The influence of biomechanical parameters of an erythrocyte and viscosity of the surrounding fluid on the hydrodynamic interaction with a solid wall
DOI:
https://doi.org/10.7242/1999-6691/2025.18.4.35Keywords:
blood flow, hemodynamics, erythrocyte, hydrodynamic interaction, numerical simulationAbstract
The nature of blood flow in capillaries, arterioles, and venules largely depends on the mechanical interactions between red blood cells and vessel walls . A theoretical understanding of the principles of hydrodynamic interaction between blood cells and vessel walls is essential for a comprehensive biophysical description of blood flow in the microcirculatory system, as well as for the design of medical microfluidic devices for processing blood samples. In this study, numerical methods are used to investigate the behavior of a single red blood cell (erythocyte) near a solid flat surface under conditions of shear flow of a viscous Newtonian fluid. The aim of the study is to identify the pattern of erythrocyte motion depending on its biomechanical parameters and hydrodynamic conditions. To address these issues, we use a numerical model that combines particle dynamics and the Lattice Boltzmann method with the Bhatnagar-Gross-Krook collision integral. The biomechanical model of the red blood cell takes into account tensile and bending elasticity, as well as the forces that maintain the membrane area and the cell volume. Computer simulation of red blood cell trajectories under various hydrodynamic conditions shows that the velocity of cell repulsion from a solid wall is linearly dependent on the shear rate. It varies non-monotonically as the red blood cell moves away from the wall, and decreases at greater distances. The lift effect in the model is most pronounced when the red blood cell moves in a “tank-treading” mode at high shear stresses. The dependence of the lift velocity on the elasticity and volume of the cell is quantified by varying the biomechanical parameters of the erythrocyte.
Downloads
References
Fahraeus R., Lindqvist T. The Viscosity Of The Blood In Narrow Capillary Tubes. American Journal of Physiology-Legacy Content. 1931. Vol. 96, no. 3. P. 562–568. DOI: 10.1152/ajplegacy.1931.96.3.562
Dintenfass L. Inversion of the Fahraeus-Lindqvist Phenomenon in Blood Flow through Capillaries of Diminishing Radius. Nature. 1967. Vol. 215, no. 5105. P. 1099–1100. DOI: 10.1038/2151099a0
Pries A., Secomb T. Rheology of the microcirculation. Clin. Hemorheol. Microcirc. 2003. Vol. 29, no. 3/4. P. 143–148.
Haynes R.H. Physical basis of the dependence of blood viscosity on tube radius. American Journal of Physiology-Legacy Content. 1960. Vol. 198, no. 6. P. 1193–1200. DOI: 10.1152/ajplegacy.1960.198.6.1193
Secomb T.W., Skalak R., Özkaya N., Gross J.F. Flow of axisymmetric red blood cells in narrow capillaries. Journal of Fluid Mechanics. 1986. Vol. 163. P. 405–423. DOI: 10.1017/s0022112086002355
Ong P.K., Namgung B., Johnson P.C., Kim S. Effect of erythrocyte aggregation and flow rate on cell-free layer formation in arterioles. American Journal of Physiology-Heart and Circulatory Physiology. 2010. Vol. 298, no. 6. P. H1870–H1878. DOI: 10.1152/ajpheart.01182.2009
Xiao L.L., Lin C.S., Chen S., Liu Y., Fu B.M., Yan W.W. Effects of red blood cell aggregation on the blood flow in a symmetrical stenosed microvessel. Biomechanics and Modeling in Mechanobiology. 2019. Vol. 19, no. 1. P. 159–171. DOI: 10.1007/s10237-019-01202-9
Soutani M., Suzuki Y., Tateishi N., Maeda N. Quantitative evaluation of flow dynamics of erythrocytes in microvessels: influence of erythrocyte aggregation. American Journal of Physiology-Heart and Circulatory Physiology. 1995. Vol. 268, no. 5. P. H1959–H1965. DOI: 10.1152/ajpheart.1995.268.5.h1959
