Evolutionary identification of laminates' granular parameters

• Autorzy: Beluch W. , Orantek P.
• Języki publikacji: EN

Abstrakty

EN

The paper deals with the identification of material constants in simple and hybrid laminates. It is assumed that identified constants are non-deterministic and can be described by means of different forms of the information granularity represented by interval numbers, fuzzy numbers or random variables. The Two-Stage Granular Strategy combining global (Evolutionary Algorithm) and local (gradient method supported by an Artificial Neural Network) optimization techniques is used to solve the identification problems. Finite Element Method in the granular form is used to solve the direct problem for laminates. Modal analysismethods are employed to collect measurement data for the identification process. Numerical examples presenting effectiveness of the strategy are enclosed.

Słowa kluczowe

EN

laminate; identification; evolutionary algorithm; artificial neural network; interval numbers; fuzzy numbers; random variables

PL

laminat; identyfikacja; algorytm ewolucyjny; sztuczna sieć neuronowa; liczby odstępu; liczby rozmyte; zmienne losowe

• Wydawca: Instytut Podstawowych Problemów Techniki PAN
• Czasopismo: Computer Assisted Mechanics and Engineering Sciences
• Rocznik: 2010
• Tom: Vol. 17, no. 1
• Strony: 51--58
• Opis fizyczny: Bibliogr. 12 poz., rys., tab.

Twórcy

autor

Beluch W.

autor

Orantek P.

• Department of Strength of Materials and Computational Mechanics Silesian University of Technology, Gliwice, Poland,

Bibliografia

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• [2] S. Adali, V.E. Verijenko. Optimum stacking sequence design of symmetric hybrid laminates undergoing free vibrations. Composite Structures, 54: 131-138, 2001.
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• [5] T. Burczyński, P. Orantek. The evolutionary algorithm in stochastic optimization and identification problems. In: Arabas, J. (Ed.) Evolutionary Computation and Global Optimization 2007, pp. 309-320, Warsaw, 2006.
• [6] T. Burczyński, P. Orantek. Uncertain Identification Problems in the Context of Granular Computing. In: A. Bargiela, W. Pedrycz (Eds.), Human-Centric Inforamtion Processing, SCI182, pp. 329-350, Springer Verlag, Berlin Heidelberg, 2009.
• [7] J. German. The basics of the fibre-reinforced composites' mechanics [in Polish]. Publ. of the Cracow University of Technology, Cracow, 2001.
• [8] M. Kleiber, T. Hien. The Stochastic Finite Element Method.. John Wiley & Sons, New York, 1992.
• [9] Z. Michalewicz. Genetic Algorithms + Data Structures = Evolutionary Programs. Springer, Berlin, 1996.
• [10] D. Moens, D. Vandepitte. Fuzzy Finite Element Method for Frequency Response Function Analysis of Uncertain Structures. AIAA Journal, 40(1): 126-136, 2002.
• [11] P. Orantek. The optimization and identification problems ofstructures with fuzzy parameters. 3rd European Conference on Computational Mechanics ECCM-2006, CD-Edition, Lisbon, 2006.
• [12] T. Uhl. Computer-Aided Identification of Constructional Models [in Polish]. WNT, Warsaw, 1997.