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Ship Design and Performance Issue
Research progress on the wake of underwater vehicles
Chinese Journal of Ship Research 2026, 21(2): 266-277
Published: 29 September 2025
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The wake characteristics of underwater vehicles during navigation are influenced by factors such as the intensity of ocean stratification, free surface effects, and unsteady motion, making them detectable and posing challenges to their stealth. This paper systematically reviews the latest research progress on underwater vehicle wakes, focusing on three key aspects: theoretical modeling, experimental research, and numerical simulation. It discusses the wake generation mechanisms, evolution patterns, and key influencing factors in stratified flows, highlighting the limitations of existing models in describing complex stratified structures, nonlinear effects, and turbulent dissipation. The paper proposes the future development of high-precision coupled models, multi-physics experimental databases, and intelligent wake control algorithms. Additionally, it explores the current state and future directions of wake detection and suppression technologies, aiming to provide insights for optimizing underwater vehicle design, enhancing stealth capabilities, and advancing efficient detection technologies.

Issue
Review of research on ship flow field measurement technology
Chinese Journal of Ship Research 2022, 17(5): 103-115
Published: 21 September 2022
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The refined description of the flow field information around a ship can provide feedback on the internal essence of the ship's macroscopic hydrodynamic performance from the perspective of the flow mechanism, and high-quality flow field measurement technology is a necessary means of ensuring such a refined description of the flow field. Based on the engineering requirements of ship flow field measurement, the current development status of flow field measurement technology is summarized according to its technical characteristics, and the applications and characteristics of each method are described in detail. The existing flow field measurement methods still have many problems that need to be solved. The exploration of hardware upgrading, technology integration, algorithm optimization, function expansion, data assimilation and machine learning may promote the rapid development of flow field measurement technology in the direction of comprehensiveness, specialization and efficiency.

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