ABSTRACT
Crickets are able to sense their surrounding environment through about 2000 filiform hairs located on a pair of abdominal cerci. The mechanism by which the cricket is able to sense a wide range of input signals using these filiform hairs of different length and orientation is of great interest. Most of the previous filiform hair models have focused on a single, rigid hair in an idealized air field. Here, we present a model of the cercus and filiform hairs that are mechanically coupled to the surrounding air, and the model equations are based on the penalty immersed boundary method. The key difference between the penalty immersed boundary method and the traditional immersed boundary method is the addition of forces to account for density differences between the immersed solid (the filiform hairs) and the surrounding fluid (air). The model is validated by comparing the model predictions to experimental results, and then the model is used to examine the interactions between multiple hairs. With multiple hairs, there is little interaction when the hairs are separated by more than 1mm, and, as they move closer, they interact through viscous coupling, which reduces the deflection of the hairs due to the air movement. We also examine the computational scalability of the algorithm and show that the computational costs grow linearly with the number of hairs being modeled.