Determination of rheological properties using hybrid optimisation method

• Autorzy: Foder B. , Sołek K.
• Języki publikacji: EN

Abstrakty

EN

Purpose: of this paper is description of special software developed for identification of parameters values of rheological models used by ProCAST package for simulation of state of stress in the solidifying castings. Design/methodology/approach: The PyTensionTest uses a hybrid optimization algorithm. This algorithm includes the stochastic method which searches the starting point for direct search optimization method. The identification of parameters values is based on measurement results obtained within the confines of the material tests carried out using the testing machine. Findings: This paper presents the results of approximation of stress-strain relationship for two grades of steel using the elasto-plastic rheological model with power law hardening where its parameters are linearly dependent on temperature. Research limitations/implications: This paper presents the special software that allows user to define any rheological model. Practical implications: Application of obtained values of rheological parameters in the ProCAST software allows to determine stress and strain distribution in continuous castings. It can help to optimize important process parameters. Originality/value: Developed software can approximate the results of static tension tests using rheological model depended on material temperature. This software makes possible an approximation of several stress-strain curves simultaneously. Application of the hybrid optimization method allows to obtain very precise approximation due to determination of the global minimum of the goal function.

Słowa kluczowe

EN

rheological properties; optimization methods; computer science

• Wydawca: International OCSCO World Press
• Czasopismo: Journal of Achievements in Materials and Manufacturing Engineering
• Rocznik: 2012
• Tom: Vol. 55, nr 2
• Strony: 477--482
• Opis fizyczny: Bibliogr. 7 poz., rys., tab.

Twórcy

autor

Foder B.

• Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Kraków, Poland

autor

Sołek K.

• Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Kraków, Poland

Bibliografia

• [1] J. Kennedy, R. Eberhart, Particle swarm optimization, Proceedings of the IEEE International Conference on Neutral Networks, Piscataway, 1995, 1942-1948.
• [2] Y. Shi, R. Eberhart, A modified particle swarm optimizer, Proceedings of the IEEE Conference on Evolutionary Computation, Anchorage, 1998, 69-73.
• [3] S. Xu, Y. Rahmat-Samii, Boundary conditions in particle swarm optimization revisited, IEEE Transactions on Antennas and Propagation 55 (2007) 760-765.
• [4] R. Hooke, T.A. Jeeves, “Direct Search“ solution of numerical and statistical problems, Journal of Association for Computing Machinery 8 (1961) 212-229.
• [5] L. L. Lay, T. F. Chan, Appendix B: The Method of Hooke and Jeeves, Distributed Generation: Induction and Permanent Magnet Generators, John Wiley and Sons, Ltd, Chichester, 2007.
• [6] B. Foder, Application for results analysis of static tension tests and identification of rheological parameters Master’s Thesis, AGH University of Science and Technology, Cracow, 2012 (in Polish),
• [7] M. Lutz, Python. Introduction, Third Edition, Helion, Gliwice, 2009 (in Polish).