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Efficient Model Reduction in Non-linear Dynamics Using the Karhunen-Loève Expansion and Dual-Weighted-Residual Methods. - (Informatikbericht Nr. 2003-01)

Autor/en :

Meyer, Marcus
Matthies, Hermann G.

Institut / Verlag :

Institut für Wissenschaftliches Rechnen, 2003

Fakultät :

01 - Mathematik und Informatik

Freigeschaltet am :

31.01.2012

Dokumente :

PDF-Dokument

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Umfang :

30 S.

Sprache :

englisch

Kurzfassung :

We look at the task of computing the time-evolution of a non-linear system for a long time, in our case under random external influences. Our specific example is the fatigue evaluation of a wind turbine. To facilitate such a computation, we look at a reduction of the computational effort by projecting everything on a low-dimensional basis. In this case we take the Karhunen-Loève basis generated from running the model a little while under the random loading. It is important that we error which is caused by this reduction process can be controlled. We estimate the error by dual or adjoint methods. This in turn allows the process of model reduction to be performed adaptively.

Schlagwörter :

model reduction, non-linear dynamics, Karhunen-Loève expansion, error estimates, dual-weighted-residual-methods

Sachgebiet :

510 Mathematik

Typ :

Publikationen der TU Braunschweig

Format :

Text/Dokument

URN:NBN :

urn:nbn:de:gbv:084-12013115229

Zitierfähige URL :

http://www.digibib.tu-bs.de/?docid=00001380