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Neural Networks in the Identification Analysis of Structural Mechanics Problems

  • Chapter
Parameter Identification of Materials and Structures

Part of the book series: CISM International Centre for Mechanical Sciences ((CISM,volume 469))

Abstract

The Chapter is related to research carried out by the authors’ teams. The Chapter contains seven Sections and list of References. Section 1 concerns basics of selected neural networks. The main attention is paid to the Back-Propagation NNs, which are mostly applied in the analysis of engineering problems. Modifications of this NN (replicator, cascade NN, Fuzzy Weight NN) and some other NNs (Radial Basis Function NN and Adaptive Neuro-Fuzzy Inference System) are discussed in short. Data preprocessing, design problems of these NNs and approximation errors are considered as well. Section 2 is related to the application of NNs for simulating trials in the Classical Monte Carlo Method. Patterns generated by an FE program are used for the NN training and testing. A great numerical efficiency of this approach is presented on an example of the reliability analysis of an elastoplastic plane frame. Section 3 deals with the identification problems of real buildings subjected to paraseismic excitations. Section 4 is related to the application of dynamic response (eigenfrequencies excited by impulse loadings or wave propagation measurements) to the parameter identification of structural elements with defects. In Section 5 the problem of FEM models updating is considered. A hybrid approach is discussed as a sequence of the application of an initially formulated FE model with control parameters, which are identified by an NN. The calibration and verification of the updated FE model is performed on the base of laboratory tests. Section 6 discusses applications of a modification of a standard NN (Fuzzy Weight NN) to the analysis of problems from experimental structural mechanics that give fuzzy results. Section 7 deals with so-called implicit modelling (i.e. model-free, data-related NNs) of physical relationships. In References, besides basic literature, also papers written by the authors and their associates are quoted3,4.

The authors would like to express deep gratitude to Doctors E. Pabisek, K. Kuzniar, G. Piatkowski, B. Miller and Ms. M. Jakubek for their help with preparing additional numerical examples presented in textbook, Ms. E. Han for careful proof reading of the manuscript, Ms. D. Juszczyk for the word processing and Eng. G. Nowak for preparing pictures and electronic form of all the chapters.

Financial support by the Foundation for the Polish Science, Subsidy No. 13/2001 “Applications of artificial neural networks to the analysis of civil engineering problems” is gratefully acknowledged.

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Author information

Authors and Affiliations

  1. Institute of Computer Methods in Civil Engineering, Cracow University of Technology, Poland

    Zenon Waszczyszyn

  2. Chair of Structural Mechanics, Rzeszow University of Technology, Poland

    Leonard Ziemiański

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  1. Zenon Waszczyszyn
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  2. Leonard Ziemiański
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Editors and Affiliations

  1. Technical University of Warsaw, Poland

    Zenon Mróz

  2. University of Ioannina, Greece

    Georgios E. Stavroulakis

  3. Technical University of Braunschweig, Germany

    Georgios E. Stavroulakis

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Waszczyszyn, Z., Ziemiański, L. (2005). Neural Networks in the Identification Analysis of Structural Mechanics Problems. In: Mróz, Z., Stavroulakis, G.E. (eds) Parameter Identification of Materials and Structures. CISM International Centre for Mechanical Sciences, vol 469. Springer, Vienna. https://doi.org/10.1007/3-211-38134-1_7

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  • DOI: https://doi.org/10.1007/3-211-38134-1_7

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-30151-7

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