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Parameter estimation with model order reduction and global measurements
Author(s) -
Lukassen Axel Ariaan,
Kiehl Martin
Publication year - 2017
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201710354
Subject(s) - snapshot (computer storage) , reduction (mathematics) , estimation theory , partial differential equation , mathematics , computer science , phase (matter) , elliptic partial differential equation , mathematical optimization , algorithm , mathematical analysis , physics , geometry , quantum mechanics , operating system
We present a new method for parameter estimation for elliptic partial differential equations. Parameter estimation requires the evaluation of the partial differential equation for many different parameter sets. Therefore, model order reduction is reasonable. Model order reduction is composed of an offline phase and an online phase. In the offline phase the reduced model is constructed using snapshots. In this paper we use the given measurement as only snapshot. Hence, the computational costs of the offline phase are reduced. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)