[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
L Pegolotti, MR Pfaller, NL Rubio, K Ding… - Computers in Biology …, 2024 - Elsevier
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
Prediction of complex fluid flows from sparse and noisy sensor measurements is widely
applied to many engineering fields. In the present study, a novel compressed sensing …
applied to many engineering fields. In the present study, a novel compressed sensing …
Automated generation of 0D and 1D reduced‐order models of patient‐specific blood flow
Abstract Three‐dimensional (3D) cardiovascular fluid dynamics simulations typically require
hours to days of computing time on a high‐performance computing cluster. One …
hours to days of computing time on a high‐performance computing cluster. One …
A one-shot overlapping 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-overlapping 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
N Discacciati, JS Hesthaven - International Journal for …, 2023 - Wiley Online Library
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 …