the EM algorithm are reformulated in parallel and a new variant that is faster is presented. All are implemented using the single program, multiple data (SPMD) programming model, which is able to take advantage of the combined collective memory of large distributed computer architectures to process larger data sets. Displays of the estimated mixture model rather than the data allow us to explore multivariate relationships in a way that scales to arbitrary size data. We study the performance of our methodology on simulated data and apply our methodology to a high resolution climate dataset produced by the community atmosphere model (CAM5). This article has supplementary material online.

Chen, Wei-Chen↗
NASA NTRS1989

Transport-related phenomena for clusters of drops

Calculations for n-decane drops evaporating in a spherical cluster surrounded by unvitiated ambient air at atmospheric pressure were performed using two previously proposed cluster models. Both cluster models predict that turbulent transport effects are more important in the case of small clusters. This is due to the smaller volume to surface ratio and thus to the greater transport of hot unvitiated gas to the drops in order to promote evaporation. The results obtained are compared with those of two turbulent models for each one of the 'trapping factors' and similarity models.

Bellan, J.↗
DOE OSTI2014

Non-ideal magnetohydrodynamic simulations of the two-stage fragmentation model for cluster formation

We model molecular cloud fragmentation with thin-disk, non-ideal magnetohydrodynamic simulations that include ambipolar diffusion and partial ionization that transitions from primarily ultraviolet-dominated to cosmic-ray-dominated regimes. These simulations are used to determine the conditions required for star clusters to form through a two-stage fragmentation scenario. Recent linear analyses have shown that the fragmentation length scales and timescales can undergo a dramatic drop across the column density boundary that separates the ultraviolet- and cosmic-ray-dominated ionization regimes. As found in earlier studies, the absence of an ionization drop and regular perturbations leads to a single-stage fragmentation on pc scales in transcritical clouds, so that the nonlinear evolution yields the same fragment sizes as predicted by linear theory. However, we find that a combination of initial transcritical mass-to-flux ratio, evolution through a column density regime in which the ionization drop takes place, and regular small perturbations to the mass-to-flux ratio is sufficient to cause a second stage of fragmentation during the nonlinear evolution. Cores of size ∼0.1 pc are formed within an initial fragment of ∼pc size. Regular perturbations to the mass-to-flux ratio also accelerate the onset of runaway collapse.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Single-size and cluster dynamics modeling of intra-granular fission gas bubbles in UO 2

For this work, we perform simulations of intra-granular fission gas bubble evolution in UO 2 using both a relatively simple, computationally inexpensive single-size model and a detailed cluster dynamics model. Simulations encompass 36 experimental cases from 4 different databases, covering various temperature and burnup levels. We systematically compare results from the two models to each other and to post-irradiation experimental data of bubble average size and number density. Overall, the model-to-model comparisons reveal an excellent agreement across the set of simulations. This outcome indicates that, in spite of the underlying assumptions, the single-size model provides a good approximation of the complex physical behavior that is more rigorously described by the cluster dynamics model. Qualitatively, both models reproduce the trends of the experimental data with temperature and burnup correctly. Quantitatively, calculated results are either in good agreement with the data or within errors that appear consistent with the inherent uncertainties. Moreover, for the single-size model, we demonstrate and assess a multiscale approach whereby values for the fission gas atom diffusion coefficient from separate atomistic calculations are used. Systematic comparisons to experimental data point out a credible accuracy of the multiscale model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

A cluster expansion model for predicting activation barrier of atomic processes

We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEB results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog.

97 MATHEMATICS AND COMPUTING↗