Numerical simulations are employed to study hydrodynamic interactions between two-dimensional fish-like bodies under a traveling wavy lateral motion in high-density diamond-shaped fish schools. This study focuses on two different streamwise spacings, a dense school with 0.4 body length (BL) spacing and a sparse school with 2.0 BL spacing, respectively. An immersed-boundary-method-based incompressible Navier–Strokes flow solver is then employed to quantitatively simulate the resulting flow patterns and associated propulsive performance
of the schools. The results suggest that a fish in the dense school achieves higher thrust production and higher propulsive efficiency than that in the sparse school due to a strong wall effect from neighboring fishes. In addition, results from changing the lateral spacing in the dense school have shown that the wall effect is enhanced as the lateral spacing decreases. Flow analyses have shown that the wake pattern of
the fish swimming diagonally behind the leading fish in a dense diamond-shaped school transfers from 2S to 2P when the lateral spacing is smaller than 0.6 BL. As a result, an angled jet is produced behind the school and brings more momentum downstream. At the same time, the appearance of the trailing fish results in a stronger pressure region behind the leading fish and leads to a higher hydrodynamic performance of the leading fish in the dense school. The insights revealed from this study will contribute to understanding physical mechanisms in fish schools and providing a new swimming strategy for bio-inspired underwater swarm robots.
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Characterization of a Multifunctional Bioinspired Piezoelectric Swimmer and Energy Harvester
Fiber-based flexible piezoelectric composites with interdigitated electrodes, namely Macro-Fiber Composite (MFC) structures, strike a balance between the deformation and actuation force capabilities for effective underwater bio-inspired locomotion. These materials are also suitable for vibration-based energy harvesting toward enabling self-powered electronic components. In this work, we design, fabricate, and experimentally characterize an MFC-based bio-inspired swimmer-energy harvester platform. Following in vacuo and in air frequency response experiments, the proposed piezoelectric robotic fish platform is tested and characterized under water for its swimming performance both in free locomotion (in a large water tank) and also in a closed-loop water channel under imposed flow. In addition to swimming speed characterization under resonant actuation, hydrodynamic thrust resultant in both quiescent water and under imposed flow are quantified experimentally. We show that the proposed design easily produces thrust levels on the order of biological fish with similar dimensions. Overall it produces thrust levels higher than other smart material-based designs (such as soft material-based concepts), while offering geometric scalability and silent operation unlike large scale robotic fish platforms that use conventional and bulky actuators. The performance of this untethered swimmer platform in piezoelectric energy harvesting is also quantified by underwater base excitation experiments in a quiescent water and via vortex induced-vibration (VIV) experiments under imposed flow in a water channel. Following basic resistor sweep experiments in underwater base excitation experiments, VIV tests are conducted for cylindrical bluff body configurations of different diameters and distances from the leading edge of the energy harvesting tail portion. The resulting concept and design can find use for underwater swimmer and sensor applications such as ecological monitoring, among others.
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- Award ID(s):
- 1705739
- NSF-PAR ID:
- 10298707
- Date Published:
- Journal Name:
- ASME 2020 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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There has been an increasing interest in the use of autonomous underwater robots to monitor freshwater and marine environments. In particular, robots that propel and maneuver themselves like fish, often known as robotic fish, have emerged as mobile sensing platforms for aquatic environments. Highly nonlinear and often under-actuated dynamics of robotic fish present significant challenges in control of these robots. In this work, we propose a nonlinear model predictive control (NMPC) approach to path-following of a tail-actuated robotic fish that accommodates the nonlinear dynamics and actuation constraints while minimizing the control effort. Considering the cyclic nature of tail actuation, the control design is based on an averaged dynamic model, where the hydrodynamic force generated by tail beating is captured using Lighthill's large-amplitude elongated-body theory. A computationally efficient approach is developed to identify the model parameters based on the measured swimming and turning data for the robot. With the tail beat frequency fixed, the bias and amplitude of the tail oscillation are treated as physical variables to be manipulated, which are related to the control inputs via a nonlinear map. A control projection method is introduced to accommodate the sector-shaped constraints of the control inputs while minimizing the optimization complexity in solving the NMPC problem. Both simulation and experimental results support the efficacy of the proposed approach. In particular, the advantages of the control projection method are shown via comparison with alternative approaches.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1115/SMASIS2020-2444
