scholarly journals A weighted least-squares finite element method for Phan-Thien–Tanner viscoelastic fluid

2016 ◽  
Vol 436 (1) ◽  
pp. 66-78 ◽  
Author(s):  
Shaoling Zhou ◽  
Lei Hou
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Least Squares ◽  
Viscoelastic Fluid ◽  
Weighted Least Squares ◽  
Element Method

scholarly journals Weighted Least-Squares Finite Element Method for Cardiac Blood Flow Simulation with Echocardiographic Data

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Fei Wei ◽  
John Westerdale ◽  
Eileen M. McMahon ◽  
Marek Belohlavek ◽  
Jeffrey J. Heys
Keyword(s):  
Experimental Data ◽  
Finite Element Method ◽  
Finite Element ◽  
Blood Flow ◽  
Left Ventricle ◽  
Least Squares ◽  
Weighted Least Squares ◽  
Measurement Techniques ◽  
Test Problems ◽  
Element Method

As both fluid flow measurement techniques and computer simulation methods continue to improve, there is a growing need for numerical simulation approaches that can assimilate experimental data into the simulation in a flexible and mathematically consistent manner. The problem of interest here is the simulation of blood flow in the left ventricle with the assimilation of experimental data provided by ultrasound imaging of microbubbles in the blood. The weighted least-squares finite element method is used because it allows data to be assimilated in a very flexible manner so that accurate measurements are more closely matched with the numerical solution than less accurate data. This approach is applied to two different test problems: a flexible flap that is displaced by a jet of fluid and blood flow in the porcine left ventricle. By adjusting how closely the simulation matches the experimental data, one can observe potential inaccuracies in the model because the simulation without experimental data differs significantly from the simulation with the data. Additionally, the assimilation of experimental data can help the simulation capture certain small effects that are present in the experiment, but not modeled directly in the simulation.

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