Ning Chen, Ruigang Zhang, Quansheng Liu, Zhaodong Ding
{"title":"基于深度强化学习的主动控制,用于减少三个等边三角形圆柱体的阻力","authors":"Ning Chen, Ruigang Zhang, Quansheng Liu, Zhaodong Ding","doi":"10.1016/j.euromechflu.2023.12.001","DOIUrl":null,"url":null,"abstract":"<div><p>Deep reinforcement learning (DRL) is gaining attention as a machine learning tool for effective active control strategy development. This study focuses on employing DRL to develop an efficient active control strategy for flow around three circular cylinders arranged in an equilateral-triangular configuration in a two-dimensional channel. The analysis of control outcomes reveals that DRL induces vortices of varying sizes between the cylinders, resulting in large elliptical vortices at the rear. This enhancement in flow stability leads to a significant 40.40% reduction in cylinder drag force and an approximate 8.23% decrease in overall drag oscillations. Our research represents a pioneering application of DRL for stabilizing complex flow around multiple cylinders, yielding remarkable control effectiveness. The noteworthy outcomes in controlling the stability of complex flows highlight the capability of DRL to grasp intricate nonlinear flow dynamics, showcasing its potential for investigating active control strategies within complex nonlinear systems.</p></div>","PeriodicalId":11985,"journal":{"name":"European Journal of Mechanics B-fluids","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deep reinforcement learning-based active control for drag reduction of three equilateral-triangular circular cylinders\",\"authors\":\"Ning Chen, Ruigang Zhang, Quansheng Liu, Zhaodong Ding\",\"doi\":\"10.1016/j.euromechflu.2023.12.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Deep reinforcement learning (DRL) is gaining attention as a machine learning tool for effective active control strategy development. This study focuses on employing DRL to develop an efficient active control strategy for flow around three circular cylinders arranged in an equilateral-triangular configuration in a two-dimensional channel. The analysis of control outcomes reveals that DRL induces vortices of varying sizes between the cylinders, resulting in large elliptical vortices at the rear. This enhancement in flow stability leads to a significant 40.40% reduction in cylinder drag force and an approximate 8.23% decrease in overall drag oscillations. Our research represents a pioneering application of DRL for stabilizing complex flow around multiple cylinders, yielding remarkable control effectiveness. The noteworthy outcomes in controlling the stability of complex flows highlight the capability of DRL to grasp intricate nonlinear flow dynamics, showcasing its potential for investigating active control strategies within complex nonlinear systems.</p></div>\",\"PeriodicalId\":11985,\"journal\":{\"name\":\"European Journal of Mechanics B-fluids\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2023-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Mechanics B-fluids\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0997754623001747\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MECHANICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Mechanics B-fluids","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0997754623001747","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MECHANICS","Score":null,"Total":0}
Deep reinforcement learning-based active control for drag reduction of three equilateral-triangular circular cylinders
Deep reinforcement learning (DRL) is gaining attention as a machine learning tool for effective active control strategy development. This study focuses on employing DRL to develop an efficient active control strategy for flow around three circular cylinders arranged in an equilateral-triangular configuration in a two-dimensional channel. The analysis of control outcomes reveals that DRL induces vortices of varying sizes between the cylinders, resulting in large elliptical vortices at the rear. This enhancement in flow stability leads to a significant 40.40% reduction in cylinder drag force and an approximate 8.23% decrease in overall drag oscillations. Our research represents a pioneering application of DRL for stabilizing complex flow around multiple cylinders, yielding remarkable control effectiveness. The noteworthy outcomes in controlling the stability of complex flows highlight the capability of DRL to grasp intricate nonlinear flow dynamics, showcasing its potential for investigating active control strategies within complex nonlinear systems.
期刊介绍:
The European Journal of Mechanics - B/Fluids publishes papers in all fields of fluid mechanics. Although investigations in well-established areas are within the scope of the journal, recent developments and innovative ideas are particularly welcome. Theoretical, computational and experimental papers are equally welcome. Mathematical methods, be they deterministic or stochastic, analytical or numerical, will be accepted provided they serve to clarify some identifiable problems in fluid mechanics, and provided the significance of results is explained. Similarly, experimental papers must add physical insight in to the understanding of fluid mechanics.