Swimming Through Parameter Subspaces of a Simple Anguilliform Swimmer

Area of Science:

• Computational fluid dynamics
• Biomimetic locomotion
• Scientific computing

Background:

• Swimming performance models often require numerous parameters, leading to sensitivity issues.
• Understanding locomotion in organisms like Caenorhabditis elegans (C. elegans) is crucial for bio-inspired engineering.

Purpose of the Study:

• To identify parameter subspaces for enhanced swimming performance in an idealized anguilliform swimmer.
• To analyze the sensitivity of swimming performance to various model parameters.

Main Methods:

• Utilized an immersed boundary method to simulate fluid-structure interaction for a 1D swimming model.
• Investigated an idealized swimmer that changes body curvature to propel itself.
• Performed extensive simulations to explore parameter spaces.

Main Results:

• Enhanced swimming performance was found in specific parameter subspaces.
• Swimmer performance showed higher sensitivity to fluid scale and stroke frequency.
• Variations in upstroke/downstroke velocity and acceleration had less impact on performance.
• Identified Pareto-like optimal fronts for cost of transport and swimming speed.

Conclusions:

• This methodology effectively locates robust parameter subspaces for desired swimming performance.
• The computational approach requires significantly more simulations than traditional methods.
• Findings can inform the design of efficient bio-inspired robotic swimmers.