Proceedings of the Thirty-second (2022) International Ocean and Polar Engineering Conference
Shanghai, China, June 5–10, 2022
Copyright © 2022 by the International Society of Offshore and Polar Engineers (ISOPE)
ISBN 978-1-880653-81-4; ISSN 1098-6189

www.isope.org

Numerical Simulations on Self-Propelled Fish with Turning Motion
1.

Pengfei Wang1, Ruoxin Li1,2, Chonglei Wang*,2, Chunyu Guo1

Qingdao Innovation and Development Centre of Harbin Engineering University, Qingdao, China
2. College of Shipbuilding Engineering, Harbin Engineering University, Harbin, China“maneuvering” vortex formation, and the final fish velocity wasaugmented by the strength of the second, “propulsive” vortex. Blakeand Chan (2006) presented the relationship between mass and radiususing an empirical model. Accordingly, turning radius scales to the0.37 power of mass. Based on the kinematic data from experimental
observation, Yang, Wu and Tong (2009) numerically simulated theroutine turns of a Koi carp and found out two kinds of basic turningmode, i.e., single-beat turn and cruising turn. It was noted that singlebeat turns were more efficient. Xin and Wu (2018) analysed therotational moment in favor of turning motion. Results showed that the3D bionic fish can turn quickly by primarily using the directional
control strategy of the head. Wang and Yu (2019) established models
of zebrafish’s C-turn and C-escape and they found that the duration had
a significant influence on escape velocity and energy consumption.
Both the C-turn and C-escape have two stages, bending of the body andbackward flapping of the tail. The difference is that C-escape has
reversed bending while C-turn only flap back to the straight-line state
at most. Feng (2020) numerically simulated the 3-DoF C-turn
maneuvering of a tuna-like swimmer with the self-propelled motion.
The simulations confirmed that two vortex pairs were shed in theturning maneuver of Thunniform swimmers. Based on the kinematic
equations of C-turn, Li, Gu and Yao (2021) numerically analyzed thehydrodynamic of the two tunas with erected and depressed median finsduring the self-propelled motion. The results illustrated that themorphology of the median fins had a great influence on hydrodynamics
and flow field structure during C-turn behaviors.

ABSTRACTIn this work, the turning motion of fish is numerically studied. It aims
at finding out the factors that could affect the turning performance offish. A NACA0012 airfoil is selected as a simplified yet representativemodel. The deformation of fish body is prescribed and its turning
motion is fully induced by the fluid-structure interaction (FSI).
Numerical simulations are carried out under a series of operating
conditions by varying the prescribed motion amplitude, frequency, andangular velocity of the fish. Results show that the turning motion of thefish head is affected by a few factors. A greater angular velocity leads
to a smaller turning radius. Moreover, reducing the frequency of thefish tail and increasing the undulating amplitude will also reduce theturning radius.

KEY WORDS: CFD; Biomimetic flow; Maneuvering; FSI; Turning
motion.

INTRODUCTION
At present, propellers are used for most of the underwater vehicles. It
has some disadvantages such as large noise and low flexibility. The
new fish-like underwater robots could learn from fish make use ofcomplicated vortices and adapt their shape to achieve optimal outcomes
instinctively. Therefore, it is interesting to learn how a fish could avoid
unexpected obstacles with few efforts.

With the increasing numbers of developed fish-like robots, two
shortcomings are obvious, i.e., the speed of a robotic fish is notcomparable to the speed of a real fish, and the man-made robots are notas agile as real fish. A typical example is that the gyration radius of therobotic fish is usually much larger than that of a real fish when it turns
around. Thus, comprehensive investigations on the factors that could
affect the turning performance of fish is necessary.

High maneuverability of fish shows up in its gyration radius, which isless than one body position. The hydrodynamic performance of fishturning was first examined by Weihs (1972). He modelled fish turning
using the Lighthill’s Large-Amplitude Slender-Body Theory.
Sakakibara, Nakagawa and Yoshida (2004) used Stereo-PIV to measure
the three-component velocity distribution around a live fish, and theside jet shed against the swept tail during turning was evident in theresults. Jing, Xin and Lu (2004) analysed the hydrodynamic of C-start.
They found that three stages were contained in the C-start process andthe change of direction mainly relied on the flap of caudal fin. Epps andTechet (2010) illuminated the formation of two distinct vortices during
the turn by using fully time-resolved (500 Hz) PIV. Results showedthat the fish body rotation was facilitated by the initial, orIn this article, the numerical simulation will be carried out to study thecruising turn motion modes of a 2D fish. As the fish's heading changes,
it turns into a turning motion while swimming forward. The purpose ofthis paper is to evaluate the influence of rotational angular velocity andundulating frequency and amplitude on the turning of robotic fish.

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