Abkarian M., Viallat A. Dynamics of Vesicles in a Wall-Bounded Shear Flow. Biophysical Journal. 2005. Vol. 89, no. 2. P. 1055–1066. DOI: 10.1529/biophysj.104.056036
Olla P. The role of tank-treading motions in the transverse migration of a spheroidal vesicle in a shear flow. Journal of Physics A: Mathematical and General. 1997. Vol. 30, no. 1. P. 317–329. DOI: 10.1088/0305-4470/30/1/022
Narsimhan V., Zhao H., Shaqfeh E.S.G. Coarse-grained theory to predict the concentration distribution of red blood cells in wall-bounded Couette flow at zero Reynolds number. Physics of Fluids. 2013. Vol. 25, no. 6. 061901. DOI: 10.1063/1.4810808
Seifert U. Hydrodynamic Lift on Bound Vesicles. Physical Review Letters. 1999. Vol. 83, no. 4. P. 876–879. DOI: 10.1103/physrevlett.83.876
Saffman P.G. The lift on a small sphere in a slow shear flow. Journal of Fluid Mechanics. 1965. Vol. 22, no. 2. P. 385–400. DOI: 10.1017/s0022112065000824
Fedosov D.A., Caswell B., Popel A.S., Karniadakis G.E. Blood Flow and Cell-Free Layer in Microvessels. Microcirculation. 2010. Vol. 17, no. 8. P. 615–628. DOI: 10.1111/j.1549-8719.2010.00056.x
Bessonov N., Babushkina E., Golovashchenko S.F., Tosenberger A., Ataullakhanov F., Panteleev M., Tokarev A., Volpert V. Numerical Modelling of Cell Distribution in Blood Flow. Mathematical Modelling of Natural Phenomena. 2014. Vol. 9, no. 6. P. 69–84. DOI: 10.1051/mmnp/20149606
Fedosov D., Dao M., Karniadakis G., Suresh S. Computational bio-rheology of human blood flow in health and disease. Ann. Biomed. Eng. 2014. Vol. 42. P. 368–387.
Faivre M., Abkarian M., Bickraj K., Stone H.A. Geometrical focusing of cells in a microfluidic device: An approach to separate blood plasma. Biorheology: The Official Journal of the International Society of Biorheology. 2006. Vol. 43, no. 2. P. 147–159. DOI: 10.1177/0006355x2006043002001
Maurya A., Murallidharan J.S., Sharma A., Agarwal A. Microfluidics geometries involved in effective blood plasma separation. Microfluidics and Nanofluidics. 2022. Vol. 26, no. 10. 73. DOI: 10.1007/s10404-022-02578-4
Javadi E., Li H., Gallastegi A.D., Frydman G.H., Jamali S., Karniadakis G.E. Circulating cell clusters aggravate the hemorheological abnormalities in COVID-19. Biophysical Journal. 2022. Vol. 121, no. 18. P. 3309–3319. DOI: 10.1016/j.bpj.2022.08.031
Chang H.- Y., Yazdani A., Li X., Douglas K.A., Mantzoros C.S., Karniadakis G.E. Quantifying Platelet Margination in Diabetic Blood Flow. Biophysical Journal. 2018. Vol. 115, no. 7. P. 1371–1382. DOI: 10.1016/j.bpj.2018.08.031
Mizeva I., Makovik I., Dunaev A., Krupatkin A., Meglinski I. Analysis of skin blood microflow oscillations in patients with rheumatic diseases. Journal of Biomedical Optics. 2017. Vol. 22, no. 7. 070501. DOI: 10.1117/1.jbo.22.7.070501
Mizeva I., Zharkikh E., Dremin V., Zherebtsov E., Makovik I., Potapova E., Dunaev A. Spectral analysis of the blood flow in the foot microvascular bed during thermal testing in patients with diabetes mellitus. Microvascular Research. 2018. Vol. 120. P. 13–20. DOI: 10.1016/j.mvr.2018.05.005
Farina A., Rosso F., Fasano A. A continuum mechanics model for the Fåhræus-Lindqvist effect. Journal of Biological Physics. 2021. Vol. 47, no. 3. P. 253–270. DOI: 10.1007/s10867-021-09575-8
Vahidkhah K., Balogh P., Bagchi P. Flow of Red Blood Cells in Stenosed Microvessels. Scientific Reports. 2016. Vol. 6, no. 1. 28194. DOI: 10.1038/srep28194
Dupin M.M., Halliday I., Care C.M., Alboul L., Munn L.L. Modeling the flow of dense suspensions of deformable particles in three dimensions. Phys. Rev. E. 2007. Vol. 75. 066707.
