The platform will undergo maintenance on Sep 14 at about 7:45 AM EST and will be unavailable for approximately 2 hours.
2021
DOI: 10.3390/chemengineering5030040
|View full text |Cite
|
Sign up to set email alerts
|

Modelling Particle Agglomeration on through Elastic Valves under Flow

Abstract: This work proposes a model of particle agglomeration in elastic valves replicating the geometry and the fluid dynamics of a venous valve. The fluid dynamics is simulated with Smooth Particle Hydrodynamics, the elastic leaflets of the valve with the Lattice Spring Model, while agglomeration is modelled with a 4-2 Lennard-Jones potential. All the models are combined together within a single Discrete Multiphysics framework. The results show that particle agglomeration occurs near the leaflets, supporting the hypo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
7
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
4
1

Relationship

2
3

Authors

Journals

citations
Cited by 5 publications
(7 citation statements)
references
References 39 publications
0
7
0
Order By: Relevance
“…Fluid inside the colon: SPH particles (liquid) Membrane: LSM particles (solid) "drain tank" "DCMDT" Further details on the DT and the simulation parameters are given in Section 2.2.2. For a general overview on the DMP theory and how it can be applied to a variety of applications such as biological flows and/or fluid-structure interactions [3,5,[21][22][23][24][25][26][27], solidification and dissolution [28][29][30], machine learning [31,32], and composite materials [33], the reader can refer to the available literature (e.g., DMP: [17,18], SPH: [34], LSM: [35][36][37]). For technical details and how it is applied to the large intestine, the reader is referred to Refs.…”
Section: Haustrum/ Sectionmentioning
confidence: 99%
“…Fluid inside the colon: SPH particles (liquid) Membrane: LSM particles (solid) "drain tank" "DCMDT" Further details on the DT and the simulation parameters are given in Section 2.2.2. For a general overview on the DMP theory and how it can be applied to a variety of applications such as biological flows and/or fluid-structure interactions [3,5,[21][22][23][24][25][26][27], solidification and dissolution [28][29][30], machine learning [31,32], and composite materials [33], the reader can refer to the available literature (e.g., DMP: [17,18], SPH: [34], LSM: [35][36][37]). For technical details and how it is applied to the large intestine, the reader is referred to Refs.…”
Section: Haustrum/ Sectionmentioning
confidence: 99%
“…In a recently published elegant study ( 28 ), authors demonstrated the initial formation of fibrin gel, followed by accumulation and activation of procoagulant platelets and thrombus growth in a microfluidics device, which combines biological (blood, tissue factor) and hemodynamic factors (valve leaflets steadily fixed at different angles) inducing thrombosis in a vein. We have recently reported a new microfluidics model with mobile valves and a pulsatile flow pattern typical for veins ( 29 ) and was validated by our in silico model ( 30 ). In the present study, we have developed a method to grow human endothelial cells on the entire surface of the channel including valve leaflets (Cellular Elastic Vein Valve model, CEVV chip).…”
Section: Introductionmentioning
confidence: 70%
“…This study uses a simulation technique called Discrete Multiphysics (DMP) (Alexiadis, 2015(Alexiadis, , 2014. DMP is a mesh-free technique that uses computational particles instead of computational grids and has been successfully used to model human organs: Ariane et al (2017aAriane et al ( , 2018aAriane et al ( , 2018bAriane et al ( , 2017b, Baksamawi et al (2021), Mohammed et al (2020Mohammed et al ( , 2021, Alexiadis (2015bAlexiadis ( , 2015aAlexiadis ( , 2019, Alexiadis et al (2017), and Schütt et al (2021, 2022. It couples particle-based methods such as Smoothed Particle Hydrodynamics (SPH), Lattice Spring Model (LSM), and Discrete Element Method (DEM) and Peridynamics (Sanfilipo et al, 2021).…”
Section: Modelling Approachmentioning
confidence: 99%