Temporal organization of swimming activity inSarsia tubulosa M. Sars (Hydrozoa)

Naut Your Everyday Jellyfish Model: Exploring How Tentacles and Oral Arms Impact Locomotion

Jellyfish are majestic, energy-efficient, and one of the oldest species that inhabit the oceans. It is perhaps the second item, their efficiency, that has captivated scientists for decades into investigating their locomotive behavior. Yet, no one has specifically explored the role that their tentacles and oral arms may have on their potential swimming performance. We perform comparative in silico experiments to study how tentacle/oral arm number, length, placement, and density affect forward swimming speeds, cost of transport, and fluid mixing. An open source implementation of the immersed boundary method was used (IB2d) to solve the fully coupled fluid–structure interaction problem of an idealized flexible jellyfish bell with poroelastic tentacles/oral arms in a viscous, incompressible fluid. Overall tentacles/oral arms inhibit forward swimming speeds, by appearing to suppress vortex formation. Nonlinear relationships between length and fluid scale (Reynolds Number) as well as tentacle/oral arm number, density, and placement are observed, illustrating that small changes in morphology could result in significant decreases in swimming speeds, in some cases by upwards of 80–90% between cases with or without tentacles/oral arms.

Identifying and modeling motion primitives for the hydromedusae Sarsia tubulosa and Aequorea victoria

The movements of organisms can be thought of as aggregations of motion primitives: motion segments containing one or more significant actions. Here, we present a means to identify and characterize motion primitives from recorded movement data. We address these problems by assuming that the motion sequences can be characterized as a series of dynamical-system-based pattern generators. By adopting a nonparametric, Bayesian formalism for learning and simplifying these pattern generators, we arrive at a purely data-driven model to automatically identify breakpoints in the movement sequences. We apply this model to swimming sequences from two hydromedusa. The first hydromedusa is the prolate Sarsia tubulosa, for which we obtain five motion primitives that correspond to bell cavity pressurization, jet formation, jetting, cavity fluid refill, and coasting. The second hydromedusa is the oblate Aequorea victoria, for which we obtain five motion primitives that correspond to bell compression, vortex separation, cavity fluid refill, vortex formation, and coasting. Our experimental results indicate that the breakpoints between primitives are correlated with transitions in the bell geometry, vortex formation and shedding, and changes in derived dynamical quantities. These dynamics quantities include terms like pressure, power, drag, and thrust. Such findings suggest that dynamics information is inherently present in the observed motions.