Use of Stored Energy Distribution in Stochastic Vertex Model

Krystian Piękoś; Jacek Tarasiuk; Krzysztof Wierzbanowski; Brigitte Bacroix

doi:10.4028/www.scientific.net/MSF.571-572.231

Paper Titles

Diffraction Contrast Tomography - A Synchrotron Radiation Technique for Mapping Polycrystalline Microstructures in 3D
p.207

Kowari – The Residual-Stress Diffractometer for Engineering Applications at OPAL
p.213

A Critical Discussion of the sin²ψ Stress Measurement Technique
p.219

Measurement of all Six Components of X-Ray Elastic Factors
p.225

Use of Stored Energy Distribution in Stochastic Vertex Model
p.231

Imaging Diffraction Using Maxim at G3/Hasylab - Spatial Resolved Strain Measurements on Linear Friction Welded Dissimilar Materials (AA7020-T6/Ti6AlV
p.237

Two-Dimensional Mapping of Crack-Face Bridging Stresses in Alumina Using Synchrotron Micro X-Ray Beam
p.243

Application of Synchrotron Radiation to Residual Stress Analysis by IP/cosα Method
p.249

Influence of Peak Determination Method on Area Detector Type Neutron Stress Measurement
p.255

HomeMaterials Science ForumMaterials Science Forum Vols. 571-572Use of Stored Energy Distribution in Stochastic...

Use of Stored Energy Distribution in Stochastic Vertex Model

Abstract:

The stored energy distribution versus crystal orientation in polycrystalline copper was determined using synchrotron radiation. This distribution is an important input data for recrystallization models. The stochastic vertex model of recrystallization was used in the present work. It is a mixture of the classical vertex model and the Monte Carlo algorithm. Both grain boundary energy and stored energy are taken into account in the calculations. In each elementary step, a reasonably small, random modification of a given vertex position is generated and a corresponding total energy change of a system is calculated. A new vertex position is retained with a probability proportional to the Boltzmann factor. In such a way one avoids solving a complex system of equations. This approach is also closer to the stochastic nature of recrystallization process. The inclusion of the stored energy distribution in the above model enables a good explanation of the recrystallization process. The recrystallization textures for polycrystalline copper rolled to low and high reductions were predicted in agreement with experimental results.