Hydrodynamic cloaks, a type of metamaterials possessing zero-drag properties, show fascinating potential for aerospace, marine engineering, and high-speed transportation. However, achieving zero drag with hydrodynamic cloaks in viscous flows is challenged by the complexity of the Navier–Stokes equations. This study designs spherical hydrodynamic cloaks based on machine learning, which allow objects to move in a viscous fluid without disturbing the flow fields. These cloaks merely require the supply of uniform external forces, unaided by metamaterials, allowing objects wrapped in the cloak to move unimpeded through viscous flow fields. Numerical simulations show that these cloaks provide significant drag reduction efficiency (up to 96.26%) and enhance flow stability by eliminating lift fluctuations. These findings provide new insights into flow control and expand the applicability of hydrodynamic metamaterials to high Reynolds number environments, with promising applications in multiphysics fields such as thermal-hydrodynamic coupling and acoustic-hydrodynamic coupling.
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January 2025
Research Article|
January 28 2025
Metamaterial-free, zero-drag, spherical hydrodynamic cloaks enabled by machine learning

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Hao Wang (王浩);
Hao Wang (王浩)
(Conceptualization, Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing)
1
School of Mechanical and Power Engineering, East China University of Science and Technology
; Shanghai, 200237, China
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Bin Wang (王斌)
;
Bin Wang (王斌)
a)
(Conceptualization, Funding acquisition, Supervision, Writing – review & editing)
1
School of Mechanical and Power Engineering, East China University of Science and Technology
; Shanghai, 200237, China
a)Author to whom correspondence should be addressed: [email protected]
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Neng-Zhi Yao (姚能智);
Neng-Zhi Yao (姚能智)
(Software, Validation)
1
School of Mechanical and Power Engineering, East China University of Science and Technology
; Shanghai, 200237, China
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Zhengyan Xiao (肖正衍);
Zhengyan Xiao (肖正衍)
(Software, Validation, Writing – review & editing)
1
School of Mechanical and Power Engineering, East China University of Science and Technology
; Shanghai, 200237, China
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Chen-Long Wu (吴晨龙)
;
Chen-Long Wu (吴晨龙)
(Investigation, Validation)
1
School of Mechanical and Power Engineering, East China University of Science and Technology
; Shanghai, 200237, China
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Xuesheng Wang (王学生)
;
Xuesheng Wang (王学生)
(Supervision, Writing – review & editing)
1
School of Mechanical and Power Engineering, East China University of Science and Technology
; Shanghai, 200237, China
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Xingsheng Wang (王兴胜)
Xingsheng Wang (王兴胜)
b)
(Supervision, Writing – review & editing)
2
China Special Equipment Inspection and Research Institute
, Beijing 100029, China
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Hao Wang (王浩)
1
Neng-Zhi Yao (姚能智)
1
Zhengyan Xiao (肖正衍)
1
Xingsheng Wang (王兴胜)
2,b)
1
School of Mechanical and Power Engineering, East China University of Science and Technology
; Shanghai, 200237, China
2
China Special Equipment Inspection and Research Institute
, Beijing 100029, China
a)Author to whom correspondence should be addressed: [email protected]
b)
Electronic mail: [email protected]
Physics of Fluids 37, 013633 (2025)
Article history
Received:
December 01 2024
Accepted:
December 12 2024
Connected Content
A companion article has been published:
Metamaterial-free hydrodynamic cloak design nearly eliminates drag in viscous flows
Citation
Hao Wang, Bin Wang, Neng-Zhi Yao, Zhengyan Xiao, Chen-Long Wu, Xuesheng Wang, Xingsheng Wang; Metamaterial-free, zero-drag, spherical hydrodynamic cloaks enabled by machine learning. Physics of Fluids 1 January 2025; 37 (1): 013633. https://doi.org/10.1063/5.0251301
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