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      Semi-intrusive multiscale metamodelling uncertainty quantification with application to a model of in-stent restenosis

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          Abstract

          We explore the efficiency of a semi-intrusive uncertainty quantification (UQ) method for multiscale models as proposed by us in an earlier publication. We applied the multiscale metamodelling UQ method to a two-dimensional multiscale model for the wound healing response in a coronary artery after stenting (in-stent restenosis). The results obtained by the semi-intrusive method show a good match to those obtained by a black-box quasi-Monte Carlo method. Moreover, we significantly reduce the computational cost of the UQ. We conclude that the semi-intrusive metamodelling method is reliable and efficient, and can be applied to such complex models as the in-stent restenosis ISR2D model.

          This article is part of the theme issue ‘Multiscale modelling, simulation and computing: from the desktop to the exascale’.

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          Author and article information

          Journal
          Philos Trans A Math Phys Eng Sci
          Philos Trans A Math Phys Eng Sci
          RSTA
          roypta
          Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
          The Royal Society Publishing
          1364-503X
          1471-2962
          8 April 2019
          18 February 2019
          : 377
          : 2142 , Theme issue ‘Multiscale modelling, simulation and computing: from the desktop to the exascale’ compiled and edited by Alfons G. Hoekstra, Simon Portegies Zwart and Peter Coveney
          : 20180154
          Affiliations
          [1 ] Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam , 1098 XH Amsterdam, The Netherlands
          [2 ] Netherlands eScience Center, 1098 XG Amsterdam, The Netherlands
          [3 ] ITMO University , Saint Petersburg, 197101, Russia
          Author notes
          Author information
          http://orcid.org/0000-0003-4813-9282
          http://orcid.org/0000-0001-6176-1143
          http://orcid.org/0000-0002-3955-2449
          Article
          PMC6388010 PMC6388010 6388010 rsta20180154
          10.1098/rsta.2018.0154
          6388010
          30967038
          faf3af49-ba9f-421b-9f1e-b9f8ea8f2fb2
          © 2019 The Author(s)

          Published by the Royal Society. All rights reserved.

          History
          : 10 October 2018
          Funding
          Funded by: European Union Horizon 2020 research and innovation programme;
          Award ID: #800925 (VECMA project)
          Award ID: #671564 (ComPat project)
          Funded by: The Russian Science Foundation;
          Award ID: #14-11-00826
          Funded by: Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organization for Science Research, NWO);
          Categories
          1003
          44
          50
          1008
          175
          Articles
          Research Article
          Custom metadata
          April 8, 2019

          multiscale modelling,semi-intrusive methods,in-stent restenosis model,uncertainty quantification

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