論文名稱：三維拍翼昆蟲在陣風條件下滯空飛行之數值模擬		
校系所組別：淡江大學航空太空工程學系熱流組
畢業時間及提要別：102學年度第2學期碩士論文提要
研究生：杭亮同								指導教授：宛 同 
論文提要內容：
    隨著不斷創新的研究及技術上的突破，航太科技正飛快的發展，其中拍撲翼為目前熱門且新穎的研究題目之一。重量輕、靈巧性強、不斷隨時間改變的升阻力皆是拍撲翼主要的特色。根據達爾文的生物演化論，我們可以粗略的認定每種生物行為都是一種最佳化的結果，故將仿生學結合數值模擬的研究則顯得相對重要。許多學者皆投入心力於拍撲翼的研究但大都只考慮單純的懸停及飛行而忽略大氣環境的影響。本研究團隊長期研究天氣影響之因素，累積豐富的分析經驗在不同的氣候環境，在本論文中吾人將探討不同陣風對於拍撲翼空氣動力的影響。此處我們是利用商用軟體ANSYS/FLUNET之動態網格機制來模擬翅膀的拍動，再利用C++編輯UDF結合Solver去模擬陣風下飛行的空氣動力性能。
    本研究首先是先與學長及Wang, J.的研究論文所提到的二維板片八字形運動做比對驗證的工作。完成二維的驗證後再根據Dudley Robert的生物實驗研究資料選用Morpho peleides 此種蝴蝶，利用繪圖軟體PRO-E 繪製擬真三維蝴蝶外形並且利用商用軟體Gambit及ANSYS產生動態網格再結合UDF模擬出蝴蝶拍動飛行。之後參考Lian,  Y.及Yang, G.等人之研究分別建立單頻率其多頻率之模擬風場進而分析三維蝴蝶在不同風場之下的空氣動力性能。根據吾人可知: 蝴蝶飛行受上下方向風場作用的影響極為劇烈，其升力係數差距可達十倍以上；由於吾人固定蝴蝶身體的俯仰角，故在定量分析上會存在誤差，吾人認為這來自於模擬前不自然的假設，但在定性的物理分析上，不論是壓力及渦度上的結果皆可充分詮釋蝴蝶的空氣動力性能。若是未來加上蝴蝶飛行時身體俯仰角的改變以及柔性結構的考量，將會增加計算結果的精準度。
關鍵詞: 三維拍撲翼，動態網格，風場，UDF

Title of Thesis:                                   Total pages: 76
  Numerical simulation of 3-D flapping-wing insect's hovering flight         under gust wind situations
Keywords: 3-D Flapping Wing, Dynamic Mesh, Gust, UDF
Name of Institute: Graduate Institute of Aerospace Engineering, Tamkang University
Graduate Date: June 2014			  	     Degree Conferred: Master
Name of Student: Liang-Tong Hang           Advisor: Dr. Tung Wan
  杭亮同                              宛 同 博士

Abstract:
With advance of science and technology, the development of aerospace technology progress fast. Flapping-wing is a popular and innovative topic. Based on Darwin's theory of evolution; we can have a general interpretation of each biological behavior patterns are the results of optimization. So it is important to combines aerodynamics and Bionics. Many researchers put effort into study the unsteady aerodynamics and flapping flight but study in flapping-wing Affected by atmospheric environment is much less. Our research team has studied the impact of weather factors for a long time and extensive lots experience in the analysis of different climatic conditions. In this thesis, we will discuss effect of flapping wings for aerodynamics in different gust. Here we use the dynamic grid mechanism of commercial software ANSYS / FLUNET to simulate flapping-wings, edit UDF in C++ and combine Solver to analysis aerodynamic performance under gust. First, we finish the validation of 2-D elliptic flapping wing section with Wang, J. We build 3D model butterfly which species is Morpho peleides Butler by PRO-E. From the morphological data of Morpho peleides is measured by Dudley. We generate mesh by Gambit and ANSYS and use dynamic mesh mechanism of ANSYS / FLUNET to simulate the butterfly forward flight. According to Liang and Yang, we create two type of the gust function with single and multiple frequencies. We analysis the butterfly under different gust and different directions and find lift coefficient is sensitive for the gust from top and bottom. The mean value of lift coefficient can be increased more than tenfold compared with the case without wind effects. And since the assumptions we make, our results may occur tolerance in quantitative values but it is worth referencing in Qualitative physical interpretation. If possible, consider the pitching oscillation of body and the flapping-wing with flexible in the future will improve accuracy of the results.