Zavodszky G., Rooij B. van, Azizi V., Hoekstra A. Cellular Level In-silico Modeling of Blood Rheology with An Improved Material Model for Red Blood Cells. Frontiers in Physiology. 2017. Vol. 8. 563. DOI: 10.3389/fphys.2017.00563
Dupire J., Socol M., Viallat A. Full dynamics of a red blood cell in shear flow. Proceedings of the National Academy of Sciences. 2012. Vol. 109, no. 51. P. 20808–20813. DOI: 10.1073/pnas.1210236109
Lanotte L., Mauer J., Mendez S., Fedosov D.A., Fromental J.-M., Claveria V., Nicoud F., Gompper G., Abkarian M. Red cells’ dynamic morphologies govern blood shear thinning under microcirculatory flow conditions. Proceedings of the National Academy of Sciences. 2016. Vol. 113, no. 47. P. 13289–13294. DOI: 10.1073/pnas.1608074113
Yao W., Wen Z., Yan Z., Sun D., Ka W., Xie L., Chien S. Low viscosity Ektacytometry and its validation tested by flow chamber. Journal of Biomechanics. 2001. Vol. 34, no. 11. P. 1501–1509. DOI: 10.1016/s0021-9290(01)00109-9
Tran-Son-Tay R., Sutera S., Rao P. Determination of red blood cell membrane viscosity from rheoscopic observations of tank-treading motion. Biophys. J. 1984. Vol. 46, no. 1. P. 65–72. DOI: 10.1016/S0006-3495(84)83999-5
Grigorev G., Lebedev A., Wang X., Qian X., Maksimov G., Lin L. Advances in Microfluidics for Single Red Blood Cell Analysis. Biosensors. 2023. Vol. 13, no. 1. 117. DOI: 10.3390/bios13010117
Kuan D.- H., Wu C.-C., Su W.-Y., Huang N.-T. A Microfluidic Device for Simultaneous Extraction of Plasma, Red Blood Cells, and On-Chip White Blood Cell Trapping. Scientific Reports. 2018. Vol. 8, no. 1. 15345. DOI: 10.1038/s41598-018-33738-8
Recktenwald S.M., Lopes M.G.M., Peter S., et al. Erysense, a Lab-on-a-Chip-Based Point-of-Care Device to Evaluate Red Blood Cell Flow Properties With Multiple Clinical Applications. Frontiers in Physiology. 2022. Vol. 13. 884690. DOI: 10.3389/fphys.2022.884690
Lyubimova T.P., Ivantsov A.O., Khlybov O.A. Application of level set method for modeling of immiscible liquids with large surface tension. Computational Continuum Mechanics. 2025. Vol. 17, no. 4. P. 509–518. DOI: 10.7242/1999-6691/2024.17.4.41
Trusov P.V., Zaitseva N.V., Tsinker M.Y., Nurislamov V.V. Simulation of airflow in the elastic deformable porous medium approximating human lungs: implementation algorithm and analysis of the results of model application. Computational Continuum Mechanics. 2024. Vol. 17, no. 3. P. 329–346. DOI: 10.7242/1999-6691/2024.17.3.28
Popel A., Regirer S., Usick P. A continuum model of blood flow. Biorheology. 1974. Vol. 11, no. 6. P. 427–437. DOI: 10.3233/bir-1974-11605
Simakov S.S. Spatially averaged haemodynamic models for different parts of cardiovascular system. Russian Journal of Numerical Analysis and Mathematical Modelling. 2020. Vol. 35, no. 5. P. 285–294. DOI: 10.1515/rnam-2020-0024
Arzani A. Accounting for residence-time in blood rheology models: do we really need non-Newtonian blood flow modelling in large arteries?. Journal of The Royal Society Interface. 2018. Vol. 15, no. 146. 20180486. DOI: 10.1098/rsif.2018.0486
Krüger T. Effect of tube diameter and capillary number on platelet margination and near-wall dynamics. Rheologica Acta. 2015. Vol. 55, no. 6. P. 511–526. DOI: 10.1007/s00397-015-0891-6
Fedosov D.A., Pan W., Caswell B., Gompper G., Karniadakis G.E. Predicting human blood viscosity in silico. Proc. Nat. Acad. Sci. USA. 2011. Vol. 108, no. 29. P. 11772–11777.
