Reducing flow fluctuation using deep reinforcement learning with a CNN-based flow feature model

doi:10.1016/j.oceaneng.2024.118089

CORC > 力学研究所 > 中国科学院力学研究所 > 流固耦合系统力学重点实验室(2012-)

	Reducing flow fluctuation using deep reinforcement learning with a CNN-based flow feature model
	Ye SR(叶舒然); Zhang, Zhen; Wang YW(王一伟); Huang CG(黄晨光)
刊名	OCEAN ENGINEERING
	2024-08-15
卷号	306 页码:10
关键词	Deep reinforcement learning Flow feature detection Flow around two square cylinders Position optimisation Deep learning
ISSN号	0029-8018
DOI	10.1016/j.oceaneng.2024.118089
通讯作者	Wang, Yiwei(wangyw@imech.ac.cn)
英文摘要	Flow control and shape optimisation are fundamental problems in fluid mechanics, particularly in certain scenarios involving ocean engineering. Attempts to manage the flow field via reinforcement learning are based on newly developed deep -learning techniques. By utilising an adaptive optimisation process in the flow around two square cylinders (the main square cylinder with a smaller square cylinder in the front) for the position of the front square cylinder, the flow state that minimises the oscillation of the flow field in the wake can be obtained through deep reinforcement learning. Furthermore, as the training process for this reinforcement learning is time consuming, the flow simulation component of the process is replaced with a feature detection model based on a convolutional neural network, which effectively accelerates the training process. This approach to simulating the optimal position -finding procedure with acceleration can be extended to other similar situations and practical engineering projects.
分类号	一类
资助项目	National Natural Science Foundation of China (NSFC)[12302514] ; National Natural Science Foundation of China (NSFC)[12202291]
WOS关键词	SQUARE CYLINDER
WOS研究方向	Engineering ; Oceanography
语种	英语
WOS记录号	WOS:001240669700001
资助机构	National Natural Science Foundation of China (NSFC)
其他责任者	Wang, Yiwei
内容类型	期刊论文
源URL	[http://dspace.imech.ac.cn/handle/311007/95560]
专题	力学研究所_流固耦合系统力学重点实验室(2012-)
推荐引用方式 GB/T 7714	Ye SR,Zhang, Zhen,Wang YW,et al. Reducing flow fluctuation using deep reinforcement learning with a CNN-based flow feature model[J]. OCEAN ENGINEERING,2024,306:10.
APA	叶舒然,Zhang, Zhen,王一伟,&黄晨光.(2024).Reducing flow fluctuation using deep reinforcement learning with a CNN-based flow feature model.OCEAN ENGINEERING,306,10.
MLA	叶舒然,et al."Reducing flow fluctuation using deep reinforcement learning with a CNN-based flow feature model".OCEAN ENGINEERING 306(2024):10.