  Jellyfish (Medusozoa) have been deemed the most energy-efficient animals in
the world. Their bell morphology and relatively simple nervous systems make
them attractive to robotocists. Although, the science community has devoted
much attention to understanding their swimming performance, there is still much
to be learned about the jet propulsive locomotive gait displayed by prolate
jellyfish. Traditionally, computational scientists have assumed uniform duty
cycle kinematics when computationally modeling jellyfish locomotion. In this
study we used fluid-structure interaction modeling to determine possible
enhancements in performance from shuffling different duty cycles together
across multiple Reynolds numbers and contraction frequencies. Increases in
speed and reductions in cost of transport were observed as high as 80% and 50%,
respectively. Generally, the net effects were greater for cases involving lower
contraction frequencies. Overall, robust duty cycle combinations were
determined that led to enhanced or impeded performance.
