Fish swim with an apparent ease that hides the intricate underlying fluid dynamics. Through numerical simulations we can visualize and understand the processes that govern self-propulsion.

Combining such simulations with numerical evolution techniques allows us to reverse-engineer hydrodynamically optimal swimming shapes, motions, or both. This provides valuable insights into what aspects of natural swimmers have been adapted for better hydrodynamics, and also how man-made robots should be designed to outperform natural fish.

Relevant publications on this topic are:

• Optimal morphokinematics of undulatory swimmers at intermediate Reynolds numbers (link)
• Quantitative flow analysis of swimming dynamics with coherent Lagrangian vortices (link)
• Self-propulsion of a counter-rotating cylinder pair in a viscous fluid (link)
• Optimal shapes for anguilliform swimmers at intermediate Reynolds numbers (link)
• C-start: optimal start of larval fish (link)
• Simulations of single and multiple swimmers with non-divergence free deforming geometries (link)

See also my visualizations of biolocomotion in the gallery.