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Statements

Subject Item
n2:RIV%2F00216305%3A26110%2F13%3APU109087%21RIV15-GA0-26110___
rdf:type
skos:Concept n21:Vysledek
dcterms:description
Design Optimization methods' application in structural designing represents a suitable manner for efficient designs of practical problems. The optimization techniques' implementation into multi-physical softwares permits designers to utilize them in a wide range of engineering problems. These methods are usually based on modified mathematical programming techniques and/or their combinations to improve universality and robustness for various human and technical problems. The presented paper deals with the analysis of optimization methods and tools within the frame of one to three-dimensional strictly convex optimization problems, which represent a component of the Design Optimization module in the Ansys program. The First Order method, based on combination of steepest descent and conjugate gradient method, and Supbproblem Approximation method, which uses approximation of dependent variables' functions, accompanying with facilitation of Random, Sweep, Factorial and Gradient Tools, are analyzed, where in Design Optimization methods' application in structural designing represents a suitable manner for efficient designs of practical problems. The optimization techniques' implementation into multi-physical softwares permits designers to utilize them in a wide range of engineering problems. These methods are usually based on modified mathematical programming techniques and/or their combinations to improve universality and robustness for various human and technical problems. The presented paper deals with the analysis of optimization methods and tools within the frame of one to three-dimensional strictly convex optimization problems, which represent a component of the Design Optimization module in the Ansys program. The First Order method, based on combination of steepest descent and conjugate gradient method, and Supbproblem Approximation method, which uses approximation of dependent variables' functions, accompanying with facilitation of Random, Sweep, Factorial and Gradient Tools, are analyzed, where in
dcterms:title
Gradient vs. approximation design optimization techniques in low-dimensional convex problems Gradient vs. approximation design optimization techniques in low-dimensional convex problems
skos:prefLabel
Gradient vs. approximation design optimization techniques in low-dimensional convex problems Gradient vs. approximation design optimization techniques in low-dimensional convex problems
skos:notation
RIV/00216305:26110/13:PU109087!RIV15-GA0-26110___
n3:aktivita
n5:P
n3:aktivity
P(GAP104/11/0703)
n3:dodaniDat
n14:2015
n3:domaciTvurceVysledku
n20:3813290
n3:druhVysledku
n13:D
n3:duvernostUdaju
n19:S
n3:entitaPredkladatele
n11:predkladatel
n3:idSjednocenehoVysledku
76787
n3:idVysledku
RIV/00216305:26110/13:PU109087
n3:jazykVysledku
n10:eng
n3:klicovaSlova
constraints, Convex optimization, efficiency, FEM/FEA, First Order Method, robustness, Subproblem Approximation Method
n3:klicoveSlovo
n4:robustness n4:First%20Order%20Method n4:Subproblem%20Approximation%20Method n4:constraints n4:Convex%20optimization n4:FEM%2FFEA n4:efficiency
n3:kontrolniKodProRIV
[4AA71ACF94B6]
n3:mistoKonaniAkce
Rhodes
n3:mistoVydani
Neuveden
n3:nazevZdroje
ICNAAM 2013
n3:obor
n18:JM
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:projekt
n9:GAP104%2F11%2F0703
n3:rokUplatneniVysledku
n14:2013
n3:tvurceVysledku
Fedorik, Filip
n3:typAkce
n12:WRD
n3:zahajeniAkce
2013-09-21+02:00
s:numberOfPages
4
n15:hasPublisher
Neuveden
n17:isbn
978-0-7354-1184-5
n8:organizacniJednotka
26110