Combinatorial reliability-based optimization of nonlinear finite element model using an artificial neural network-based approximation
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Combinatorial reliability-based optimization of nonlinear finite element model using an artificial neural network-based approximation
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20101 - Civil engineering
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science
ISBN
978-3-030-64583-0
ISSN
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e-ISSN
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Number of pages
13
Pages from-to
359-371
Publisher name
Neuveden
Place of publication
Siena, Italy
Event location
Siena, Itálie
Event date
Jul 19, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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