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'.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Non-intrusive and semi-intrusive uncertainty quantification of a multiscale in-stent restenosis model
    Ye, Dongwei
    Nikishova, Anna
    Veen, Lourens
    Zun, Pavel
    Hoekstra, Alfons G.
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2021, 214
  • [2] Uncertainty Quantification of a Multiscale Model for In-Stent Restenosis
    Anna Nikishova
    Lourens Veen
    Pavel Zun
    Alfons G. Hoekstra
    [J]. Cardiovascular Engineering and Technology, 2018, 9 : 761 - 774
  • [3] Uncertainty Quantification of a Multiscale Model for In-Stent Restenosis
    Nikishova, Anna
    Veen, Lourens
    Zun, Pavel
    Hoekstra, Alfons G.
    [J]. CARDIOVASCULAR ENGINEERING AND TECHNOLOGY, 2018, 9 (04) : 761 - 774
  • [4] Semi-intrusive uncertainty propagation for multiscale models
    Nikishova, Anna
    Hoekstra, Alfons G.
    [J]. JOURNAL OF COMPUTATIONAL SCIENCE, 2019, 35 : 80 - 90
  • [5] Uncertainty quantification of a three-dimensional in-stent restenosis model with surrogate modelling
    Ye, Dongwei
    Zun, Pavel
    Krzhizhanovskaya, Valeria
    Hoekstra, Alfons G.
    [J]. JOURNAL OF THE ROYAL SOCIETY INTERFACE, 2022, 19 (187)
  • [6] Towards a Complex Automata Multiscale Model of In-Stent Restenosis
    Caiazzo, Alfonso
    Evans, David
    Falcone, Jean-Lue
    Hegewald, Jan
    Lorenz, Eric
    Stahl, Bernd
    Wang, Dinan
    Bernsdorf, Joerg
    Chopard, Bastien
    Gunn, Julian
    Hose, Rod
    Krafczyk, Manfred
    Lawford, Patricia
    Smallwood, Rod
    Walker, Dawn
    Hoekstra, Alfons G.
    [J]. COMPUTATIONAL SCIENCE - ICCS 2009, PART I, 2009, 5544 : 705 - 714
  • [7] Semi-intrusive multivariable model invalidation
    Kammer, LC
    Gorinevsky, D
    Dumont, GA
    [J]. AUTOMATICA, 2003, 39 (08) : 1461 - 1467
  • [8] A semi-intrusive deterministic approach to uncertainty quantification in non-linear fluid flow problems
    Abgrall, Remi
    Congedo, Pietro Marco
    [J]. JOURNAL OF COMPUTATIONAL PHYSICS, 2013, 235 : 828 - 845
  • [9] Semi-intrusive approach for stiffness and strength topology optimization under uncertainty
    Steltner, Kai
    Pedersen, Claus B. W.
    Kriegesmann, Benedikt
    [J]. OPTIMIZATION AND ENGINEERING, 2023, 24 (03) : 2181 - 2211
  • [10] Semi-intrusive approach for stiffness and strength topology optimization under uncertainty
    Kai Steltner
    Claus B. W. Pedersen
    Benedikt Kriegesmann
    [J]. Optimization and Engineering, 2023, 24 : 2181 - 2211