On the Impact of Fluid Structure Interaction in Blood Flow Simulations

Failer, Lukas; Minakowski, Piotr; Richter, Thomas

doi:10.1007/s10013-020-00456-6

Cited by 14 publications

(3 citation statements)

References 43 publications

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“…The transition to more realistic 3d problems will substantially increase the effort in both parts, finite elements and particle dynamics. For the Navier-Stokes simulation it has been demonstrated that realistic 3d blood flow situations can be handled in reasonable time, see [8,9,10]. If the number of particles is to be substantially increased, the neural network coupling for estimating hemodynamic coefficients should be realized in a high performance package such as LAMMPS [28] that allows for an efficient GPU implementation.…”

Section: Configuration Of the Test Casementioning

confidence: 99%

A finite element / neural network framework for modeling suspensions of non-spherical particles. Concepts and medical applications

Minakowska,

Richter,

Sager

2020

Preprint

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An accurate prediction of the translational and rotational motion of particles suspended in a fluid is only possible if a complete set of correlations for the force coefficients of fluid-particle interaction is known. The present study is thus devoted to the derivation and validation of a new framework to determine the drag, lift, rotational and pitching torque coefficients for different non-spherical particles in a fluid flow. The motivation for the study arises from medical applications, where particles may have an arbitrary and complex shape. Here, it is usually not possible to derive accurate analytical models for predicting the different hydrodynamic forces. However, considering for example the various components of blood, their shape takes an important role in controlling several body functions such as control of blood viscosity or coagulation. Therefore, the presented model is designed to be applicable to a broad range of shapes. Another important feature of the suspensions occurring in medical and biological applications is the high number of particles.The modelling approach we propose can be efficiently used for simulations of solid-liquid suspensions with numerous particles. Based on resolved numerical simulations of prototypical particles we generate data to train a neural network which allows us to quickly estimate the hydrodynamic forces experienced by a specific particle immersed in a fluid.

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Section: Configuration Of the Test Casementioning

confidence: 99%

A finite element / neural network framework for modeling suspensions of non-spherical particles. Concepts and medical applications

Minakowska,

Richter,

Sager

2020

Preprint

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“…Dong et al [ 23 ] presented a correlation between the angulation of the coronary artery branches and the local mechanical and hemodynamic stresses at the artery bifurcation using FSI analysis. Additionally, Failer et al [ 24 ] investigated the impact of using FSI to simulate blood flow in simple stenotic geometry. Zouggari et al [ 25 ] investigated the influence of plaques on the WSS distribution using FSI analysis and CFD simulations.…”

Section: Introductionmentioning

confidence: 99%

Influence of Rigid–Elastic Artery Wall of Carotid and Coronary Stenosis on Hemodynamics

et al. 2022

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Cardiovascular system abnormalities can result in serious health complications. By using the fluid–structure interaction (FSI) procedure, a comprehensive realistic approach can be employed to accurately investigate blood flow coupled with arterial wall response. The hemodynamics was investigated in both the coronary and carotid arteries based on the arterial wall response. The hemodynamics was estimated based on the numerical simulation of a comprehensive three-dimensional non-Newtonian blood flow model in elastic and rigid arteries. For stenotic right coronary artery (RCA), it was found that the maximum value of wall shear stress (WSS) for the FSI case is higher than the rigid wall. On the other hand, for the stenotic carotid artery (CA), it was found that the maximum value of WSS for the FSI case is lower than the rigid wall. Moreover, at the peak systole of the cardiac cycle (0.38 s), the maximum percentage of arterial wall deformation was found to be 1.9%. On the other hand, for the stenotic carotid artery, the maximum percentage of arterial wall deformation was found to be 0.46%. A comparison between FSI results and those obtained by rigid wall arteries is carried out. Findings indicate slight differences in results for large-diameter arteries such as the carotid artery. Accordingly, the rigid wall assumption is plausible in flow modeling for relatively large diameters such as the carotid artery. Additionally, the FSI approach is essential in flow modeling in small diameters.

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“…Particulate flows, particle settling and in the broader sense fluid solid interactions play a major role in applications, ranging from medicine [8,34,9] and biology [25] to industry [2,39].…”

Section: Introductionmentioning

confidence: 99%

Error analysis for a parabolic PDE model problem on a coupled moving domain in a fully Eulerian framework

Wahl¹,

Richter²

2021

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We introduce an unfitted finite element method with Lagrange-multipliers to study an Eulerian timestepping scheme for moving domain problems applied to a model problem where the domain motion is implicit to the problem. We consider the heat equation as the partial differential equation (PDE) in the bulk domain, and the domain motion is described by an ordinary differential equation (ODE), coupled to the bulk partial differential equation through the transfer of forces at the moving interface. The discretisation is based on an unfitted finite element discretisation on a time-independent mesh. The method-of-lines time discretisation is enabled by an implicit extension of the bulk solution through additional stabilisation, as introduced by Lehrenfeld & Olshanskii (ESAIM: M2AN, 53:585-614, 2019). The analysis of the coupled problem relies on the Lagrange-multiplier formulation, the fact that the Lagrange-multiplier solution is equal to the normal stress at the interface and that the motion of the interface is given through rigid-body motion. This paper covers the complete stability analysis of the method and an error estimate in the energy norm. This includes the dynamic error in the domain motion resulting from the discretised ODE and the forces from the discretised PDE. To the best of our knowledge this is the first error analysis of this type of coupled moving domain problem in a fully Eulerian framework. Numerical examples illustrate the theoretical results.

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On the Impact of Fluid Structure Interaction in Blood Flow Simulations

Cited by 14 publications

References 43 publications

A finite element / neural network framework for modeling suspensions of non-spherical particles. Concepts and medical applications

A finite element / neural network framework for modeling suspensions of non-spherical particles. Concepts and medical applications

Influence of Rigid–Elastic Artery Wall of Carotid and Coronary Stenosis on Hemodynamics

Error analysis for a parabolic PDE model problem on a coupled moving domain in a fully Eulerian framework

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