Abstract
The identification or optimization of structures in macro scale is widely used nowadays. The goal of the paper is to apply identification techniques to obtain information about material distribution on the micro level. The presented methods open new possibilities. The structures build with the use of materials with optimal microstructure can obtain the best performance. The parameters of microstructure can be identified taking into account loads of the macro structure. The identification of microstructure parameters is not easy currently, but in future, in applications where performance of the structure is very important, the presented approach may be used with success. A bio-inspired method based on the artificial immune system (AIS) is used to solve the identification problem. Immune computing provides a great probability of finding the accurate solution. It is developed on the basis of a mechanism discovered in biological immune systems.
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References
Balthrop, J., Esponda, F., Forrest, S., Glickman, M.: Coverage and generalization in an artificial immune system. In: Proceedings of the Genetic and Evolutionary Computation. Conference GECCO, pp. 3–10 (2002)
Bąk, R., Burczyński, T.: Computational Strength of Materials (in Polish Wytrzymałość materiałów z elementami ujęcia komputerowego) WNT Warszawa (2009)
Bendsøe, M.P., Sigmund, O.: Topology Optimization – Theory, Methods and Applications. Springer, Berlin (2003)
de Castro, L.N., Von Zuben, F.J.: Learning and optimization using the clonal selection principle. IEEE Trans. Evolut. Comput. Spec. Issue Artif. Immune Syst. 6(3), 239–251 (2002)
de Castro, L.N., Timmis, J.: Artificial immune systems as a novel soft computing paradigm. Soft. Comput. 7(8), 526–544 (2003)
de Castro, L.N., Von Zuben, F.J.: Immune and neural network models: theoretical and empirical comparisons. IJCIA 1(3), 239–257 (2001)
Madej, Ł., Mrozek, A., Kuś, W., Burczyński, T., Pietrzyk, M.: Concurrent and upscaling methods in multi scale modelling – case studies. Comput. Methods Mater. Sci. 8(1), 1–15 (2008)
Poteralski, A.: Optimization of mechanical structures using artificial immune algorithm. Beyond databases, architectures, and structures. Commun. Comput. Inf. Sci. 424, 280–289 (2014)
Poteralski, A.: Data processing in immune optimization of the structure. Beyond databases, architectures, and structures (BDAS). Commun. Comput. Inf. Sci. 521, 309–319 (2015)
Poteralski, A.: Hybrid artificial immune strategy in identification and optimization of mechanical systems. J. Comput Sci. 23, 216–225 (2017)
Poteralski, A., Kuś, W., Burczyński, T.: Identification of topology of the microstructure using artificial immune system. Inverse Problems in Mechanics of Structure and Materials (IPM), Rzeszów - Baranów Sandomierski, pp. 49–50 (2013)
Ptak, M., Ptak, W.: Basics of Immunology. Jagiellonian University Press, Cracow (2000)
Wierzchoń, S.T.: Sztuczne systemy immunologiczne. Teoria i zastosowania (Artificial Immune Systems. Theory and Applications). EXIT, Warszawa (2001) (in polish)
Xie, Y.M., Steven, G.P.: Evolutionary Structural Optimization. Springer, London (1997)
Acknowledgements
The scientific research was partially funded by National Science Centre, Poland, grant no. 2015/19/B/ST8/02629 and from the statute subvention of Silesian University of Technology, Faculty of Mechanical Engineering.
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Poteralski, A. (2019). Complex System of Identification of Material Properties of Microstructure Using Bioinspired Method. In: Rodrigues, H., et al. EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization. EngOpt 2018. Springer, Cham. https://doi.org/10.1007/978-3-319-97773-7_60
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DOI: https://doi.org/10.1007/978-3-319-97773-7_60
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