Analysis of the suitability of an effective viscosity to represent interactions between red blood cells

TL;DR

This study evaluates whether an effective viscosity can accurately model interactions between red blood cells in shear flow, finding that single-cell simulations with blood viscosity are sufficiently accurate for hemolysis prediction, offering a computationally efficient alternative.

Contribution

The paper demonstrates that single-cell simulations using blood viscosity can reliably approximate cell-cell interactions, reducing computational costs in hemolysis modeling.

Findings

Single-cell simulations with blood viscosity closely match multiple-cell results in peak strain.

At least 8 cells and a spherical harmonic degree >10 are needed for converged statistics.

Single-cell approach predicts maximum strain with 13% average difference, suitable for hemolysis prediction.

Abstract

Many methods to computationally predict red blood cell damage have been introduced, and among these are Lagrangian methods which track the cells along their pathlines. Such methods typically do not explicitly include cell-cell interactions. Due to the high volume fraction of red blood cells in blood, these interactions could impact cell mechanics and thus, the amount of damage caused by the flow. To investigate this question, cell-resolved simulations of red blood cells in shear flow were performed for multiple interacting cells, as well as for single cells in unbounded flow at an effective viscosity. Simulations run without adjusting the bulk viscosity produced larger errors unilaterally and were not considered further for comparison. We show that a periodic box containing at least 8 cells and a spherical harmonic of degree larger than 10 are necessary to produce converged higher-order statistics. The maximum difference between the single-cell and multiple-cell cases in terms of peak strain was 3.7%. To achieve this agreement, one must use the whole blood viscosity and average over multiple cell orientations when adopting a single-cell simulation approach. There were some differences between the two models in terms of average strain (maximum difference of 13%). However, given the accuracy of the single-cell approach in predicting the maximum strain, which is useful in hemolysis prediction, and its computational cost that is orders of magnitude less than the multiple-cell approach, one may use it as an affordable cell-resolved approach for hemolysis prediction.