Breannan Smith, University of North Carolina


Stress Communication in Sheared Viscoelastic Layers: Selection Mechanisms and Redundancy

Abstract: Recent research has highlighted the role of stress communication in biological systems; processes ranging from the growth of vascular tissue to the regulation of biochemical pathways in the respiratory system are influenced by stress signals passing through complex fluids. Studies on pulmonary mucus have focused on its transport to the larynx to clear trapped pathogens. It is now clear, however, that stress signals passing through the mucus layer carry information to epithelial cells. Epithelial cells, in turn, regulate both the release rates of chemical species and the production of mucin. My project has focused on developing an understanding of stress communication and the properties of stress signals in driven viscoelastic layers. In this poster, we model stress communication with the simplest of constitutive laws that captures the nonlinearity of viscoelastic media.

We investigate the Upper Convected Maxwell (UCM) constitutive law with biologically-relevant boundary conditions. We discover criteria for maximizing or minimizing stress communication across a viscoelastic fluid layer. Modeling cilia metachronal waves or components of a cough signal as a large amplitude oscillatory shear (LAOS) boundary condition, we track the stress evolution within a viscoelastic layer confined between a stationary upper plate and an oscillating lower plate. These conditions are those imposed in a micro-parallel plate rheometer built by D. Hill and R. Superfine at UNC-Chapel Hill. Running a frequency sweep, peaks in maximum shear stress and maximum normal stress occur at precise, periodically spaced frequencies. We extend and verify this observation to a stress peak scaling law for all parameters in the system, indicating a remarkable redundancy with respect to stress signal control that we believe must be relevant to biology. Furthermore, in restricted regimes of parameter space, we identify scaling laws for the amplitudes of these peaks.



Advisor: Greg Forest (UNC)