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

被引:14
|
作者
Nikishova, A. [1 ]
Veen, L. [2 ]
Zun, P. [1 ,3 ]
Hoekstra, A. G. [1 ,3 ]
机构
[1] Univ Amsterdam, Computat Sci Lab, Inst Informat, Fac Sci, NL-1098 XH Amsterdam, Netherlands
[2] Netherlands eSci Ctr, NL-1098 XG Amsterdam, Netherlands
[3] ITMO Univ, St Petersburg 197101, Russia
基金
欧盟地平线“2020”; 俄罗斯科学基金会;
关键词
in-stent restenosis model; uncertainty quantification; semi-intrusive methods; multiscale modelling;
D O I
10.1098/rsta.2018.0154
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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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页数:11
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