Reduced order models for fluid-structure interaction problems with applications in haemodynamics
Claudia M. Colciago, Simone Deparis

TL;DR
This paper introduces a two-level reduced order modeling approach combining mathematical reformulation and numerical techniques to enable fast, accurate simulations of fluid-structure interactions in large arteries, significantly reducing computational costs.
Contribution
The paper presents a novel combined reduction method using proper orthogonal decomposition and greedy algorithms for efficient haemodynamics simulations.
Findings
Achieved three orders of magnitude CPU time reduction.
Validated the method on realistic haemodynamics problems.
Demonstrated accurate results with reduced computational effort.
Abstract
This paper deals with fast simulations of the haemodynamics in large arteries by considering a reduced model of the associated fluid-structure interaction problem, which in turn allows an additional reduction in terms of the numerical discretisation. The resulting method is both accurate and computationally cheap. This goal is achieved by means of two levels of reduction: first, we describe the model equations with a reduced mathematical formulation which allows to write the fluid-structure interaction problem as a Navier-Stokes system with non-standard boundary conditions; second, we employ numerical reduction techniques to further and drastically lower the computational costs. The numerical reduction is obtained coupling two well-known techniques: the proper orthogonal decomposition and the reduced basis method, in particular the greedy algorithm. We start by reducing the numerical…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsModel Reduction and Neural Networks · Computational Fluid Dynamics and Aerodynamics · Advanced Numerical Methods in Computational Mathematics
