Jellyfish have been called one of the most energy-efficient animals in the world due to the ease in which they move through their fluid environment, by product of their morphological, muscular, and material properties. We investigated jellyfish locomotion by conducting in silico comparative studies and explored swimming performance in different fluids (e.g., changing viscosities) at different fluid scales (e.g., Reynolds Number), bell contraction frequencies,  contraction phase kinematics , as well as bell morphologies and contraction amplitude . To study these relationships, an open source implementation of the immersed boundary method was used (IB2d) to solve the fully coupled fluid-structure interaction problem of a flexible jellyfish bell in a viscous fluid. Complex relationships between scale, morphology, and frequency lead to optimized forward swimming speeds for a particular bell composition, stemming from intricate vortex wake topology, interactions, and fluid mixing. Lastly, we offer an open source computational jellyfish locomotion model to the science community that can be used as a starting place for future numerical experimentation.
Jellyfish have been called one of the most energy-efficient animals in the world due to the ease in which they move through their fluid environment, by product of their morphological, muscular, and material properties. We investigated jellyfish locomotion by conducting in silico comparative studies and explored swimming performance across different fluid scales (e.g., Reynolds Number), bell contraction frequencies, and contraction phase kinematics for a jellyfish with a fineness ratio of 1 (ratio of bell height to bell diameter) . To study these relationships, an open source implementation of the immersed boundary method was used (IB2d) to solve the fully coupled fluid-structure interaction problem of a flexible jellyfish bell in a viscous fluid. Thorough 2D parameter subspace explorations illustrated optimal parameter combinations in which give rise to enhanced swimming performance. All performance metrics indicated a higher sensitivity to bell actuation frequency than fluid scale or contraction phase kinematics, via Sobol sensitivity analysis, on a high performance parameter subspace. Moreover, Pareto-like fronts were identified in the overall performance space involving the cost of transport and forward swimming speed. Patterns emerged within these performance spaces when highlighting different parameter regions, which complemented the global sensitivity results. Lastly, an open source computational model for jellyfish locomotion is offered to the science community that can be used as a starting place for future numerical experimentation.
R
in different fluids (e.g., changing viscosities) at different
across different
A
and
R
, as well as bell morphologies and contraction amplitude
for a jellyfish with a fineness ratio of 1 (ratio of bell height to bell diameter)
R
Complex relationships between scale, morphology, and frequency lead to optimized forward swimming speeds for a particular bell composition, stemming from intricate vortex wake topology, interactions, and fluid mixing. Lastly, we offer
Thorough 2D parameter subspace explorations illustrated optimal parameter combinations in which give rise to enhanced swimming performance. All performance metrics indicated a higher sensitivity to bell actuation frequency than fluid scale or contraction phase kinematics, via Sobol sensitivity analysis, on a high performance parameter subspace. Moreover, Pareto-like fronts were identified in the overall performance space involving the cost of transport and forward swimming speed. Patterns emerged within these performance spaces when highlighting different parameter regions, which complemented the global sensitivity results. Lastly,
R
jellyfish locomotion model
model for jellyfish locomotion is offered