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3D Fluid-Structure Interaction Simulation of Aortic Valves Using a Unified Continuum ALE FEM Model

Overview of attention for article published in Frontiers in Physiology, April 2018
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  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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1 X user
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1 patent

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118 Mendeley
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Title
3D Fluid-Structure Interaction Simulation of Aortic Valves Using a Unified Continuum ALE FEM Model
Published in
Frontiers in Physiology, April 2018
DOI 10.3389/fphys.2018.00363
Pubmed ID
Authors

Jeannette H. Spühler, Johan Jansson, Niclas Jansson, Johan Hoffman

Abstract

Due to advances in medical imaging, computational fluid dynamics algorithms and high performance computing, computer simulation is developing into an important tool for understanding the relationship between cardiovascular diseases and intraventricular blood flow. The field of cardiac flow simulation is challenging and highly interdisciplinary. We apply a computational framework for automated solutions of partial differential equations using Finite Element Methods where any mathematical description directly can be translated to code. This allows us to develop a cardiac model where specific properties of the heart such as fluid-structure interaction of the aortic valve can be added in a modular way without extensive efforts. In previous work, we simulated the blood flow in the left ventricle of the heart. In this paper, we extend this model by placing prototypes of both a native and a mechanical aortic valve in the outflow region of the left ventricle. Numerical simulation of the blood flow in the vicinity of the valve offers the possibility to improve the treatment of aortic valve diseases as aortic stenosis (narrowing of the valve opening) or regurgitation (leaking) and to optimize the design of prosthetic heart valves in a controlled and specific way. The fluid-structure interaction and contact problem are formulated in a unified continuum model using the conservation laws for mass and momentum and a phase function. The discretization is based on an Arbitrary Lagrangian-Eulerian space-time finite element method with streamline diffusion stabilization, and it is implemented in the open source software Unicorn which shows near optimal scaling up to thousands of cores. Computational results are presented to demonstrate the capability of our framework.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 118 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 24%
Student > Master 16 14%
Researcher 13 11%
Student > Bachelor 12 10%
Student > Doctoral Student 8 7%
Other 10 8%
Unknown 31 26%
Readers by discipline Count As %
Engineering 45 38%
Medicine and Dentistry 12 10%
Mathematics 7 6%
Computer Science 3 3%
Psychology 2 2%
Other 10 8%
Unknown 39 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 July 2022.
All research outputs
#7,240,812
of 22,880,230 outputs
Outputs from Frontiers in Physiology
#3,492
of 13,671 outputs
Outputs of similar age
#115,344
of 296,311 outputs
Outputs of similar age from Frontiers in Physiology
#151
of 491 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 13,671 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 296,311 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 491 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.