Cimrak I., Gusenbauer M., Jancigova I. An ESPResSo implementation of elastic objects immersed in a fluid. Computer Physics Communications. 2014. Vol. 185, no. 3. P. 900–907.
Belyaev A.V. Towards realistic blood cell biomechanics in microvascular thrombosis simulations. Russian Journal of Numerical Analysis and Mathematical Modelling. 2024. Vol. 39, no. 5. P. 223–242. DOI: 10.1515/rnam-2024-0021
Dunweg B., Ladd A.J.C. Lattice Boltzmann Simulations of Soft Matter Systems. Adv. in Polymer Sci. Springer Berlin Heidelberg, 2008. P. 89–166.
Succi S. The Lattice Boltzmann Equation for Fluid Dynamics and Beyond (Numerical Mathematics and Scientific Computation). Oxford University Press, USA, 2001
Bhatnagar P.L., Gross E.P., Krook M. A Model for Collision Processes in Gases. I. Small Amplitude Processes in Charged and Neutral One-Component Systems. Physical Review. 1954. Vol. 94, no. 3. P. 511–525. DOI: 10.1103/physrev.94.511
Chen S., Doolen G.D. Lattice Boltzmann Method for Fluid Flows. Annual Review of Fluid Mechanics. 1998. Vol. 30. P. 329–364.
Guo Z., Zheng C., Shi B. Discrete lattice effects on the forcing term in the lattice Boltzmann method. Physical Review E. 2002. Vol. 65, no. 4. 046308. DOI: 10.1103/physreve.65.046308
Ladd A.J.C. Numerical simulations of particulate suspensions via a discretized Boltzmann equation. Part 1. Theoretical foundation. Journal of Fluid Mechanics. 1994. Vol. 271. P. 285–309. DOI: 10.1017/s0022112094001771
Verlet L. Computer “Experiments” on Classical Fluids. I. Thermodynamical Properties of Lennard-Jones Molecules. Physical Review. 1967. Vol. 159, no. 1. P. 98–103. DOI: 10.1103/physrev.159.98
Ahlrichs P., Dünweg B. Lattice-Boltzmann Simulation of Polymer-Solvent Systems. International Journal of Modern Physics C. 1998. Vol. 09, no. 08. P. 1429–1438. DOI: 10.1142/s0129183198001291
Mills J.P., Qie L., Dao M., Lim C.T., Suresh S. Nonlinear Elastic and Viscoelastic Deformation of the Human Red Blood Cell with Optical Tweezers. Mol. Cell. Biomech. 2004. Vol. 1. P. 169–180.
Eggleton C.D., Popel A.S. Large deformation of red blood cell ghosts in a simple shear flow. Physics of Fluids. 1998. Vol. 10, no. 8. P. 1834–1845. DOI: 10.1063/1.869703
Losserand S., Coupier G., Podgorski T. Migration velocity of red blood cells in microchannels. Microvascular Research. 2019. Vol. 124. P. 30–36. DOI: 10.1016/j.mvr.2019.02.003
Yazdani A.Z.K., Bagchi P. Phase diagram and breathing dynamics of a single red blood cell and a biconcave capsule in dilute shear flow. Physical Review E. 2011. Vol. 84, no. 2. 026314. DOI: 10.1103/physreve.84.026314
Voevodin V., Antonov A., Nikitenko D., Shvets P., Sobolev S., Sidorov I., Stefanov K., Voevodin V., Zhumatiy S. Supercomputer Lomonosov-2: Large Scale, Deep Monitoring and Fine Analytics for the User Community. Supercomputing Frontiers and Innovations. 2019. Vol. 6, no. 2. P. 4–11. DOI: 10.14529/jsfi190201
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Computational Continuum Mechanics

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.