(431e) Recent Enhanced Structural Stress and Tensor Upgrades to Mhawb Tevp Model for Characterization of Human Blood | AIChE

(431e) Recent Enhanced Structural Stress and Tensor Upgrades to Mhawb Tevp Model for Characterization of Human Blood


Armstrong, M. - Presenter, United States Military Academy
Pincot, A., United States Military Academy
Horner, J. S., University of Delaware
Beris, A., University Of Delaware
Recent work modeling the rheological behavior of human blood indicates that blood has all of the hallmark features of a complex material, including shear-thinning, viscoelastic behavior, a yield stress and thixotropy. After decades of modeling steady state blood data, and the development of steady state models, like the Casson, Carreau-Yasuda, Herschel-Bulkley, etc. the advancement and evolution of blood modeling to transient flow conditions now has a renewed interest [1,2,5,11]. Using recently collected human blood rheological data we show and compare modeling efforts with the new enhanced structural stress modified Horner-Armstrong-Wagner-Beris (mHAWB), along with its full stress tensor form with the original. We compare the new approaches by ability to predict small, uni-directional and large amplitude oscillatory shear flow.

This effort is followed with a discussion of novel transient flow rheological experiments applied to human blood including for model fitting purposes including step-up/step-down, and triangle ramp experiments [7-10]. The family of models that can handle these transient flows involve modifications to the recently published mHAWB model [1-11]. We fist discuss the development of the scalar, structure parameter evolution models and we compare fitting results with our newly acquired transient blood data to the models [5,11]. We also highlight our novel model fitting procedure by first fitting to steady state, and while keeping the steady state parameters constant fitting the remaining model transient parameters to a series of step up/down in shear rate experiments. With the full set of parameters determined with a global, stochastic optimization algorithm the SAOS, LAOS and unidirectional oscillatory shear flow is predicted and compared to the data. Model efficacy is then compared.


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