臺灣博碩士論文加值系統

本研究係針對NACA0012翼剖面之性能，在等飛行高度及速度下，對不同攻角、速度進行最佳化之搜尋，以求得最大的升阻比。將熱流的應用分析軟體CFD-ACE+與另ㄧ分析軟體MATLAB工具箱內的基因演算法，做軟體應用程式的整合，計算其最佳的性能。本研究利用基因演算法中菁英、交配與突變的機制，期望能跳出區域最佳解而找到全域最佳解。應用基因演算法的原理與運算方式，搜尋最佳參數組，求得NACA0012翼剖面對應的最大升阻比之探討。
在海平面等速飛行的單一變數條件下，當其飛行速度為43.8m/s時，其對應的雷諾數為 。用前述整合的計算軟體，可得到在攻角為5.4033°，有最大的升阻比6.7782。本文亦單獨用CFD-ACE+計算0°到10°的11個不同攻角的升阻比，將此組數據用最小平方誤差法取得其多項式擬合函數，再將此函數微分並令其等於零的方程式求解，亦可估算其最大升阻比。此法得到的攻角為5.5662°，其對應的最大升阻比則為6.7314。不同的兩方法可得到相近的結果，唯基因演算法的結果較最小平方誤差法略佳。當在海面飛行時，其飛行速度與攻角均改變的雙變數條件下，將分析範圍界定為：飛行速度由0～100 m/s，攻角則由0～10°。用前述整合的計算軟體，可得到在攻角為2.8804°、飛行速度為10.0 m/s，有其相對應的最大升阻比為22.3371，得到了所需的全域最大升阻比。

In this NACA0012 airfoil performance analysis, the flight height is remained the same, and by varying its angle of attack and flight speed, the maximum lift to drag ratio can then be found. Applying the aerodynamic analysis software CFD-ACE+ in cooperation with the Genetic Algorithm toolbox in another software package MATLAB, the optimized performance are obtained. In the Genetic Algorithm process, the elite, crossover and mutation mechanisms are applied in each generation of the process. So it can avoid the local maximum solution, and find the global maximum solution.
At sea level with a constant flight speed 43.8m/s, the corresponding Reynold’s number is 3×10 . By using the integrated afore-mentioned software packages, the optimized angle of attack is found as 5.4033°, and the corresponding maximum lift to drag ratio is 6.7782. Selecting eleven angles between 0° to 10°, then calculate their lift to drag ratios by using CFD-ACE+ alone. The obtained data set is fitted to a polynomial by using the least square curve fitting method. Differentiating this polynomial and set it equals to zero, the angle of attack with the maximum lift to drag ratio can be solved. The calculated angle of attack is 5.5662°, and its maximum lift to drag ratio is 6.7314. The two different methods give a similar result, but the Genetic Algorithm provides a slightly better solution. In the second case which remains the sea level flight, but, not only the angle of attack but also the flight speed are selected as the variables. And the two variables’ ranges are set as: the flight speed and the angle of attack are between 0～100 m/s and 0～10°, respectively. Applying the same integrated software packages, the maximum lift to drag ratio is found as 22.3371 which took place at the speed of flight 10.0 m/s with a corresponding angle of attack 2.8804°. The global maximum solution is found.

Abstract..........................................................................i
摘 要........................................................................... ii
目 次...........................................................................iii
圖目錄..............................................................v
表目錄..........................................................................vi
符號表.........................................................................viii
第一章 緒論.........................................................1
第一節 研究背景.................................................1
第二節 基因演算法...............................................1
第三節 研究動機.................................................2
第四節 文獻回顧.................................................3
第五節 論文架構.................................................4
第二章 流場分析與最佳化數學模式.....................................5
第一節 流場計算升阻比分析.......................................5
第二節 統禦方程式...............................................6
第三節 紊流介紹.................................................7
第四節 NACA系列翼形剖面之設計.................................9
第五節 CFD-ACE+介紹..........................................16
第六節 基因演算法最佳化目標函數設定............................19
第三章 基因演算法理論..............................................33
第一節 基因演算法的基本架構....................................33
第二節 基因演算法之特性........................................36
第三節 基因演算法之運算量......................................38
第四章 單一變數(攻角)之最大升阻比解析..............................43
第一節 最小平方誤差法之步驟....................................43
第二節 基因演算法解析..........................................46
第五章 雙變數(攻角與速度)之最大升阻比解析..........................52
第一節 問題參數設定............................................52
第二節 圖解法..................................................52
第三節 基因演算法解析..........................................53
第六章 結論........................................................60
參考文獻...........................................................63

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