PO113 


Poster Session


Multifaceted blood prediction using contemporary thixotropic and viscoelastic models


October 17, 2018 (Wednesday) 6:30


Poster Session / Woodway II/III

(Click on name to view author profile)

  1. Clark, Michael (United States Military Academy, Chemistry and Life Science)
  2. Armstrong, Matthew J. (United States Military Academy, Chemistry and Life Science)
  3. Horner, Jeffrey S. (University of Delaware, Chemical and Biomolecular Engineering)

(in printed abstract book)
Michael Clark1, Matthew J. Armstrong1, and Jeffrey S. Horner2
1Chemistry and Life Science, United States Military Academy, West Point, NY 10996; 2Chemical and Biomolecular Engineering, University of Delaware, Newark, DE


Clark, Michael


Many complex materials have thixotropic behaviors, displaying time dependent viscous and elastic properties that are a function of microstructure. Some examples of thixotropic materials are aqueous nuclear waste, crude oil, and paints. Another example is blood. Modeling the behavior of these materials allows us to better understand how they can be used effectively in their respective industry. We have characterized human blood using recently collected steady state data and the Blackwell-Ewoldt TEVP model, and an enhanced Apostolidis-Armstrong-Beris with viscoelastic modification model. First, we analyzed steady state data and compared parameter predictions to physiological parameters, then we simultaneously fit the models to steady state and a triangle ramp and step up/down rheological human blood data. Using the best fit parameter values from the steady state-triangle ramp-step up/down fit, we predict and Large Amplitude Oscillatory Shear flow. We characterize blood to develop better models, and evolve strategies to give way to better understanding of blood to facilitate benchmarking blood’s “normal” rheological fingerprint, with a view toward a methodology to diagnose pathologies based on rheological deviations from blood’s baseline mechanical properties. Based on the biochemistry of blood, its fluid mechanics, and rheological properties, pathological blood will have different rheological properties than healthy blood. By modeling healthy blood, we can establish a baseline that will then allow us to characterize and diagnose pathological blood based on its flow behavior, as was seen in the Moreno paper with high cholesterol. We then look for statistically significant relationships between certain model parameters and physiological parameters measured from the blood like cholesterol, sugar, hematocrit, etc.