Identification of the static recrystallization cellular automata model parameters based on inverse analysis

Mateusz Sitko¹ , Łukasz Madej¹, Roman Kuziak²

¹Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, 30 Mickiewicza Ave., 30-059 Kraków, Poland.
²Institute for Ferrous Metallurgy, 12-14 Karola Miarki St., 44-100 Gliwice, Poland.

DOI:

https://doi.org/10.7494/cmms.2014.4.0492

Abstract:

Development of the inverse algorithm for identification of the discrete cellular automata model of the static recrystallization based on the particle swarm optimization method is the main aim of the work. First, the idea of the inverse analysis approach is presented. Then subsequent modules of the algorithm are discussed, namely: direct problem model, experimental setup and optimization algorithm. The optimization part is realized by the basic variant of particle swarm optimization (PSO) method. Finally, examples of identified model parameters are presented and obtained results of recrystallized microstructures are compared with the experimental data.

Cite as:

Sitko, M., Madej, Ł., & Kuziak, R. (2014). Identification of the static recrystallization cellular automata model parameters based on inverse analysis. Computer Methods in Materials Science, 14(4), 206 – 214. https://doi.org/10.7494/cmms.2014.4.0492

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