Jay A. Stotsky

Jay A. Stotsky, David M. Bortz

A posteriori error analysis is a technique to quantify the error in particular simulations of a numerical approximation method. In this article, we use such an approach to analyze how various error components propagate in certain moving boundary problems. We study quasi-steady state simulations where slowly moving boundaries remain in mechanical equilibrium with a surrounding fluid. Such problems can be numerically approximated with the Method of Regularized Stokelets(MRS), a popular method used for studying viscous fluid-structure interactions, especially in biological applications. Our approach to monitoring the regularization error of the MRS is novel, along with the derivation of linearized adjoint equations to the governing equations of the MRS with a elastic elements. Our main numerical results provide a clear illustration of how the error evolves over time in several MRS simulations.

Jay A. Stotsky, Jason F. Hammond, Leonid Pavlovsky et al.

The goal of this work is to develop a numerical simulation that accurately captures the biomechanical response of bacterial biofilms and their associated extracellular matrix (ECM). In this, the second of a two-part effort, the primary focus is on formally presenting the heterogeneous rheology Immersed Boundary Method (hrIBM) and validating our model against experimental results. With this extension of the Immersed Bounadry Method (IBM), we use the techniques originally developed in Part I, (Hammond et al. (2014) ) to treat the biofilm as a viscoelastic fluid possessing variable rheological properties anchored to a set of moving locations (i.e., the bacteria locations). We validate our modeling approach from Part I by comparing dynamic moduli and compliance moduli computed from our model to data from mechanical characterization experiments on Staphylococcus epidermidis biofilms. The experimental setup is described in Pavlovsky et al. (2013) in which biofilms are grown and tested in a parallel plate rheometer. Matlab code used to produce results in this paper will be available at https://github.com/MathBioCU/BiofilmSim.