tunnel = cT.Tunnel() 'Tail Off case' dir = 'data/' polar_tailOff = dir + 'raw_tailOff_bal.txt' polar_tailOff_0 = dir + 'zero_tailOff_bal.txt' polar_tailOff_raw = source.BAL_class.BAL_data(polar_tailOff, polar_tailOff_0, 5) raw_data_40 = [] for data_i in polar_tailOff_raw.data: if np.abs(data_i[polar_tailOff_raw.index.V] - 40) < 2: raw_data_40.append(data_i[:]) raw_data_40 = np.array(raw_data_40) polar_tailOff_uncorr = cP.Polar(raw_data_40, polar_tailOff_raw.index, aircraft) polar_tailOff_corr = copy.deepcopy(polar_tailOff_uncorr) fb.correct_notail(polar_tailOff_corr, aircraft, tunnel, 'w') CLu_tailOff = fb.get_listfrompolar(polar_tailOff_uncorr, 'CL') CDu_tailOff = fb.get_listfrompolar(polar_tailOff_uncorr, 'CD') CMu_tailOff = fb.get_listfrompolar(polar_tailOff_uncorr, 'CM') CLc_tailOff = fb.get_listfrompolar(polar_tailOff_corr, 'CL') CDc_tailOff = fb.get_listfrompolar(polar_tailOff_corr, 'CD') CMc_tailOff = fb.get_listfrompolar(polar_tailOff_corr, 'CM') 'Tail On case' polar_tailOn = dir + 'raw_tailOn_bal.txt' polar_tailOn_0 = dir + 'zero_tailOn_bal.txt' polar_tailOn_raw = source.BAL_class.BAL_data(polar_tailOn, polar_tailOn_0, 5) polar_tailOn_uncorr = cP.Polar(polar_tailOn_raw.data, polar_tailOn_raw.index,
tunnel = cT.Tunnel() 'Tail Off case' dir = 'data/' polar_tailOff = dir + 'raw_tailOff_bal.txt' polar_tailOff_0 = dir + 'zero_tailOff_bal.txt' polar_tailOff_raw = source.BAL_class.BAL_data(polar_tailOff, polar_tailOff_0, 5) raw_data_40 = [] for data_i in polar_tailOff_raw.data: if np.abs(data_i[polar_tailOff_raw.index.V] - 40) < 2: raw_data_40.append(data_i[:]) raw_data_40 = np.array(raw_data_40) polar_tailOff_uncorr = cP.Polar(raw_data_40, polar_tailOff_raw.index, aircraft) polar_tailOff_corr_block = cP.Polar(raw_data_40, polar_tailOff_raw.index, aircraft) fb.correct_blockage(polar_tailOff_corr_block, aircraft, tunnel, 'w') polar_tailOff_corr = copy.deepcopy(polar_tailOff_corr_block) fb.correct_streamline(polar_tailOff_corr, aircraft, tunnel, 'w') df = pd.DataFrame(np.zeros((len(polar_tailOff_corr.points), 11)), columns=[ 'alphau', 'alpha', 'CLu', 'CDu', 'CMu', 'CLc_b', 'CDc_b', 'CMc_b', 'CL', 'CD', 'CM' ]) for i, point in enumerate(polar_tailOff_corr.points): df.at[i, 'alphau'] = polar_tailOff_uncorr.points[i].alpha df.at[i, 'alpha'] = polar_tailOff_corr.points[i].alpha df.at[i, 'CLu'] = polar_tailOff_uncorr.points[i].CFl