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A Hierarchical A-Posteriori Error Estimator for the Reduced Basis Method

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      Abstract

      We present an online-efficient hierarchical a-posteriori error estimator for the Reduced Basis Method (RBM), which uses the difference of two reduced approximations of different accuracy to estimate the true error of a reduced approximation. Effectivity as well as performance are investigated, especially for those cases where the inf-sup constant has small values and/or is hard to compute numerically.

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      Affiliations
      [1 ]Institute for Numerical Mathematics, Ulm University
      [2 ]Applied Mathematics, University of Münster
      [* ]Correspondence: stefan.hain@ 123456uni-ulm.de
      Journal
      ScienceOpen Posters
      ScienceOpen
      27 April 2018
      10.14293/P2199-8442.1.SOP-MATH.THIDBV.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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