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[HTML][HTML] Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease
Physics-based computational models of the cardiovascular system are increasingly used to
simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and …
simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and …
Learning reduced-order models for cardiovascular simulations with graph neural networks
Reduced-order models based on physics are a popular choice in cardiovascular modeling
due to their efficiency, but they may experience loss in accuracy when working with …
due to their efficiency, but they may experience loss in accuracy when working with …
Unsteady flow prediction from sparse measurements by compressed sensing reduced order modeling
X Zhang, T Ji, F ** Schwarz method for component-based model reduction: application to nonlinear elasticity
We propose a component-based (CB) parametric model order reduction (pMOR) formulation
for parameterized nonlinear elliptic partial differential equations (PDEs) based on …
for parameterized nonlinear elliptic partial differential equations (PDEs) based on …
Localized model reduction for nonlinear elliptic partial differential equations: localized training, partition of unity, and adaptive enrichment
We propose a component-based (CB) parametric model order reduction (pMOR) formulation
for parameterized nonlinear elliptic partial differential equations. CB-pMOR is designed to …
for parameterized nonlinear elliptic partial differential equations. CB-pMOR is designed to …
A non-overlap** optimization-based domain decomposition approach to component-based model reduction of incompressible flows
We present a component-based model order reduction procedure to efficiently and
accurately solve parameterized incompressible flows governed by the Navier-Stokes …
accurately solve parameterized incompressible flows governed by the Navier-Stokes …
Localized model order reduction and domain decomposition methods for coupled heterogeneous systems
We propose a model order reduction technique to accurately approximate the behavior of
multi‐component systems without any a‐priori knowledge of the coupled model. In the …
multi‐component systems without any a‐priori knowledge of the coupled model. In the …
Where Do the Analytical Methods Stand in Cardiovascular Problems: An Overview of Blood Flow as a Biomechanical Problem in Arteriosclerosis
E Kayaalp Ata - Archives of Computational Methods in Engineering, 2024 - Springer
Complex problems require multidisciplinary studies. Cardiovascular diseases, which are
closely related to our health and have a very complex structure, attract the attention of many …
closely related to our health and have a very complex structure, attract the attention of many …
A physics-based machine learning technique rapidly reconstructs the wall-shear stress and pressure fields in coronary arteries
B Morgan, AR Murali, G Preston, YA Sima… - Frontiers in …, 2023 - frontiersin.org
With the global rise of cardiovascular disease including atherosclerosis, there is a high
demand for accurate diagnostic tools that can be used during a short consultation. In view of …
demand for accurate diagnostic tools that can be used during a short consultation. In view of …