Using the penalty immersed boundary method to model the interaction between filiform hairs of crickets

Abstract

Fluid-structure interactions are important in a wide range of applications and, due to their complexity, need extensive experimental and computational research. One such example comes from crickets, which have evolutionarily developed an excellent micro-air-flow sensory system. Understanding principles of the cricket' micro-air-flow sensor will help design and manufacture artificial sensors. This thesis focuses on improving and validating a Penalty Immersed Boundary (PIB) model of the cricket sensory system, which consists of hundreds of filiform hairs. Previous efforts by others have modeled the filiform hair as a rigid inverted pendulum. Advantages to the PIB approach over previous models include a flexible fluid solver (previous models used an idealized, analytical flow field), the filiform hairs are not required to be completely rigid, and, most importantly, the entire cerci and all the filiform hairs can be modeled. The first goal was to improve the precision and accuracy of modeling a single filiform hair by adjusting model parameters so that the model predictions more accurately fit experimental data. A second goal was to model a portion of a full cercus based on filiform hair data from a real cricket and use the model to determine the interactions occurring between multiple hairs and identify any evolutionary optimization of the cercal system.