ABSTRACT
The microbond test of natural fibers tends to produce scattered interfacial shear stress (IFSS) values. The sources of this scattering are known, but the roles they play in producing high IFSS scattering remain to be investigated. In this study, a numerical method was used to simulate microbond testing and to examine the experimental parameters in a microbond test of Typha angustifolia fiber/epoxy. Three parameters were considered: fiber diameter, fiber length embedded in the epoxy, and the distance between the vise and the specimen. The geometries were modeled and analyzed by ABAQUS software using its cohesive zone model features. There were two types of contact used in this analysis: tie constraint and surface-to-surface. The results showcased the roles of the following experimental parameters: a larger fiber diameter from a sample increased the IFSS value, a longer embedded length reduced the IFSS value, and a shorter vise-specimen distance increased the IFSS value. The IFSS scattering in the microbond test could have originated from the interaction between these parameters. Of the three parameters, only the vise-specimen distance was found to be able to be reasonably controlled. When the IFSS value was atypically large, fiber diameter and/or embedded length potentially drove the scattering. This study advises further compilation and classification of the role of each experimental parameter in modulating the IFSS value.
ABSTRACT
Inflammation is a process driven by underlying cell-cell communication and many other factors. In this study, a model of cell-cell communications was proposed to study factors driving the inflammation time course. Analyses of inflammations that are driven by the combined effects of strain (mechanical stimuli) and/or pathogens are considered in this paper. An agent-based model was employed to simulate inflammation where macrophages and fibroblasts influence each other through cell signaling cytokines that diffuse and spread in the tissue space. The communication network of macrophages and fibroblasts was then inferred and its network model (termed TE network) was generated and analyzed. The results suggest that factors driving inflammation time course can be discriminated by the characteristics of TE networks. Inflammation driven only by pathogens has certain TE network characteristics indicating slower and lower information exchange among cells. Multiple stimuli can help to maintain sufficient information exchange among cells, which is beneficial for inflammation resolution. The TE network captures the unfolding of the innate immune system over time, and the history of pathogens invasion. The resulting network leads to an improved understanding of the resilience of the system to future pathogen invasion.
