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中文核心期刊

预置气泡对近壁空化的防护特性与智能预测

PROTECTIVE CHARACTERISTICS AND INTELLIGENT PREDICTION OF NEAR-WALL CAVITATION WITH PRE-EXISTING BUBBLES

  • 摘要: 空化侵蚀在海洋船舶, 管道运输中广泛存在, 严重危害设备的使用寿命. 如何减轻空化侵蚀一直是热点问题. 本文使用实验方法, 通过在壁面上预置空气泡, 来控制空化射流方向, 从而达到防止空化侵蚀的效果. 重点研究了预置单气泡、双气泡与空化泡之间的耦合动力学过程以及射流的方向改变规律, 并构建多层感知器(MLP)模型, 来对不同空化泡阵列的空化防护范围进行智能预测. 结果表明, 空化泡在预置气泡附近的溃灭模式分为三种: 自由表面主导模式、固壁主导模式、弱作用模式. 自由表面主导模式下, 空化泡由于气泡的影响, 溃灭射流方向远离固壁, 大大减轻了空化侵蚀的程度, 因此发生该模式的区域被称为预置气泡的有效防护区域, 预置单气泡的有效防护区域呈新月状. 双气泡布局在空泡溃灭过程中展现了更强的耦合机制, 然而增加气泡数量并不会增强气泡的垂直壁面方向上的防护强度, 但由于气泡覆盖的面积增加, 空化防护区域也线性增大. MLP模型具备良好的分类精度与泛化能力, 能够准确预测不同气泡阵列的空化防护区域, 为实际复杂工况下防护效果的评估与优化提供了智能化、数据驱动的解决方案.

     

    Abstract: Cavitation erosion is widespread in marine vessels and pipeline transportation, posing a serious threat to equipment service life. Mitigating cavitation erosion has long been a research focus. This paper employs an experimental method by pre-setting air bubbles on the wall to control the direction of cavitation jets, thereby achieving the effect of preventing cavitation erosion. The study focuses on the coupled dynamics between pre-set single bubbles, double bubbles, and cavitation bubbles, as well as the patterns of jet direction alteration. A Multilayer Perceptron (MLP) model is constructed to intelligently predict the protective range of cavitation for different cavitation bubble arrays. The results indicate that the collapse modes of a cavitation bubble near pre-set bubbles can be classified into three types: the free-surface dominated mode, the solid-wall dominated mode, and the weak interaction mode. In the free-surface dominated mode, influenced by the bubble, the direction of the collapse jet is away from the solid wall, significantly reducing the degree of cavitation erosion. Consequently, the region where this mode occurs is defined as the effective protective region of the pre-set bubble, which is crescent-shaped for a single pre-set bubble. The dual-bubble configuration exhibits a stronger coupling mechanism during the bubble collapse process. However, increasing the number of bubbles does not enhance the protective intensity in the direction perpendicular to the wall. Nevertheless, due to the increased area covered by the bubbles, the cavitation protective region expands linearly. The MLP model demonstrates good classification accuracy and generalization ability, enabling accurate prediction of cavitation protective regions for various bubble arrays. This provides an intelligent, data-driven solution for the evaluation and optimization of protective effects under complex practical conditions.

     

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