Microplane Model Parameters Identification from Different Types of Loading Experiments

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F06%3A00118143" target="_blank" >RIV/68407700:21110/06:00118143 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Jazyk výsledku
angličtina
Název v původním jazyce
Microplane Model Parameters Identification from Different Types of Loading Experiments
Popis výsledku v původním jazyce
A procedure based on layered feed-forward neural networks for the microplane material model parameters identification is proposed in the present paper. Stochastic sensitivity analysis is used to investigate influence of material parameters on the response of the structure during the loading process. Three types of loading tests are simulated and the resulting load-deflection curves served as the input values for the neural network. The following training process is governed by an evolutionary algorithm.Advantages and disadvantages of this approach are also discussed.
Název v anglickém jazyce
Microplane Model Parameters Identification from Different Types of Loading Experiments
Popis výsledku anglicky
A procedure based on layered feed-forward neural networks for the microplane material model parameters identification is proposed in the present paper. Stochastic sensitivity analysis is used to investigate influence of material parameters on the response of the structure during the loading process. Three types of loading tests are simulated and the resulting load-deflection curves served as the input values for the neural network. The following training process is governed by an evolutionary algorithm.Advantages and disadvantages of this approach are also discussed.

Rok uplatnění
2006
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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