Neural procedures for the hybrid FEM/NN analysis of elastoplatic plates

• Autorzy: Kaczmarczyk Ł. , Waszczyszyn Z.
• Języki publikacji: EN

Abstrakty

EN

A neural procedure was formulated in [4] as BPNN (Back-Propagation Neural Networks) for the simulation of generalized RMA (Return Mapping Algorithm). This procedure was evaluated to be too large to make a corresponding hybrid FEM/BPNN numerically efficient. That is why two new procedures NPI and NP2 were formulated. A description of their efficiency is presented in the paper, related to the computation number of computer operations and CPU time, carried out by FEM program FEAP and two hybrid programs FEAP/NP1 and FEAP/NP2.

Słowa kluczowe

EN

neural networks; return mapping algorithm

PL

sieci neuronowe

• Wydawca: Instytut Podstawowych Problemów Techniki PAN
• Czasopismo: Computer Assisted Mechanics and Engineering Sciences
• Rocznik: 2005
• Tom: Vol. 12, No. 4
• Strony: 379--391
• Opis fizyczny: Bibliogr. 11 poz., wykr.

Twórcy

autor

Kaczmarczyk Ł.

• Institute of Computer Methods in Civil Engineering, Cracow University of Technology, Warszawska 24, 31-155 Kraków, Poland

autor

Waszczyszyn Z.

• Institute of Computer Methods in Civil Engineering, Cracow University of Technology, Warszawska 24, 31-155 Kraków, Poland

Bibliografia

• [1] T. Purukawa, G. Yagawa. Implicit constitutive modelling for viscoplasticity using neural networks, Int. J. Num. Meth. Eng., 43: 195-219, 1998.
• [2] Z. Waszczyszyn, E. Pabisek. Hybrid NN/FEM analysis of elatoplastic plane stress problem, Comp. Assisti. Mech. Eng. Sci., 6: 177-188, 1999.
• [3] J.C. Simo, T.J.R. Hughes. Computational Inelasticity, Springer-Verlag, New York, 1998.
• [4] Z. Waszczyszyn, E. Pabisek. Neural network supported FEM analysis of elastoplastic plate binding, Research News, Budapest UTE, Special Issue 2000/4: 12-19, 2000.
• [5] Z. Waszczyszyn, Cz. Cichoń, M. Radwańska. Stability of Structures by Finite Element Methods, Elsevier, Amsterdam, 1994.
• [6] R. Taylor. FEAP - A Finite Element Analysis Program. Version 7.4 Theory Manual, Univ. of California at Berkley, 2002.
• [7] S. Haykin. Neural Networks - A Systematic Introduction, 2nd Ed., John Wiley, 1999.
• [8] Z. Waszczyszyn (Ed.). Neural Networks in the Analysis and Design of structures CISM Courses and Notes No. 404, Springer, Wien - New York, 1999.
• [9] A. Zell (Ed.) SNNS - Stuttgart Neural Simulator, User's Manual, Version 4.2, Univ. of Stuttgart and Univ. Tubingen, 1998
• [10] R. Haj-Ali, D.A. Pecknold, J. Głiaboussi, G.Z. Voyiadjis. Simulated micromechanicał models using artificial neural networks, J. Eng. Mech., 127: 730-738, 2001.
• [11] http://www.gnu.org/manual/gprof-2.9.l/gprof.html