Paper Number
PO114 

Session
Poster Session

Title
Multifaceted blood prediction using the Horner-Armstrong-Wagner-Beris thixo-elasto-visco-plastic (TEVP) model

Presentation Date and Time
October 17, 2018 (Wednesday) 6:30

Track / Room
Poster Session / Woodway II/III

Authors (Click on name to view author profile)

  1. Deegan, 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)

Author and Affiliation Lines (in printed abstract book)
Michael Deegan1, 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

Speaker / Presenter 
Deegan, Michael

Text of Abstract
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 Horner-Armstrong-Wagner-Beris TEVP model. First, we analyzed steady state data and compared parameter predictions to physiological parameters, then we simultaneously fit the HAWB model to steady state and a series of triangle ramp functions again using recently collected blood data. Using the best fit HAWB parameter values from the steady state-sawtooth fit, we predict Large Amplitude Oscillatory Shear flow. We also demonstrate and compare using fits with step up/step down transient experiments. 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.