0
Research Papers

An Approach for Assessing Turbulent Flow Damage to Blood in Medical Devices

[+] Author and Article Information
Mesude Ozturk

Department of Chemical, Biological,
and Materials Engineering,
Sarkeys Energy Center Room T301,
University of Oklahoma,
100 East Boyd Street,
Norman, OK 73019
e-mail: mozturk@ou.edu

Dimitrios V. Papavassiliou

Department of Chemical, Biological, and
Materials Engineering,
Sarkeys Energy Center Room T301,
University of Oklahoma,
100 East Boyd Street,
Norman, OK 73019
e-mail: dvpapava@ou.edu

Edgar A. O'Rear

Department of Chemical, Biological, and
Materials Engineering,
Sarkeys Energy Center Room T301,
University of Oklahoma Biomedical
Engineering Center,
100 East Boyd Street,
Norman, OK 73019
e-mail: eorear@ou.edu

Manuscript received June 27, 2016; final manuscript received September 30, 2016; published online November 4, 2016. Assoc. Editor: Keefe B. Manning.

J Biomech Eng 139(1), 011008 (Nov 04, 2016) (8 pages) Paper No: BIO-16-1268; doi: 10.1115/1.4034992 History: Received June 27, 2016; Revised September 30, 2016

In this work, contributing factors for red blood cell (RBC) damage in turbulence are investigated by simulating jet flow experiments. Results show that dissipative eddies comparable or smaller in size to the red blood cells cause hemolysis and that hemolysis corresponds to the number and, more importantly, the surface area of eddies that are associated with Kolmogorov length scale (KLS) smaller than about 10 μm. The size distribution of Kolmogorov scale eddies is used to define a turbulent flow extensive property with eddies serving as a means to assess the turbulence effectiveness in damaging cells, and a new hemolysis model is proposed. This empirical model is in agreement with hemolysis results for well-defined systems that exhibit different exposure times and flow conditions, in Couette flow viscometer, capillary tube, and jet flow experiments.

FIGURES IN THIS ARTICLE
<>
Copyright © 2017 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Fig. 1

Mean velocity profiles for k–ε and k–ω SST turbulence models. (a) Mean axial velocity profile as a function of radial distance for k–ε turbulence model at different x/d locations. (b) Mean axial velocity profile as a function of radial distance for k–ω SST turbulence model at different x/d locations. The velocity for both the k–ε and k–ω SST models was 20.39 m/s.

Grahic Jump Location
Fig. 2

Variations of KLS values and regions of smaller KLS values. (a) Changes of KLS values with increasing axial distance in the syringe starting from jet exit (x/d = 0 with d as the needle bore diameter) to the syringe end (x/d = 80) for the highest velocity experiment. (b) Regions are shown from KLS ≤ 5 to KLS ≤ 10 in syringe for the highest velocity experiment.

Grahic Jump Location
Fig. 3

KLS distributions and relation between KLS distributions and hemolysis. (a) The distribution of KLS in the jet for different mean jet velocities. (b) Relation between KLS distributions and hemolysis up to specific KLS values. Each data point corresponds to observed hemolysis reported in the experiment.

Grahic Jump Location
Fig. 4

Relation between hemolysis and eddy surface area. Hemolysis as a function of eddy surface area in jet experiments for even values of KLS (experimental data from Forstrom [28]). Each data point corresponds to observed hemolysis reported in the experiment, while the eddy area for the specified KLS size is as found from simulation of that experiment. The lines are plotted to guide the eye over the data points. It is seen that when hemolysis is plotted as a function of the area of eddies the line shape changes as diameter increases from 8 μm to 10 μm, with the lines curving back and tending to vertical for larger eddies, suggesting no effect on hemolysis.

Grahic Jump Location
Fig. 5

Relation between hemolysis and cumulative eddy surface area. Hemolysis data from Forstrom's jet experiment plotted as a function of cumulative eddy surface area. Each data point corresponds to observed hemolysis from experiment, while the total eddy area up to the specified KLS size is found from simulation of that experiment. The data almost collapse for eddies larger than 10 μm.

Grahic Jump Location
Fig. 6

Relation between cumulative eddy number and hemolysis. Hemolysis as a function of cumulative eddy number. Each data point corresponds to observed hemolysis from experiment, while the total eddy number up to the specified KLS size is found from simulation.

Grahic Jump Location
Fig. 7

Hemolysis calculations of our model. Comparison of experimental hemolysis and hemolysis from our model (Eq. (2) and Table 3) in jet flow (left panel), capillary tube (center panel), and Couette viscometer (right panel).

Grahic Jump Location
Fig. 8

Hemolysis calculations of our model. Comparison of experimental hemolysis and hemolysis from our model (Eq. (2) and Table 4) with separate fits for jet flow (left panel), capillary tube (center panel), and Couette viscometer (right panel).

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In