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

Kluska-Nawarecka S., Górny Z., Smolarek-Grzyb A.

Archives of Foundry Engineering

2010

Vol. 10, iss. 4

89--92

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.