本論文旨在探討ATR72全機受到颱風外圍環流下的氣動力影響，其中包含陣風以及降雨的影響。使用CATIA繪圖軟體將ATR72全機與螺旋槳建模；匯入模擬軟體後，在推力與阻力平衡下取出巡航時的氣動力參數，並與Seeckt [1] 比較做為全機驗證；接著使用數個橋接模擬將巡航與進場做連結，每次更變一組參數，並用定量或定性的方式分析之；之後在進場模擬中加入單一飛安事件的黑盒子資料，並獲取飛機進場期間不受風雨時的氣動力參數；接著在模擬中加入當時機場自動天氣觀測系統所記錄的陣風以及雨的參數；對兩者進行分析與討論，其中飛機姿態與側向力的結果與飛安失事調查報告相符，並且飛機姿態的變化受到向上左後方翻滾的力，因此間接證明獲取氣動力參數的方法是可行的，而飛機的外型亦是極為接近的;最後，如我們所知，當飛機使用高升力裝置以及用較低的速度飛行時容易受到側風的影響，而我們藉由此研究得到該飛安事件中飛機之側向力係數與滾轉係數受側風影響的量化結果並提出建議。

This thesis discusses the aerodynamic performance of a full ATR72 configuration under the scenarios, with or without gusts and rain, which affected by the outer rain bands of a typhoon. Combined with learning concepts in the aircraft design courses and related information in aircraft manuals, the full scale ATR72 geometry with rotating propellers in clean and landing configurations are built with software, CATIA. Under the force equilibrium condition in cruising, a specific method to obtain the performance parameters is found. At first, parameters in cruising are validated with Seeckt [1] and followed by several linking cases in advance of the approaching cases with stable descent rate. One group of parameters is replaced from one to another for linking and connecting each other with qualitative and quantitative analysis. Afterward, the realistic weather data refer to the flight data recorder (FDR) and take into simulating a specific event about ATR72. Thus the approaching parameters are obtained. For gusty winds and rain conditions, this information is taken from the data of Automated Weather Observing System (AWOS) and inputted. The corresponding parameters can be compared between approaching cases with or without crosswinds and rain and providing the basis for analysis. By comparison, the parameters are changing with gusty winds and rain, and further the results of the side force and attitude are consistent with the event investigation. Then it indirectly proves that both the method for data acquisition and our ATR72 geometry are valid. Lastly, as we know, the aircraft is easier to be affected by the crosswinds while HLDs extending, and flying at a lower speed. The results of the side-force coefficient and the rolling moment coefficient are quantified to show how much it is in the situation of this event.

Contents

Abstract	III
Contents	V
List of Tables	VIII
List of Figures	IX
List of Abbreviations	XIII
List of Symbols	XV
Chapter 1 Introduction	1
   1.1 Research Background and Purpose	1
   1.2 Case Study	3
   1.3 Framework	6
Chapter 2 Literature Review	11
Chapter 3 Theoretical Foundations	16
   3.1 Governing Equations	16
   3.2 Multiple Rotating Frame	17
   3.3 Wind Manipulation	20
   3.4 DPM Model	25
   3.5 Assumptions	27
Chapter 4 Numerical Modeling	30
   4.1 Research Tools	30
   4.2 Validation Cases	30
   4.3 Geometric Modeling	39
   4.4 Grid Generation	45
   4.5 Flight Environment	48
   4.6 Boundary Conditions	49
   4.7 Solver	50
   4.8 Turbulence Model	51
   4.9 Method of Data Aquisition	51
Chapter 5 Results and Disccusions	54
Chapter 6 Conclusions	70 
References	72
Appendix I	79
Appendix II	80
Appendix III	81
Appendix IV	82

