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An analytical and experimental investigation on the normal grain growth in metals using the Monte Carlo method
AbstractThe prediction of material microstructure is of great interest to the material designers since the property and performance of materials depend strongly on their microstructures. In this work, a Monte Carlo approach is used to investigate the normal grain growth of aluminum and pure copper. The grain growth was calculated at certain temperatures using the grain growth law and compared with the simulation results by varying the Q as a parameter of simulation lattice orientation for pure aluminum. Also the results predicted by the Monte Carlo method showed a good agreement with the experimental results of grain growth of pure cooper. It was found that increase in Q increases the accuracy of the predicted results and the Monte Carlo method can be used to assess both the grain growth mechanism as well as the grain rotation in the microstructure simulation.
An analytical and experimental investigation on the normal grain growth in metals using the Monte Carlo method
AbstractThe prediction of material microstructure is of great interest to the material designers since the property and performance of materials depend strongly on their microstructures. In this work, a Monte Carlo approach is used to investigate the normal grain growth of aluminum and pure copper. The grain growth was calculated at certain temperatures using the grain growth law and compared with the simulation results by varying the Q as a parameter of simulation lattice orientation for pure aluminum. Also the results predicted by the Monte Carlo method showed a good agreement with the experimental results of grain growth of pure cooper. It was found that increase in Q increases the accuracy of the predicted results and the Monte Carlo method can be used to assess both the grain growth mechanism as well as the grain rotation in the microstructure simulation.
An analytical and experimental investigation on the normal grain growth in metals using the Monte Carlo method
Hafez Haghighat, S.M. (author) / Taheri, A. Karimi (author)
2006-09-13
7 pages
Article (Journal)
Electronic Resource
English
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