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

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.

Content

Author and article information

Journal

Title: ScienceOpen Posters

Publisher: ScienceOpen

Publication date (Electronic): 27 April 2018

Affiliations

[1 ]Institute for Numerical Mathematics, Ulm University

[2 ]Applied Mathematics, University of Münster

[* ]Correspondence: stefan.hain@ 123456uni-ulm.de

Article

DOI: 10.14293/P2199-8442.1.SOP-MATH.THIDBV.v1

SO-VID: caedfd0b-784c-42f5-ba0f-e320a7238894

License:

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.

History

ScienceOpen disciplines: Applied mathematics,Applications,Statistics,Data analysis,Mathematics,Mathematical modeling & Computation

Keywords: A-Posteriori Error Estimator,Reduced Basis Method,Hierarchical Error Estimator