本文主要探討具歪斜(Skew)以及偏斜(Rake)之FRP船用螺槳,經疊層最佳化後,對螺槳性能的影響。 基因演算法適合FRP的疊層角度這種多變數、離散變數等最佳化的問題,但計算量十分龐大;若利用反應表面法結合基因演算法,先得到設計變數與最終反應值之間的關係,然後以反應表面的函數取代原來費時的計算,可節省大量的計算時間;而在基因演算法中加入局部搜尋,以局部的反應表面取代原來的計算,能提高搜尋的準確度。 本文結合流力計算程式PSF2與結構計算程式ABAQUS,得到螺槳性能;利用上述改良式基因演算法尋找最佳疊層的角度與順序,進一步使用預變形設計調整螺槳外型。最後進行FRP螺槳性能實驗,以碳纖維複合材料製作螺槳,在空蝕水槽中運轉以量測推力、扭力等螺槳性能,並以攝影的方式觀測螺葉在軸向的變形量印證計算結果。由實驗可得知當入流速度變小時,螺距變小,螺槳扭力係數也隨之下降,與計算結果吻合。經疊層最佳化的複合材料螺槳的性能的確較傳統金屬材料螺槳優越。
This thesis investigated the performance of highly-skewed and highly-raked FRP marine propellers with optimization of arranging the stacking sequence. The application of genetic algorithms(GA) to the stacking sequence of composite laminates has grown in recent years, but GA always takes a lot of time because of huge calculation. To reduce calculation time, we insert a local improvement into GA, and the calculation by finite element analysis is replaced by a regression model. The GA with local improvement is applied to the composite propeller. It converges much sooner than a standard GA and the calculation time greatly reduced. So this thesis uses the improved GA to search for the optimal stacking sequence. We get the performance and the deformation of FRP propeller by Combining with PSF2, ABAQUS, and the improved GA. The pre-deformed propellers conform to the demands of optimization. Finally, an experiment is made to verify the result of calculation. The performance and the deformation of the propeller are found to be close to the result of the calculation in this study. The pitch of the propeller is reduced when the axial inflow velocity is reduced. The optimized composite material propeller outperforms traditional metal propellers.
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