Application of evolutionary algorithms to optimize the model parameters of casting cooling process

• Autorzy: Kluska-Nawarecka, S. , Górny, Z. , Smolarek-Grzyb, A.
• Języki publikacji: EN

Abstrakty

EN

One of the most commonly used methods of numerical simulation is the finite element method (FEM). Its popularity is reflected in the number of tools supporting the preparation of simulation models. However, despite its usefulness, FEM is often very troublesome in use; the problem is the selection of the finite element mesh or shape function. In addition, MES assumes a complete knowledge of the simulated process and of the parameters describing the investigated phenomena, including model geometry, boundary conditions, physical parameters, and mathematical model describing these phenomena. A comparison of the data obtained from physical experiments and simulations indicates an inaccuracy, which may result from the incorrectly chosen shape of element or geometry of the grid. The application of computational intelligence methods, combined with knowledge of the manufacturing technology of metal products, should allow an efficient selection of parameters of the mathematical models and, as a consequence, more precise control of the process of the casting solidification and cooling to ensure the required quality. The designed system has been integrated with the existing simulation environment, which will significantly facilitate the preparation and implementation of calculations of this type. Moreover, the use of a distributed model will significantly reduce the time complexity of calculations, requiring multiple repetition of complex simulations to estimate the quality of the different sets of parameters.

Słowa kluczowe

PL

krzepnięcie; odlewy; parametry krzepnięcia; symulacja numeryczna

EN

solidification casting process; casting; parameters of casting solidification; evolutionary algorithm; numerical simulation; cooling process

• Czasopismo: Archives of Foundry Engineering
• Rocznik: 2010
• Tom: Vol. 10, iss. 4
• Strony: 89--92
• Opis fizyczny: Bibliogr. 11 poz., rys., wykr.

Twórcy

autor

Kluska-Nawarecka, S.

• Foundry Research Institute, ul. Zakopiańska 73, 30-418 Kraków, Poland

autor

Górny, Z.

• Foundry Research Institute, ul. Zakopiańska 73, 30-418 Kraków, Poland

autor

Smolarek-Grzyb, A.

• AGH University of Science and Technology, Department of Industrial Computer Science, Al. Adama Mickiewicza 30, 30 - 059 Kraków, Poland ,

Bibliografia

• [1] Górny Z., Kluska–Nawarecka S., Kisiel–Dorohinicki M., Mathematical and simulation models in studies of copper and aluminium alloys, The Foundry Research Institute, Krakow 2003.
• [2] Byrski A., Kisiel-Dorohinicki M., Kluska-Nawarecka S., Evolutionary optimisation of FEM simulation parameters of cooling and solidification process, KomPlasTech 2004, Krakow 2004.
• [3] Suchy J., Mochnacki B., Modelling and simulation solidification process, PWN, Warsaw 1993.
• [4] Goldberg D.E, Genetic Algorithms in Search, Optimization and Machine Learning, Kluwer Academic Publishers, Boston, 1989.
• [5] J. Arabas: Lectures in evolutionary algorithms, Warszawa: WNT, 2001.
• [6] Kluska–Nawarecka S., Computer-aided methods od the diagnosis of casting defects, The Foundry Research Institute, Krakow, 1999.
• [7] Handzlik P., Trębacz L., Byrski A., Kisiel-Dorohinicki M., Application of distributed genetic algorithm to optimisation of FEM simulation parameters of solidification process, KomPlasTech 2005, Krakow, 2005.
• [8] Górny Z., Casting non-ferrous alloys, WNT, 1992.
• [9] Duda J.: An evolutionary algorithm for scheduling in a foundry, Archives of Foundry vol. 8, Katowice 2003.
• [10] Macioł A., Stawowy A.: Discrete event simulation for foundry system design, Archives of Foundry, 2005, R. 5, nr 17, str. 155-162.
• [11] Stawowy A., Wrona R., Macioł A.: Evolutionary algorithm for castings cost evaluation, Archives of Foundry, 2006, R. 6, nr 18, t. 1, str. 21-26.