Computationally-validated surrogate models for optimal geometric design of bio-inspired swimming robots: Helical swimmers

Abstract

Research on micro-swimming robots without tether is growing fast owing to their potential impact on minimally invasive medical procedures. Candidate propulsion mechanisms of robots are vastly based on micro-organisms with rotating helical tails. For design of swimming robots, accurate models are necessary to compute velocities with corresponding hydrodynamic forces. Resistive force theory (RFT) provides an excellent framework for six degrees-of-freedom (dof) surrogate models in order to carry out effective design studies. However, resistance coefficients reported in literature are based on approximate analytical solutions for asymptotical cases, and do not address the effect of hydrodynamic interactions between the body and the tail, even in unbounded fluid media. Here, we use hydrodynamic interaction coefficients that multiply the body resistance coefficients along with no further modification to local resistance coefficients of the tail. Interaction coefficients are obtained from the solution of the inverse problem once for a fixed representative design with a computational fluid dynamics (CFD) simulation or an experiment. Results of the RFT-based hydrodynamic model are compared against further CFD simulations, and indicate that the model with hydrodynamic interaction coefficients obtained from a representative design provides a viable surrogate for computationally intensive three-dimensional time-dependent CFD models for a range of design variables. Finally, the validated hydrodynamic model is employed to investigate efficient geometric designs with helical wave propagation method within a wider range of design parameters.