Contents
Abstract:	III
Contents	V
List of Table	VII
List of Figure	VIII
Nomenclatures	XI
Chapter 1 Introduction	13
1.1 Bionics	13
1.2 Flapping-Wing and Micro Air Vehicle (MAV)	14
Chapter 2 Literature Review	16
2-1 Flapping-Wing Vehicle	16
2-2 Power Spectral Density Form of Gusts	18
2-3 Realistic Gust Winds	20
Chapter 3 Numerical Modeling	24
3-1 Governing Equations	24
3-2 Preprocessing	25
3-3 Modeling and Mesh System	26
3-4 UDF and Gust Function	28
3-5 Fluent Solver	29
Chapter 4 Results and Discussions	37
4-1 Validation of 2-D and 3-D flapping-wing	37
4-2 Simulation of 2-D Flapping-wing	40
4-3 Simulation of 3-D Flapping-wing	41
Chapter 5 Conclusions	67
References	69
Appendix A	72
Appendix B	74
Appendix C	77
List of Table
Table3.1 Morphological data of Morpho peleides measured by Dudley	32
Table 4.1 The number of structured and unstructured grids	45
Element number	45
Table 4.2 Classification of different number of grids and grid type	45
Table 4.3 The mean lift and drag coefficient	45
Table 4.4 The mean lift and drag coefficient compared with case 1	45
Table 4.5 The mean lift and drag coefficient without gusty effect	45
Table 4.6 Classification of gusty effect and gust direction	46
Table 4.7 Classification of simulate real wind in different directions	46
List of Figure
Fig. 1.1 A mechanical wing device - ca. 1485 [1]	15
Fig. 2.1 Gustave Trouve’s flapping-wing vehicle in 1870 [17]	21
Fig. 2.2 A. M. Lippisch’s flapping-wing vehicle (1929) [17]	21
Fig. 2.3 Adalbert Schmid flapping-wing vehicle (1942) [17]	22
Fig. 2.4 Emil Hartman’s driving force flapping-wing vehicle (1959) [17]	22
Fig. 2.5 University of Toronto flapping-wing vehicle (1991) [17]	22
Fig. 2.6 Flapper flow visualization with smoke released from the leading edge wing at different time [11]	23
Fig. 3.1 The process of leading edge vortex generation [21]	32
Fig. 3.2 The size of Various parts of the the butterfly	33
Fig. 3.3 Nature butterfly compare with butterfly model created by PRO-E	34
Fig. 3.4 The mesh and the calculating field of the butterfly	35
Fig. 3.5 The symmetry face at computational domain	35
Fig. 3.6 1-D control volume [18]	36
Fig. 3.7 The mesh near the butterfly field	36
Fig. 4.1 a, Grids and calculated domain b, grids near the flapping wing field	47
Fig. 4.2 The positions of flapping wing in one period [12]	48
Fig. 4.3 Lift vs. period comparing with references [12][23]	48
Fig. 4.4 Lift coefficient vs. period comparing with references [23]	49
Fig. 4.5 Stroke amplitude in flapping motion	49
Fig. 4.6 Grid convergence with CL and CD in four cycles	50
Fig. 4.7 Grid convergence with CL and CD in one cycle	50
Fig. 4.8 Lift coefficient compared with reference in one cycle	51
Fig. 4.9 Vorticity contour at different instants in one cycle	52
Fig. 4.10 Pressure contour at different instants in one cycle	53
Fig. 4.11 Lift and Drag coefficient in first ten periods	54
Fig. 4.12 The curve of sinusoidal wave function	55
Fig. 4.13 Lift coefficient in periods	55
Fig. 4.14 Drag coefficient in periods	56
Fig. 4.15 Lift coefficient in five cycles	56
Fig. 4.16 Drag coefficient in five cycles	57
Fig.4.17 The stream line of the wing	57
Fig. 4.18 Pressure contour of different instants in a cycle	59
Fig. 4.19 The curve of gust function in ten seconds	60
Fig. 4.20 Lift coefficient in ten second affected by gust wind from bottom	60
Fig. 4.21 Drag coefficient in ten second affected by gust wind from bottom	61
Fig. 4.22 The vorticity contour at 0.25 t/T and 0.75 t/T	62
Fig. 4.23 Lift coefficient in ten second affected by gust wind from top	62
Fig. 4.24 Drag coefficient in ten second affected by gust wind from top	63
Fig. 4.25 The vorticity contour at 0.25 t/T and 0.75 t/T	64
Fig. 26 wind function with multiple frequencies	64
Fig. 27 Lift coefficient in 5.5 seconds	65
Fig. 28 Drag coefficient in 5.5 seconds	65
Fig. 29 Lift coefficient in 10.7 seconds	66
Fig. 30 Drag coefficient in 10.7 seconds	66


 

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