Interactions between internal forces, body stiffness, and fluid environment in a neuromechanical model of lamprey swimming

Abstract

Animal movements result from a complex balance of many different forces. Muscles produce force to move the body; the body has inertial, elastic, and damping properties that may aid or oppose the muscle force; and the environment produces reaction forces back on the body. The actual motion is an emergent property of these interactions. To examine the roles of body stiffness, muscle activation, and fluid environment for swimming animals, a computational model of a lamprey was developed. The model uses an immersed boundary framework that fully couples the NavierStokes equations of fluid dynamics with an actuated, elastic body model. This is the first model at a Reynolds number appropriate for a swimming fish that captures the complete fluid-structure interaction, in which the body deforms according to both internal muscular forces and external fluid forces. Results indicate that identical muscle activation patterns can produce different kinematics depending on body stiffness, and the optimal value of stiffness for maximum acceleration is different from that for maximum steady swimming speed. Additionally, negative muscle work, observed in many fishes, emerges at higher tail beat frequencies without sensory input and may contribute to energy efficiency. Swimming fishes that can tune their body stiffness by appropriately timed muscle contractions may therefore be able to optimize the passive dynamics of their bodies to maximize peak acceleration or swimming speed.computational fluid dynamics | elasticity | locomotion

Optimal shape and motion of undulatory swimming organisms

“…As discussed earlier, the choice of performance measure for optimization is not unique. For comparison, we provide results for the minimization of power coefficients, namely of power output-based C M P ; P L mech =P 0 (used in Tytell et al [14]) and of power consumption-based C T P ; P L musc =P 0 (suggested in Yates [39]). …”

“…The model also neglects vortex shedding, lateral flow separation and viscous drag (relevant at lower Re numbers [13]). Despite these restrictions, Lighthill's model has been shown to provide sufficiently accurate values for the obtained lateral force [14,43]. It is important to point out, however, that our primary interest is in the correct scaling of quantities with Re and the proper dependence on kinematic and geometric parameters, rather than in the quantitative accuracy (requiring substantially greater computational cost).…”

“…Mathematical models of muscle behaviour during swimming have mostly been developed to study the muscle response to a given neural activation [9][10][11][12], with model parameters being often fine-tuned for particular species [12][13][14]. The actuation-response relationship varies widely among species [15][16][17], making these models unsuitable for the optimization of morphological traits of a generic organism.…”

Biological clockwork underlying adaptive rhythmic movements

“…Because of the high complexity, mathematical modeling is essential for understanding mechanisms underlying neuronal information processing in the CNS. Taking animal locomotion as a tractable focus of study, a number of models have previously been developed, ranging from neuronal circuit models for CPGs (44)(45)(46)(47) and body-fluid interactions during swimming (35,48) to integrated neuromechanical models for locomotion (49)(50)(51). An ultimate goal is to have dynamical models that are simple and amenable not only to numerical simulations but also to analytical studies, and which are fully validated by experimental data, with demonstrated predictability under perturbed conditions.…”

A fish perspective: detecting flow features while moving using an artificial lateral line in steady and unsteady flow

“…Sensors at the nose region directly in front of the eye can sense dorsalventral flows, such as those generated by vertical movements of the fish or shed vortices [4]. Bioinspired underwater robotics is one field of research that can address robotic navigational challenges and provide us insights into how animals achieve successful aquatic navigation [5][6][7][8][9].…”