Abstract
Tensors are the natural mathematical objects to describe physical quantities that evolve over multiple independent variables. This paper considers the computation of empirical projection spaces by decomposing a tensor that can be associated with measured data. We show how these projection spaces can be used to derive reduced order models. The procedure is applied to a two-dimensional heat diffusion problem and a problem in fluid flow dynamics.
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van Belzen, F., Weiland, S. (2010). Efficient Simulation of Large-scale Dynamical Systems Using Tensor Decompositions. In: Roos, J., Costa, L. (eds) Scientific Computing in Electrical Engineering SCEE 2008. Mathematics in Industry(), vol 14. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12294-1_51
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DOI: https://doi.org/10.1007/978-3-642-12294-1_51
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Online ISBN: 978-3-642-12294-1
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