Combinatorial reliability-based optimization of nonlinear finite element model using an artificial neural network-based approximation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F21%3APU139277" target="_blank" >RIV/00216305:26110/21:PU139277 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-64583-0_33" target="_blank" >http://dx.doi.org/10.1007/978-3-030-64583-0_33</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-64583-0_33" target="_blank" >10.1007/978-3-030-64583-0_33</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Combinatorial reliability-based optimization of nonlinear finite element model using an artificial neural network-based approximation

Popis výsledku v původním jazyce

The paper describes the reliability-based optimization of TT shaped precast roof girder produced in Austria. Extensive experimental studies on small specimens and small and full-scale beams have been performed to gain information on fracture mechanical behaviour of utilized concrete. Subsequently, the destructive shear tests under laboratory conditions were performed. Experiments helped to develop an accurate numerical model of the girder. The developed model was consequently used for advanced stochastic analysis of structural response followed by reliability-based optimization to maximize shear and bending capacity of the beam and minimize production cost under defined reliability constraints. The enormous computational requirements were significantly reduced by the utilization of artificial neural network-based approximations of the original nonlinear finite element model of optimized structure.

Název v anglickém jazyce

Combinatorial reliability-based optimization of nonlinear finite element model using an artificial neural network-based approximation

Popis výsledku anglicky

The paper describes the reliability-based optimization of TT shaped precast roof girder produced in Austria. Extensive experimental studies on small specimens and small and full-scale beams have been performed to gain information on fracture mechanical behaviour of utilized concrete. Subsequently, the destructive shear tests under laboratory conditions were performed. Experiments helped to develop an accurate numerical model of the girder. The developed model was consequently used for advanced stochastic analysis of structural response followed by reliability-based optimization to maximize shear and bending capacity of the beam and minimize production cost under defined reliability constraints. The enormous computational requirements were significantly reduced by the utilization of artificial neural network-based approximations of the original nonlinear finite element model of optimized structure.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20101 - Civil engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

Lecture Notes in Computer Science

ISBN

978-3-030-64583-0

ISSN

—

e-ISSN

—

Počet stran výsledku

13

Strana od-do

359-371

Název nakladatele

Neuveden

Místo vydání

Siena, Italy

Místo konání akce

Siena, Itálie

Datum konání akce

19. 7. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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