Simulation of inertial aquatic swimmers requires fluid structure interactions with temporal body geometry deformation. In practice, his results in a change of the computational domain boundaries that represent the ”swimmer.” These simulations are traditionally done sing body-fitted mesh and mesh morphing methods, but have drawbacks of negative cell volumes and small time-steps to account for the complex swimming motion. In contrast, the overset mesh method, also provided by OpenFOAM®, overcomes most of the drawbacks of the mesh morphing method at the expense of interpolation error. The current OpenFOAM® overset motion library only supports rigid body motion and cannot be used to resolve a body undergoing undulation. A modified motion solver is presented that allows for the complex mesh motion of an overset mesh for four body-caudal fin (BCF) virtual swimmers. The results of this solver are compared with published data of body-fitted meshes. The effect of different simulation parameters (including number of solving iterations, time delay, and temporal resolution) is investigated. Additionally, a novel simulation and comparison of the Ostraciiform locomotion mode with Anguilliform, Carangiform, and Thunniform modes are made investigating the wake, drag and lift. It is concluded that fish undulation has a marked effect on reducing lift generation. Lastly, a comparison of turbulence models (Spalart-Allmaras, k − ω SST, and k − kL − ω) at multiple Reynolds numbers shows that all three models have similar performance at lower Reynolds numbers but diverge at higher numbers.
A useful measure of efficiency of transport in aquatic animals and autonomous underwater vehicles is cost of transport. Often, cost of transport data on specific animals or platforms is not readily available or does not fit specific use cases, but images are readily available. In this work, we present a methodology to synthesize such data without the need for a specimen or laboratory tests. We propose a computer vision in a methodology called Ika-Fit to determine important physical characteristics, such as surface area, slenderness ratio, and mass, that are used for a cost of transport model. The Ika-Fit method provides a good estimation of parameters when compared to biological data and robotic platforms. These parameters are estimated for existing engineered systems, and the model is compared to published data; the model is found to demonstrate higher accuracy using fewer parameters in estimating cost of transport over existing methods.
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