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Structural and Multidisciplinary Optimization
Erschienen in: Structural and Multidisciplinary Optimization 1/2015

01.01.2015 | INDUSTRIAL APPLICATION

Structure and fluid optimization of the guide vane blade with the decomposition of the optimization problem

verfasst von: Domen Stadler, Damjan Čelič

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 1/2015

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Abstract

The paper presents a new method for the fully automated decomposition of the optimization problem. The decomposition is performed on the space of the optimization input arguments. The method is firstly tested on the optimization of the mathematical functions. Afterwards, the decomposition method is used to optimize the geometry of a guide vane blade of a reversible water turbine. The objectives of the optimization are the maximal efficiency of the whole turbine and the minimal volume of a single blade with the condition that the blade remains undamaged during the normal operation of the turbine. The fluid analysis is performed with the use of the finite volume method, while the structural analysis is performed either with the finite element method or with the meshless method. The comparison of the two structural analysis methods shows that they have a different result sensitivity about the mesh distortion. A comparison of optima, obtained on the basis of both structural analysis methods, is made in order to assess the impact of the mesh distortion on results of the design optimization.
Vorheriger Artikel A new approach of preform design for forging of 3D blade based on evolutionary structural optimization
Nächster Artikel Determination of back-pressure profile for forward extrusion using sequential approximate optimization

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Metadaten
Titel
Structure and fluid optimization of the guide vane blade with the decomposition of the optimization problem
verfasst von
Domen Stadler
Damjan Čelič
Publikationsdatum
01.01.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Structural and Multidisciplinary Optimization / Ausgabe 1/2015
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-014-1122-y

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