螺槳跡流幾何模型於小板法之參數化研究

Abstract

在勢流理論中，流場可藉由求解奇異點分布進行解析，實體幾何通常以源(source)與偶源(doublet)表示。然而，對於升力體，則需額外引入由偶源所組成的跡流（wake）結構進入計算。本研究旨在探討螺槳跡流幾何參數化後，各參數對面元法（panel method）計算螺槳單獨螺槳試驗的影響。 分析部分首先進行幾何參數的敏感度分析，以判斷對計算結果影響最大的參數，接著針對幾何參數進行大範圍變化分析以了解整體參數的作用與趨勢。最後將不同的螺槳跡流幾何模型以小板法計算並與官方實驗數據進行比較。 參數分析結果顯示，跡流幾何的螺距比對性能計算的影響最為顯著，其次為流縮比，高負載相對於低負載對跡流幾何參數較敏感。基本上所有的幾何參數對結果的影響皆呈現單調變化，但幾何參數的調整對整體的壓力分佈與環流分布影響有限，難以直接滿足Kutta Condition。將不同的跡流幾何模型與實驗資料進行比較，低負載時所有的跡流模型與實驗值符合且差異不大，表示螺槳在低負載時對跡流幾何不敏感，但隨著負載增加，跡流需隨負載變化且以提升預測準確性。

In potential flow theory, the flow field can be resolved through the distribution of singularities, with solid boundaries typically represented using sources and doublets. However, for lifting bodies, an additional wake structure composed of doublets must be introduced into the computation. This study examines the influence of propeller wake geometry on the panel method's prediction of open-water performance. The analysis begins with a sensitivity study on wake geometric parameters to identify which parameter most significantly affects the computational results. A large parametric variation is then conducted to examine the influence and trends of the parameters. Finally, different wake models are evaluated using the panel method and compared against official experimental data. The parameter analysis reveals that the ultimate wake pitch ratio has the most significant impact on performance predictions, followed by the contraction ratio. The geometry is also found to be more sensitive to parameter changes under high loading conditions. In general, geometric parameters exhibit monotonic effects on the results; however, their influence on overall pressure and circulation distributions is limited, making it difficult to directly satisfy the Kutta condition through parameter tuning alone. When comparing the wake models with experimental data, all models demonstrate good agreement under low loading conditions, indicating that propeller performance is less sensitive to wake geometry in such regimes. As the loading increases, the wake must be adjusted accordingly to improve prediction accuracy.