2021/03/09 by Luca Berti, Mickaël Binois, Berti, Luca +9
Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Mathematics #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Micro and Nano Robotics #Microfluidic and Bio-sensing Technologies #Molecular Communication and Nanonetworks #Optimization and Control (math.OC) #Soft Condensed Matter (cond-mat.soft)
paper · pdf · doi:10.48550/arxiv.2103.05637
openalex publication_date 2021/03/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
In this paper we are interested in optimizing the shape of multi-flagellated helical microswimmers. Mimicking the propagation of helical waves along the flagella, they self-propel by rotating their tails. The swimmer's dynamics is computed using the Boundary Element Method, implemented in the open source Matlab library Gypsilab. We exploit a Bayesian optimization algorithm to maximize the swimmer's speeds through their shape optimization. Our results show that the optimal tail shapes are helices with large wavelength, such that the shape periodicity is disregarded. Moreover, the best propulsion speed is achieved for elongated heads when the swimmer has one or two flagella. Surprisingly, a round head is obtained when more flagella are considered. Our results indicate that the position and number of flagella modify the propulsion pattern and play a significant role in the optimal design of the head. It appears that Bayesian optimization is a promising method for performance improvement in microswimming.