Modeling Recrystallization in Aluminum Using Input from Experimental Observations

2007 ◽  
Vol 558-559 ◽  
pp. 1057-1061 ◽  
Author(s):  
Abhijit P. Brahme ◽  
Joseph M. Fridy ◽  
Anthony D. Rollett
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Aluminum Alloys ◽  
Grain Boundary ◽  
Microstructural Evolution ◽  
Nearest Neighbor ◽  
Electron Back Scatter Diffraction ◽  
Effect Of Temperature ◽  
Model Predictions ◽  
Boundary Properties

A model has been constructed for the microstructural evolution that occurs during the annealing of aluminum alloys. Geometric and crystallographic observations from two orthogonal sections through a polycrystal using automated Electron Back-Scatter Diffraction (EBSD) were used as an input to the computer simulations to create a statistically representative threedimensional model. The microstructure is generated using a voxel-based tessellation technique. Assignment of orientations to the grains is controlled to ensure that both texture and nearest neighbor relationships match the observed distributions. The microstructures thus obtained are allowed to evolve using a Monte-Carlo simulation. Anisotropic grain boundary properties are used in the simulations. Nucleation is done in accordance with experimental observations on the likelihood of occurrences in particular neighborhoods. We will present the effect of temperature on the model predictions.

Monte Carlo Simulation of Texture and Microstructure Transformation during Annealing of Steel

2007 ◽  
Vol 129 ◽  
pp. 83-87
Author(s):  
Hua Long Li ◽  
Jong Tae Park ◽  
Jerzy A. Szpunar
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Grain Boundary ◽  
Computer Model ◽  
Graphical Representation ◽  
Structural Characteristics ◽  
Polycrystalline Materials ◽  
Virtual Experiments ◽  
Grain Boundary Character ◽  
Simulation Based

Controlling texture and microstructure evolution during annealing processes is very important for optimizing properties of steels. Theories used to explain annealing processes are complicated and always case dependent. An recently developed Monte Carlo simulation based model offers an effective tool for studying annealing process and can be used to verify the arbitrarily defined theories that govern such processes. The computer model takes Orientation Image Microscope (OIM) measurements as an input. The abundant information contained in OIM measurement allows the computer model to incorporate many structural characteristics of polycrystalline materials such as, texture, grain boundary character, grain shape and size, phase composition, chemical composition, stored elastic energy, and the residual stress. The outputs include various texture functions, grain boundary and grain size statistics that can be verified by experimental results. Graphical representation allows us to perform virtual experiments to monitor each step of the structural transformation. An example of applying this simulation to Si steel is given.

Monte Carlo simulation of Mg segregation to Ni3Al grain boundary

2000 ◽  
Vol 44 (6) ◽  
pp. 319-324 ◽  
Author(s):  
Bingyao Jiang ◽  
Xianghuai Liu ◽  
L.P Zheng ◽  
D.X Li
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Grain Boundary

MONTE CARLO SIMULATION OF ISING-LIKE IMMUNOLOGICAL SHAPE SPACE

1994 ◽  
Vol 05 (03) ◽  
pp. 513-518 ◽  
Author(s):  
DIETRICH STAUFFER
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Immune System ◽  
Response Curve ◽  
Nearest Neighbor ◽  
Shape Space ◽  
High Dimensional ◽  
Immune Systems ◽  
Probabilistic Generalization ◽  
Dimensional Shape

The high-dimensional shape space for the antibodies of the immune system is simulated with an Ising-like interaction. However, instead of the molecular field being linear in the sum of the neighbor spins, we take it as quadratic and negative. In this way the bell-shaped response curve of biological immune systems is approximated, as a probabilistic generalization of window automata. We find phase transitions only in five and more dimensions, not in two to four, for nearest-neighbor interactions.

In Situ TEM Analysis of Facet Motion in Gold Σ=3 {112} Boundaries

2001 ◽  
Vol 7 (S2) ◽  
pp. 324-325
Author(s):  
D.L. Medlin
Keyword(s):  
Thin Films ◽  
Grain Boundary ◽  
Microstructural Evolution ◽  
Experimental Studies ◽  
In Situ Tem ◽  
Tem Analysis ◽  
Computational Approaches ◽  
Boundary Properties ◽  
Boundary Curvature

Interfacial anisotropy complicates the prediction of microstructural evolution, particularly ir extreme cases for which the presence of facets and corners prevents the application of classical notions of grain-boundary curvature. Although there has been much effort at incorporating anisotropic grain-boundary properties, including faceted geometries, into computational approaches for microstructural evolution, at present our mechanistic understanding of the behavior of facets anc their junctions remains limited. In this presentation, we investigate the development of faceted boundaries between Σ=3 <111> oriented grains in epitaxially deposited gold thin films. This system is well suited tc experimental studies of facet evolution since the crystallography and structure of the boundaries is already well understood. It is well known that “double-positioning” of epitaxially aligned <111> grains on a surface of three-fold or six-fold symmetry results in a microstructure composed of grains in two twin-related (Σ=3) variants that are separated by facets running vertically through the film and forming 120 degree corners [1,2].

An AB Initio Calculation of the Pd-V FCC Superstructure Phase Diagram with Fourth Nearest Neighbor Cluster Interactions

1992 ◽  
Vol 291 ◽  
Author(s):  
Patrick D. Tepesch ◽  
G. Ceder ◽  
C. Wolverton ◽  
D. De Fontaine
Keyword(s):  
Phase Diagram ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Ab Initio Calculation ◽  
Nearest Neighbor ◽  
Tight Binding ◽  
Monte Carlo Simulation Technique ◽  
Experimental Diagram ◽  
Neighbor Cluster ◽  
Independent Pair

ABSTRACTThe Monte Carlo technique was used to calculate the phase diagram of the fee superstructures in the Pd-V system using up to fourth nearest neighbor, concentration independent, pair and multiplet interactions. The interactions were computed by the method of Direct Configurational Averaging using a Linearized Muffin-Tin Orbital Hamiltonian cast into the tight binding form. The phase diagram was computed with a fast Monte Carlo simulation technique using environment sampling. The two fee ground states in experimental diagram are predicted to be stable. The computed transition temperatures are higher than those found experimentally.

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