Parametric modelling of a biomimetic propulsion system using additive manufacturing for autonomous underwater vehicles

Abstract

This work presents a novel pseudorandom algorithm for generating in-silico biomimetic models of caudal fins for additive manufacturing for flexible materials. The methodology provides a tool to develop caudal fin models for different morphologies (within rounded, truncated, forked, and lunate), geometrical features and, considering randomness to improve the lifelikeness of the model. The capability of the algorithm to generate designs with customized hydrodynamic features was evaluated in-silico using computational fluid dynamics comparing the maximum velocity and the angle of attack. Numerical data shows that customization of key dimensional can be integrated into a flexible and dynamic design process. This work is a step towards reproducing more robust and lifelike engineering systems.