ArticleComputational mechanics2019
Performance of preconditioned iterative linear solvers for cardiovascular simulations in rigid and deformable vessels.
Article in Computational mechanics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Assessment of Aortic Dissection Remodeling With Patient-Specific Fluid-Structure Interaction Models.IEEE transactions on bio-medical engineering · 2025Article
- A Modular Framework for Implicit 3D-0D Coupling in Cardiac Mechanics.Computer methods in applied mechanics and engineering · 2024Article
- Fluid-structure interaction simulation of tissue degradation and its effects on intra-aneurysm hemodynamics.Biomechanics and modeling in mechanobiology · 2022Article
- Geometric Uncertainty in Patient-Specific Cardiovascular Modeling with Convolutional Dropout Networks.Computer methods in applied mechanics and engineering · 2021Article
- The effects of clinically-derived parametric data uncertainty in patient-specific coronary simulations with deformable walls.International journal for numerical methods in biomedical engineering · 2020Article
- Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics.Computer methods in applied mechanics and engineering · 2020Article
- MULTIFIDELITY ESTIMATORS FOR CORONARY CIRCULATION MODELS UNDER CLINICALLY INFORMED DATA UNCERTAINTY.International journal for uncertainty quantification · 2020Article
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Authors and funding
3 authors.
Funding
Abstract
Computing the solution of linear systems of equations is invariably the most time consuming task in the numerical solutions of PDEs in many fields of computational science. In this study, we focus on the numerical simulation of cardiovascular hemodynamics with rigid and deformable walls, discretized in space and time through the variational multiscale finite element method. We focus on three approaches: the problem agnostic generalized minimum residual (GMRES) and stabilized bi-conjugate gradient (BICGS) methods, and a recently proposed, problem specific, bi-partitioned (BIPN) method. We also perform a comparative analysis of several preconditioners, including diagonal, block-diagonal, incomplete factorization, multigrid, and resistance based methods. Solver performance and matrix characteristics (diagonal dominance, symmetry, sparsity, bandwidth and spectral properties) are first examined for an idealized cylindrical geometry with physiologic boundary conditions and then successively tested on several patient-specific anatomies representative of realistic cardiovascular simulation problems. Incomplete factorization preconditioners provide the best performance and results in terms of both strong and weak scalability. The BIPN method was found to outperform other methods in patient-specific models with rigid walls. In models with deformable walls, BIPN was outperformed by BICG with diagonal and Incomplete LU preconditioners.
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