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Adaptive Approximation of Shapes
by A. Buffa and R. Hiptmair and P. Panchal
(Report number 2020-60)
Abstract
We consider scalar-valued shape functionals on sets of shapes which are small
perturbations of a reference shape. The shapes are described by parameterizations and
their closeness is induced by a Hilbert space structure on the parameter domain.
We justify a heuristic for finding the best low-dimensional parameter subspace with
respect to uniformly approximating a given shape functional. We also propose an adaptive
algorithm for achieving a prescribed accuracy when representing the shape functional
with a small number of shape parameters.
Keywords: Model reduction, shape calculus, shape gradient, shape Hessian, low-rank approximation, power iteration
BibTeX@Techreport{BHP20_933, author = {A. Buffa and R. Hiptmair and P. Panchal}, title = {Adaptive Approximation of Shapes}, institution = {Seminar for Applied Mathematics, ETH Z{\"u}rich}, number = {2020-60}, address = {Switzerland}, url = {https://www.sam.math.ethz.ch/sam_reports/reports_final/reports2020/2020-60.pdf }, year = {2020} }
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