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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Nikishova, A., Veen, L., Zun, P., & Hoekstra, A. G. (2019). Semi-intrusive multiscale metamodelling uncertainty quantification with application to a model of in-stent restenosis. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 377(2142). https://doi.org/10.1098/rsta.2018.0154

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