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 study on an actively controlled flat plate breakwater
Hongjian Liang a, b, c, Hao Qin *, a, b, c, Lin Mu a, daSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, Chinab
College of Marine Science and Technology, China University of Geosciences, Wuhan, ChinacShenzhen Research Institute, China University of Geosciences, Shenzhen, Chinad College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China

breakwater under the consideration of incident wave angle, relative plate
length and wave height based on physical model tests, indicating thatoblique incident waves produced different wave patterns in the two-sided
fluid regimes of the multiple-layer breakwater significantly comparedwith positive incidents waves. Qin et al. (2017) investigated theinteraction between Peregrine breather based freak waves and horizontal
deck structures numerically, in which the phenomena, wave loads andstructural response were obtained. He et al. (2018) numerically studied
the effect of plate submergence on the wave-heaving plate interactions
based on the smoothed particle hydrodynamics (SPH) method, which
points out that the heaving plates are effective in wave dissipation.
However, it should be pointed out that the wave-dissipation effect of
fixed plates is restricted by the relationship between wave conditions andthe position of plates. As for heaving plates, similarly, to obtain a low
wave transmission coefficient, the optimal spring stiffness of the heaving
plate must be related to the incident wave frequency. As a result, inreality, it is difficult for either fixed and heaving plates to adapt thecomplex and changeable wave conditions.

ABSTRACT
Flat plate breakwater is widely studied for wave dissipation due to its
good performance near the water surface and low cost in deep-water area.
However, fixed flat plate suffers from low adaptability problem due tovarious incoming waves. This paper studies the wave dissipation of asubmerged movable flat plate against regular waves, in which the plateis actively controllable so as to maximize the wave dissipation ability.
Simulations of the interaction between regular waves and the active
controlled plate are conducted in an in-house solver, while the deep
reinforcement learning (DRL) method is applied to control the platemotion.

KEY WORDS: Wave dissipation, Flat plate breakwater, Deep
reinforcement learning, Active controlling
INTRODUCTION
Ocean waves usually create a huge impact on the numerous costal,
offshore and marine structures, resulting in structural damages anddestructions. In order to protect structures along the shoreline and off thecoast, great efforts have been made on the interaction between ocean
wave and structures over the past years. Many types of breakwaters havebeen developed and analyzed by researchers to be used under different
environmental conditions in recent decades. Among various breakwaters,
plate-type breakwaters are favorable since most of the wave energy isconcentrated near the water surface. Lo and Liu (2013) investigated thewave scattering of a solitary wave traveling over a submerged horizontal
plate experimentally, numerically and analytically, where the fluid field,
surface elevation and wave loads were calculated and compared. Koraim(2013) studied the hydrodynamic efficiency of the breakwater consistingof one or more horizontal rows of half pipes suspended on supporting
piles, showing that the proposed breakwater system was more efficientthan the smooth plate type by about 5 to 25%. Wang et al. (2016)
proposed a kind of arc plate breakwater made up of several arc plates
suspended on supporting piles and explored the wave damping
performance of the breakwater. The performance of the arc plate
breakwater was shown to be better than the performance of a similarbreakwater with several horizontal plates. Gu and Zhang (2016), Gu etal. (2017) studied the wave-dissipating performance of a twin-plate

Recently, the rapid development of artificial intelligence (AI) has
provided us with new ideas to deal with the nonlinear relationshipbetween plates and waves. Data-driven and learning-based approaches
have been applied to discover the control strategy in model-free control
technologies, among which deep reinforcement learning (DRL) is themost popular one. For example, Ma et al. (2018) achieved to balance arigid body at a fixed position with several fluid jets through DRL
algorithm. Fan et al. (2020) studied the bluff body flow control problems
and proved the effectiveness of DRL algorithm in experimental fluid
mechanics. Qin et al. (2021) focus on the active flow control (AFC) of
the flow over a circular cylinder with synthetic jets through DRL byimplementing a reward function based on dynamic mode decomposition(DMD). Ren et al. (2021) performed the first Proximal Policy
Optimization (PPO) DRL trained AFC in weakly turbulent conditions,which reduced the drag and mitigate lift fluctuations experienced by acircular cylinder at Re = 1000. Currently, AI, especially DRL, is mainly
used for active control, which is embodied as AFC in Computational
Fluid Dynamics (CFD).
More significant, Xie and Zhao (2021) applied a DRL framework to findan optimal control strategy to suppress tank sloshing with two active-2541