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Neural analysis of elastoplastic plane stress problem with unilateral constraints

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Języki publikacji
EN
Abstrakty
EN
The paper is a development and continuation of paper [1] where the Panagiotopoulos approach was extended for the elastoplastic analysis. In case of elastic analysis the parameters of the Hopfield–Tank Neural Network (HTNN) are calibrated only once but the updating of the elastoplastic stiffness matrix needs an iteration of HTNN and FE system. The main problem is the matrix condensation repeated for each iteration step of the Newton–Raphson method. Besides all the improvements proposed in [2], a new interacting program has been implemented which enables a significant decrease of the processing time (number of iterations) in comparison with the time achieved in [1]. The results of the extensive numerical analysis are discussed for a tension perforated strip with a rigid bolt placed frictionlessly in a circular hole in the middle of the strip.
Rocznik
Strony
497--507
Opis fizyczny
Bibliogr. 18 poz., rys., tab., wykr.
Twórcy
autor
  • Cracow University of Technology, Institute for Computational Civil Engineering, ul. Warszwska 24, 31-155 Kraków, Poland
Bibliografia
  • [1] A.V. Avdelas et al. Neural networks for computing in the elastoplastic analysis of structures. Mechanica, 30: 1-15, 1995.
  • [2] G. Engeln-Miillges, F. Uhlig. Numerical Algorithms with C. Springer, Berlin-Heidelberg, 1996.
  • [3] J. Ghaboussi et al. Knowledge-based modeling of material behavior with neural networks. ASCE J. Engrg. Mech., 117: 132-153, 1991.
  • [4] L. Kaczmarczyk, Z. Waszczyszyn. Neural procedures for the hybrid FEM/NN analysis of elastoplastic plates. Corn-put. Assisted Mech. Engrg. Sci., 12: 379-391, 2005.
  • [5] S. Kortesis, P.G. Panagiotopoulos. Neural networks for computing in structural analysis — methods and prospects of applications. Int. J. Num. Meth. Engrg., 36: 2305-2318, 1993.
  • [6] E.S. Mistakidis, P.G. Panagiotopoulos. Numerical treatment of problems involving nonmonotone boundary or strain-stress laws. Comput. Struct., 64: 533-565, 1997.
  • [7] A.K. Noor. Computational structures technology: leap frogging into the twenty-first century. Comput. Struct., 73: 1-31, 1999.
  • [8] E. Pabisek, Z. Waszczyszyn. Neural networks in the analysis of elastoplastic stress problem with unilateral constraints. In: B.H.V. Topping, ed., Computational Engineering Using Metaphors from Nature, pp. 1-6, Civil-Comp Press, Edinburgh, 2000.
  • [9] E. Pabisek, Z. Waszczyszyn. Hybrid FEM/NN analysis of friction contact of elastic and elastoplastic bodies. In Proc. of Conf. on Numerical Methods in Continuum Mechanics, pp. 1-12, Zilina, Slovak Republic, 2003. D&D Digital Printing Office.
  • [10] P.S. Theocaris, P.G. Panagiotopoulos. Neural networks for computing in fracture mechanics — methods and prospects of applications. Comput. Methods Appl. Mech. Engry., 106: 213-228, 1993.
  • [11] P.S. Theocaris, P.G. Panagiotopoulos. Generalized hardening plasticity approximated via anisotropic elasticity: a neural network approach. Comput. Methods Appl. Mech. Engrg., 125: 123-139, 1995.
  • [12] Z. Waszczyszyn, Cz. Cichori, M. Radwanska. Stability of Structures by Finite Element Method. Elsevier, Amsterdam-Tokyo, 1994.
  • [13] Z. Waszczyszyn, ed. Neural Networks in the Analysis and Design of Structures. CISM Courses and Lectures No. 404. Springer, 1999.
  • [14] Z. Waszczyszyn, E. Pabisek. Hybrid NN/FEM analysis of the elastoplastic plane stress problem. Comput. Assisted Mech. Engrg. Sci., 6: 177-188, 1999. [15] Z. Waszczyszyn, E. Pabisek. Application of a Hopfield type neural network to the analysis of elastic problems with unilateral constraints. Comput. Assisted Mech. Engrg. Sci., 7: 757-765, 2000.
  • [16] Z. Waszczyszyn, L. Ziemianski. Neural Networks in the identification analysis of structural mechanics problems. CISM Courses and Lectures No. 469. Springer, 2005.
  • [17] Z. Waszczyszyn, L. Ziemianski. Neurocomputing in the analysis of selected inverse problems of mechanics of structures and materials. Comput. Assisted Mech. Engrg. Sci., 13: 125-159, 2006.
  • [18] P. Wriggers. Computational Contact Mechanics. John Willey &Sons, Chichester, UK, 2002.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPB1-0032-0037
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