BF23 


Biomaterials and Bio-fluid Dynamics


Recent advances to the thixo-elasto-viscoplastic (TEVP) modeling of blood rheology


October 11, 2022 (Tuesday) 5:25


Track 4 / Michigan AB

(Click on name to view author profile)

  1. Armstrong, Matthew (United States Military Academy, Department of the Army)
  2. Pincot, Andre (United States Military Academy, Department of Chemistry and Life Science,)
  3. Jariwala, Soham (University of Delaware, Chemical & Biomolecular Engineering)
  4. Wagner, Norman J. (University of Delaware, Chemical and Biomolecular Engineering)
  5. Beris, Antony N. (University of Delaware, Chemical & Biomolecular Engineering)

(in printed abstract book)
Matthew Armstrong1, Andre Pincot1, Soham Jariwala2, Norman J. Wagner2 and Antony N. Beris2
1Department of the Army, United States Military Academy, New York, NY; 2Chemical & Biomolecular Engineering, University of Delaware, Newark, DE 19711


Beris, Antony N.


theoretical methods; computational methods; bio-fluids; colloids; suspensions


Human blood exhibits the hallmark features of a rheologically complex material, including shear-thinning, viscoelastic behavior, yield stress, and thixotropy. Previous work [Armstrong and Tussing, Phys. Fluids 32, 094111 (2020)] has led to the development of the enhanced thixotropic viscoelastic (ETV) model for blood that incorporates viscoelastic contribution by the rouleaux aggregates to the stress response, in addition to a nonlinear viscoelastic description of the stress contributed by the individual red blood cells deforming under the action of the flow. This model has shown superior performance in fitting human blood steady state and transient rheological data from a strain-controlled rheometer [Horner et al., J. Rheol. 62, 577–591 (2018); 63, 799–813 (2019)] as compared to other alternate models.

In the present work, we first discuss the development of scalar and tensorial variants of the ETV model, the enhanced structural stress thixotropic-viscoelastic (ESSTV) model [Armstrong et al., J. Rheol, 66, 327 (2022)] and outline the improvements that have been made to reduce the number of fit parameters. We fit the model parameters using rheological measurements (steady shear, step-ups and step-downs in shear rate) of human blood from several blood donors and compare the predictions against small, large, and unidirectional large amplitude oscillatory shear experiments. We find that the full tensor stress formulations t-ETV and t-ESSTV significantly improved the predictive capability of the earlier ETV model. Further developments, resulting in a reduction of the model parameters and/or a more thermodynamically consistent formulation are also going to be discussed.