Quasi-static Modeling of Feeding Behavior in Aplysia Californica.

Behaviors that are produced solely through geometrically complex three-dimensional interactions of soft-tissue muscular elements, and which do not move rigid articulated skeletal elements, are a challenge to mechanically model. This complexity often leads to simulations requiring substantial computational time. We discuss how using a quasi-static approach can greatly reduce the computational time required to model slow-moving soft-tissue structures, and then demonstrate our technique using the biomechanics of feeding behavior by the marine mollusc, Aplysia californica. We used a conventional 2nd order (from Newton's equations), forward dynamic model, which required 14 s to simulate 1 s of feeding behavior. We then used a quasi-static reformulation of the same model, which only required 0.35 s to perform the same task (a 40-fold improvement in computation speed). Lastly, we re-coded the quasi-static model in Python to further increase computation speed another 3-fold, creating a model that required just 0.12 s to model 1 s of feeding behavior. Both quasi-static models produce results that are nearly indistinguishable from the original 2nd order model, showing that quasi-static formulations can greatly increase the computation speed without sacrificing model accuracy.