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Sequential simulation and neural network in the stress–strain curve identification over the large strains using tensile test

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F17%3APU123821" target="_blank" >RIV/00216305:26210/17:PU123821 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/s00419-017-1234-0" target="_blank" >http://dx.doi.org/10.1007/s00419-017-1234-0</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s00419-017-1234-0" target="_blank" >10.1007/s00419-017-1234-0</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Sequential simulation and neural network in the stress–strain curve identification over the large strains using tensile test

  • Original language description

    Two alternative methods for the stress–strain curve determination in the large strains region are proposed. Only standard force–elongation response is needed as an input into the identification procedure. Both methods are applied to eight various materials, covering a broad spectre of possible ductile behaviour. The first method is based on the iterative procedure of sequential simulation of piecewise stress–strain curve using the parallel finite element modelling. Error between the computed and experimental force–elongation response is low, while the convergence rate is high. The second method uses the neural network for the stress–strain curve identification. Large database of force–elongation responses is computed by the finite element method. Then, the database is processed and reduced in order to get the input for neural network training procedure. Training process and response of network is fast compared to sequential simulation. When the desired accuracy is not reached, results can be used as a starting point for the following optimization task.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20302 - Applied mechanics

Result continuities

  • Project

    <a href="/en/project/LO1202" target="_blank" >LO1202: NETME CENTRE PLUS</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    ARCHIVE OF APPLIED MECHANICS

  • ISSN

    0939-1533

  • e-ISSN

    1432-0681

  • Volume of the periodical

    87

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    17

  • Pages from-to

    1077-1093

  • UT code for WoS article

    000403361400010

  • EID of the result in the Scopus database

    2-s2.0-85014578067