Diving into a Simple Anguilliform Swimmer's Sensitivity.

Area of Science:

• Fluid dynamics
• Biomechanics
• Computational modeling

Background:

• Aquatic locomotion models vary in complexity, from simple 2D swimmers to intricate 3D simulations of collective behavior.
• Model outputs, such as performance metrics, are highly dependent on numerous input parameters.

Purpose of the Study:

• Investigate swimming performance sensitivity to parameters in a 2D anguilliform model.
• Explore how fluid scale (Reynolds number), stroke frequency, and kinematic parameters influence locomotion.
• Extend previous parameter exploration of the same model.

Main Methods:

• Utilized an idealized 2D anguilliform swimming model with dynamic body curvature.
• Performed 5000 fluid-structure interaction simulations with parameter combinations selected via Sobol sequence.
• Conducted global sensitivity analysis to identify key performance drivers.

Main Results:

• Swimming performance demonstrated highest sensitivity to stroke frequency variations.
• Identified trends in swimming performance by projecting data onto 2D subspaces.
• Discovered Pareto-like optimal fronts indicating trade-offs in performance metrics.

Conclusions:

• Stroke frequency is the dominant factor influencing the simulated anguilliform swimmer's performance.
• Sensitivity analysis provides insights for optimizing aquatic locomotion models.
• The findings contribute to understanding bio-inspired propulsion and collective dynamics.