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      Adaptive POD-DEIM model reduction based on an improved error estimator

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          Abstract

          For reliable, efficient, rapid simulations of dynamical systems, a reduced order model (ROM) with certified accuracy is highly desirable. The ROM is derived from a full order model (FOM) through model reduction. In this work, we propose an adaptive approach for nonlinear model reduction by making use of a suitable output error estimator, thus enable the generation of a compact ROM, with appropriate balance between the state and nonlinear approximations.

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          Author and article information

          Journal
          ScienceOpen Posters
          ScienceOpen
          27 April 2018
          Affiliations
          [1 ]Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
          [* ]Correspondence: chellappa@ 123456mpi-magdeburg.mpg.de
          Article
          10.14293/P2199-8442.1.SOP-MATH.ENKDNC.v1
          Copyright © 2018

          This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

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