Visual analysis of flow and diffusion of hemolytic agents and hematomas

The elimination of intracranial hematomas has received widespread attention and the interactions between hemolytic agents and hematomas have become a hot research topic. In this study, we used the Navier-Stokes equation to describe the flow control equation for hemolytic agents in a tube and used Fick’s law and the Maxwell-Stefan diffusion theory to describe the diffusion and mass transfer of hemolytic agents and hematomas. The physical fields and initial boundary conditions were set according to the parametric properties of the fluid and drainage tube. The COMSOL Multiphysics software was used to simulate the streamline distribution of hemolytic agents in a bifurcated drainage tube. Additionally, the diffusion behaviors of the hemolytic agents into hematomas were simulated and visual analysis of coupled multiphysics was performed to realize the digitization and visualization of engineering fluid problems and contribute to the field of medical engineering.

[1]  S. N. Ashrafizadeh,et al.  Mass transfer simulation of nanofiltration membranes for electrolyte solutions through generalized Maxwell-Stefan approach , 2015, Korean Journal of Chemical Engineering.

[2]  Zou Lin Real-Time Approach for Dynamic Liquid Simulation Using Semi-Lagrangian , 2013 .

[3]  Jincai Chang,et al.  Research on a bifurcation location algorithm of a drainage tube based on 3D medical images , 2020, Visual Computing for Industry, Biomedicine, and Art.

[4]  Sedat Yayla,et al.  Numerical investigation of coalescing plate system to understand the separation of water and oil in water treatment plant of petroleum industry , 2017 .

[5]  AUBREY BURSTALL,et al.  History of Hydraulics , 1973, Nature.

[6]  Werner Lehnert,et al.  Modelling of gas transport phenomena in SOFC anodes , 2000 .

[7]  Francesco Salvarani,et al.  A mathematical and numerical analysis of the Maxwell-Stefan diffusion equations , 2012 .

[8]  Takayuki Itoh,et al.  Streamline pair selection for comparative flow field visualization , 2020, Vis. Comput. Ind. Biomed. Art.

[9]  D. Birchall,et al.  Computational Fluid Dynamics , 2020, Radial Flow Turbocompressors.

[10]  Maziar Arjomandi,et al.  Visualization of the flow structure in a vortex tube , 2011 .

[11]  T. Ramazanov,et al.  Thermodynamics and statistical physics of quasiparticles within the quark–gluon plasma model , 2019, Modern Physics Letters A.

[12]  Three-Dimensional Coupling Compact Finite Difference Methods for Navier-Stokes Equations , 2007 .

[13]  F. Sharipov Gaseous mixtures in vacuum systems and microfluidics , 2013 .

[14]  John David Anderson,et al.  A history of aerodynamics and its impact on flying machines , 1997 .

[15]  S. Travis Waller,et al.  In-depth analysis of traffic congestion using computational fluid dynamics (CFD) modeling method , 2011 .

[16]  P. Saracco,et al.  On Fick’s law in asymptotic transport theory , 2019, The European Physical Journal Plus.

[17]  Yue Qi,et al.  Real-Time Approach for Dynamic Liquid Simulation Using Semi-Lagrangian: Real-Time Approach for Dynamic Liquid Simulation Using Semi-Lagrangian , 2014 .

[18]  Roger D. Launius,et al.  A History of Aerodynamics and Its Impact on Flying Machines , 1999 .

[19]  Dieter Bothe,et al.  On the Maxwell-Stefan Approach to Multicomponent Diffusion , 2010, 1007.1775.

[20]  Ansgar Jüngel,et al.  Analysis of an Incompressible Navier–Stokes–Maxwell–Stefan System , 2013, 1310.3376.