List of Figures

Fig. 1 The ATR72-500 photograph	4
Fig. 2 The pilot’s operation and flight track, flight no. GE-222 [3]	5
Fig. 3 The runway 20 VOR approach chart, Makung airport [3]	5
Fig. 4 The (a) clean and (b) landing configuration, ATR72	7
Fig. 5 The flow chart for all cases in this study	7
Fig. 6 Surface mesh, Boeing 747-200 [4]	12
Fig. 7 Pressure contours, Boeing 747-200 [4]	12
Fig. 8 Surface grid, F-111/TACT [5]	13
Fig. 9 The force and moment coefficients for M=1.6, F-111/TACT [5]	13
Fig. 10 AX-1 models of deformed and un-deformed configurations [6]	14
Fig. 11 The actuator disk model [7]	15
Fig. 12 The rotating mesh and fixed mesh [8]	15
Fig. 13 The stationary and moving reference frame [9]	17
Fig. 14 The multiple reference frame approach [9]	19
Fig. 15 The coordinate system of computational domains	20
Fig. 16 Total velocity and each component, sustained crosswind	23
Fig. 17 The output of total pure fluctuations	24
Fig. 18 Total velocity and each component, pure fluctuations	24
Fig. 19 Total velocity and each component, gusty crosswinds	25
Fig. 20 The NASA experimental model of helicopter rotor in hover [14]	31
Fig. 21 Pressure coefficient at 0.50 (a) lower and (b) upper, steady	32
Fig. 22 Pressure coefficient at 0.68 (a) lower and (b) upper, steady	32
Fig. 23 Pressure coefficient at 0.80 (a) lower and (b) upper, steady	32
Fig. 24 Pressure coefficient at 0.89 (a) lower and (b) upper, steady	33
Fig. 25 Pressure coefficient at 0.96 (a) lower and (b) upper, steady	33
Fig. 26 Pressure coefficient at 0.50 (a) lower and (b) upper, transient	33
Fig. 27 Pressure coefficient at 0.68 (a) lower and (b) upper, transient	34
Fig. 28 Pressure coefficient at 0.80 (a) lower and (b) upper, transient	34
Fig. 29 Pressure coefficient at 0.89 (a) lower and (b) upper, transient	34
Fig. 30 Pressure coefficient at 0.96 (a) lower and (b) upper, transient	35
Fig. 31 Velocity magnitude at X/C =0.96, steady	35
Fig. 32 Velocity magnitude viewed form top, steady	35
Fig. 33 The experiment model of ONERA M6 wing [15]	36
Fig. 34 The coefficient of pressure at (a) 0.20 and (b) 0.44, steady	37
Fig. 35 The coefficient of pressure at (a) 0.65 and (b) 0.80, steady	37
Fig. 36 The coefficient of pressure at (a) 0.90 and (b) 0.95, steady	37
Fig. 37 The coefficient of pressure at 0.99, steady	38
Fig. 38 Mach number at a wing section	38
Fig. 39 Mach (left) and C_p (right) distribution at upper wing	38
Fig. 40 The whole computational domains	40
Fig. 41 The full-size ATR72 configuration	40
Fig. 42 The span length of the main wing, ATR72	42
Fig. 43 The (a) drag polar and (b) lift coefficient to AOA, ATR72SM-IL	42
Fig. 44 The airfoil of main wing, ATR72SM-IL	42
Fig. 45 The airfoil of stabilator, NACA 63012A	43
Fig. 46 The diameter of a set of propellers	44
Fig. 47 The span length of the flaps, ATR72	44
Fig. 48 Mesh of the whole domain	45
Fig. 49 Refined mesh near the aircraft	45
Fig. 50 Neighbor mesh of the main wing and HLDs	46
Fig. 51 Mesh of the propeller section	47
Fig. 52 Mesh along the wingspan section	47
Fig. 53 Mesh located near the fuselage and lower wing surface	47
Fig. 54 The six named surfaces of the outer domain	49
Fig. 55 The method of data acquisition	52
Fig. 56 Pressure distribution at (a) 129.74 m/s (b) 62.69 m/s, side view	57
Fig. 57 Velocity magnitude at (a) 129.74 m/s (b) 62.69 m/s, side view	57
Fig. 58 Pressure distribution at (a) 129.74 m/s (b) 62.69 m/s, side view	57
Fig. 59 Velocity magnitude at (a) 129.74 m/s (b) 62.69 m/s, side view	57
Fig. 60 Pressure distribution at (a) 129.74 m/s (b) 62.69 m/s, front view	58
Fig. 61 Velocity magnitude at (a) 129.74 m/s (b) 62.69 m/s, front view	58
Fig. 62 Pressure distribution, (a) calm (b) sustained crosswind, front view	59
Fig. 63 Velocity magnitude, (a) calm (b) sustained crosswind, front view	59
Fig. 64 Q-criterion at 4e-5, (a) calm (b) sustained crosswind, front view	59
Fig. 65 Q-criterion at 4e-5, (a) calm (b) sustained crosswind, top view	60
Fig. 66 The changes of C_L, C_D and C_SF affected by gusty winds, case 8	61
Fig. 67 The changes of C_L, C_M and C_ℵ affected by gusty winds, case 8	62
Fig. 68 Difference between extreme value and average value, case 8	63
Fig. 69 (a) pressure contour, (b) velocity magnitude at 1.0 sec, case 8	63
Fig. 70 (a) pressure contour, (b) velocity magnitude at 1.1 sec, case 8	64
Fig. 71 (a) pressure contour, (b) velocity magnitude at 1.2 sec, case 8	64
Fig. 72 pressure contour viewed from (a) top (b) bottom, 1.0 sec, case 8	64
Fig. 73 pressure contour viewed from (a) top (b) bottom, 1.1 sec, case 8	64
Fig. 74 pressure contour viewed from (a) top (b) bottom, 1.2 sec, case 8	65
Fig. 75 Q-criteria at 1.7e-5, 1.0 sec, case 8	65
Fig. 76 Q-criteria at 1.7e-5, 1.1 sec, case 8	65
Fig. 77 Q-criteria at 1.7e-5, 1.2 sec, case 8	65
Fig. 78 Velocity magnitude of raindrops, case 9	67
Fig. 79 The changes of C_L, C_D and C_SF affected by gusty winds, case 9	68
Fig. 80 The changes of C_L, C_M and C_ℵ affected by gusty winds, case 9	68
Fig. 81 Rain affects the aircraft performance, case 9	69


List of Tables

Table 1 The replaced variables in the different cases	8
Table 2 The x, y, z components of wind at different AOA	21
Table 3 The ATR72 geometric parameters	39
Table 4 The flight environmental setup in all cases	49
Table 5 The comparison from case 1 to Seeckt [1]	54
Table 6 Computational results for the steady state cases	55
Table 7 Computational results for the transient state cases	55
Table 8 The average and extreme values in case 8	62
Table 9 The average and extreme values in case 9	69

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