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Statements

Subject Item
n2:RIV%2F68407700%3A21110%2F04%3A01099173%21RIV%2F2005%2FMSM%2F211105%2FN
rdf:type
skos:Concept n20:Vysledek
dcterms:description
Concrete as a man-made heterogeneous material shows very complex nonlinear behavior which is extremely difficult to model both theoretically and numerically. The microplane model is a fully three-dimensional material law that includes tensional and compressive softening, damage of the material, different combinations of loading, unloading and cyclic loading along with the development of damage-induced anisotropy of the material. As a result, it is fully capable of predicting behavior of real-world concrete structures once provided with proper input data. Although the authors of the model proposed a heuristic calibration procedure, it is based on the trial-and-error method and provides guide to determination of selected material parameters. Therefore, a reliable and inexpensive procedure for parameters identification of this model is on demand. In the view of potential improvements proposed in a recent work on soft computing methods, a new procedure based on artificial neural networks . Tento příspěvek diskutuje identifikaci parametrů komplexního inženýrského modelu pomocí metod umělé inteligence. Konkrétně je představena stochastická optimalizační metoda SADE a její aplikace na určení parametrů mikroploškového modelu betonu. Concrete as a man-made heterogeneous material shows very complex nonlinear behavior which is extremely difficult to model both theoretically and numerically. The microplane model is a fully three-dimensional material law that includes tensional and compressive softening, damage of the material, different combinations of loading, unloading and cyclic loading along with the development of damage-induced anisotropy of the material. As a result, it is fully capable of predicting behavior of real-world concrete structures once provided with proper input data. Although the authors of the model proposed a heuristic calibration procedure, it is based on the trial-and-error method and provides guide to determination of selected material parameters. Therefore, a reliable and inexpensive procedure for parameters identification of this model is on demand. In the view of potential improvements proposed in a recent work on soft computing methods, a new procedure based on artificial neural networks .
dcterms:title
Microplane Model Parameters Estimation Using Soft Computing Methods Určení parametrů mikroploškového modelu pomocí metod umělé inteligence Microplane Model Parameters Estimation Using Soft Computing Methods
skos:prefLabel
Microplane Model Parameters Estimation Using Soft Computing Methods Určení parametrů mikroploškového modelu pomocí metod umělé inteligence Microplane Model Parameters Estimation Using Soft Computing Methods
skos:notation
RIV/68407700:21110/04:01099173!RIV/2005/MSM/211105/N
n5:strany
536 ; 539
n5:aktivita
n19:Z
n5:aktivity
Z(MSM 210000003)
n5:dodaniDat
n17:2005
n5:domaciTvurceVysledku
n11:9081429 n11:4695046
n5:druhVysledku
n9:D
n5:duvernostUdaju
n15:S
n5:entitaPredkladatele
n21:predkladatel
n5:idSjednocenehoVysledku
573499
n5:idVysledku
RIV/68407700:21110/04:01099173
n5:jazykVysledku
n8:eng
n5:klicovaSlova
Concrete; Finite element method; Genetic algorithms; Inverse problems; Microplane model; Neural network
n5:klicoveSlovo
n6:Genetic%20algorithms n6:Concrete n6:Neural%20network n6:Finite%20element%20method n6:Inverse%20problems n6:Microplane%20model
n5:kontrolniKodProRIV
[4343C371AAC2]
n5:mistoKonaniAkce
Bled
n5:mistoVydani
Ljubljana
n5:nazevZdroje
Multi-physics and Multi-scale Computer Models in Non-linear Analysis and Optimal Design of Engineering Structures Under Extreme Conditions: Proceedings of NATO Advanced Research Worshop
n5:obor
n12:JN
n5:pocetDomacichTvurcuVysledku
2
n5:pocetTvurcuVysledku
3
n5:rokUplatneniVysledku
n17:2004
n5:tvurceVysledku
Lepš, Matěj Zeman, Jan Kučerová, Anna
n5:typAkce
n13:WRD
n5:zahajeniAkce
2004-06-13+02:00
n5:zamer
n7:MSM%20210000003
s:numberOfPages
4
n14:hasPublisher
University of Ljubljana
n10:isbn
961-6167-60-X
n16:organizacniJednotka
21110