def plotLift(inputFile):
'''
DESCRIPTION: This function plots the CL-alpha curve
========
INPUT:\n
... inputFile [String]: Name of excel file; choose between 'reference' or 'actual'\n
OUTPUT:\n
'''
# Import the data
param = imPar.parametersStatic()
static1NotSI = imStat.staticMeas(inputFile, 'static1', SI=False)
aeroCoeff = calcAeroCoeff(inputFile)[-1]
static1FlightCond = imStat.staticFlightCondition(inputFile, 'static1')
# Get the required parameters
aoa_deg = static1NotSI['aoa'].to_numpy()
CL = aeroCoeff['CL'].to_numpy()
# Mach range
M = static1FlightCond['Mach'].to_numpy()
Mmax = np.max(M)
Mmin = np.min(M)
# Reynolds number range
rho = static1FlightCond['rho'].to_numpy()
Vt = static1FlightCond['Vt'].to_numpy()
mac = param.c
T = static1FlightCond['Temp'].to_numpy() * (9 / 5) # [Rankine]
T0 = 518.7 # [Rankine]
mu0 = 3.62E-7 # [lb s/ft2]
mu = mu0 * (T / T0)**1.5 * ((T0 + 198.72) / (T + 198.72))
mu = mu * (0.45359237 / (0.3048**2))
Re = rho * Vt * mac / mu
Remax = np.max(Re)
Remin = np.min(Re)
# Plot lift curve
plt.figure('Lift curve', [10, 7])
plt.title('Lift Curve', fontsize=22)
plt.plot(aoa_deg, CL, marker='o')
plt.xlabel(r'$\alpha$ [$\degree$]', fontsize=16)
plt.ylabel(r'$C_L$ [$-$]', fontsize=16)
props = dict(boxstyle='round', facecolor='white', alpha=0.5)
plt.text(1.03 * aoa_deg[1],
1.05 * CL[-2],
'Aircraft configuration: Clean' + '\nMach number range: ' +
str(round(Mmin, 2)) + ' - ' + str(round(Mmax, 2)) +
'\nReynolds number range: ' + '{:.2e}'.format(Remin) + ' - ' +
'{:.2e}'.format(Remax),
bbox=props,
fontsize=16)
plt.grid()
return
def calcAeroCoeff(inputFile, dataSet):
'''
DESCRIPTION: This function calculates the lift coefficient for the static measurements. (CL \approx CN)
========
INPUT:\n
... inputFile [String]: Name of excel file; choose between 'reference' or 'actual'\n
... dataSet [String]: Name of data set; choose between 'static1', 'static2a' or 'static2b'\n
... SI [Condition]: By default set to SI=True\n
OUTPUT:\n
... aeroCoeff [Dataframe]: Pandas dataframe containing Cl, Cd, e, Cla, Cd0, aoa0
'''
# Import data
param = imPar.parametersStatic()
static = imStat.staticMeas(inputFile, dataSet)
staticNotSI = imStat.staticMeas(inputFile, dataSet, SI=False)
staticFlightCond = imStat.staticFlightCondition(inputFile, dataSet)
staticTp = imStat.staticThrust(inputFile, dataSet)
staticWeight = imWeight.calcWeightCG(inputFile, dataSet)
# Obtain vales from data
S = param.S
A = param.A
aoa_rad = static['aoa'].to_numpy()
aoa_deg = staticNotSI['aoa'].to_numpy()
rho = staticFlightCond['rho'].to_numpy()
Vt = staticFlightCond['Vt'].to_numpy()
W = staticWeight['Weight'].to_numpy()
Tp = staticTp['Tp'].to_numpy()
# Calculations
Cl = W / (0.5 * rho * Vt**2 * S)
Cd = Tp / (0.5 * rho * Vt**2 * S)
aeroCoeff = {}
if dataSet == 'static1':
Cl_aoa = stats.linregress(aoa_deg,Cl)
Cd_Cl2 = stats.linregress(Cl**2,Cd)
Cla = Cl_aoa.slope
aoa0 = -Cl_aoa.intercept / Cla
e = 1/(np.pi*A*Cd_Cl2.slope)
Cd0 = Cd_Cl2.intercept
dataNames = ['Cl','Cd','e','Cla','Cd0','aoa0']
for name in dataNames:
aeroCoeff[name] = locals()[name]
else:
dataNames = ['Cl','Cd']
for name in dataNames:
aeroCoeff[name] = locals()[name]
aeroCoeff = pd.DataFrame(data=aeroCoeff)
return aeroCoeff
def calcAeroCoeff(inputFile):
'''
DESCRIPTION: This function calculates the aerodynamic coefficient for the first static measurement. (CL \approx CN)
========
INPUT:\n
... inputFile [String]: Name of excel file; choose between 'reference' or 'actual'\n
OUTPUT:\n
... CLa [float]: Lift curve slope
... aoa0 [float]: Zero lift angle of attack
... e [float]: Oswald efficiency factor
... CD0 [float]: Zero lift drag
... aeroCoeff [Dataframe]: Pandas dataframe containing CL, CD
'''
# Import data
param = imPar.parametersStatic()
static = imStat.staticMeas(inputFile, 'static1')
staticNotSI = imStat.staticMeas(inputFile, 'static1', SI=False)
staticFlightCond = imStat.staticFlightCondition(inputFile, 'static1')
staticTp = imStat.staticThrust(inputFile, 'static1')
staticWeight = imWeight.calcWeightCG(inputFile, 'static1')
# Obtain vales from data
S = param.S
A = param.A
aoa_rad = static['aoa'].to_numpy()
aoa_deg = staticNotSI['aoa'].to_numpy()
rho = staticFlightCond['rho'].to_numpy()
Vt = staticFlightCond['Vt'].to_numpy()
W = staticWeight['Weight'].to_numpy()
Tp = staticTp['Tp'].to_numpy()
# Calculations
CL = W / (0.5 * rho * Vt**2 * S)
CD = Tp / (0.5 * rho * Vt**2 * S)
CL_aoa = stat.linregress(aoa_rad, CL)
CD_CL2 = stat.linregress(CL**2, CD)
CLa = CL_aoa.slope
aoa0 = -CL_aoa.intercept / CLa
e = 1 / (np.pi * A * CD_CL2.slope)
CD0 = CD_CL2.intercept
aeroCoeff = {}
dataNames = ['CL', 'CD']
for name in dataNames:
aeroCoeff[name] = locals()[name]
aeroCoeff = pd.DataFrame(data=aeroCoeff)
return CLa, aoa0, e, CD0, aeroCoeff
def plotRedElevContrForceCurve(inputFile):
'''
DESCRIPTION: Function description
========
INPUT:\n
... inputFile [String]: Name of excel file; choose between 'reference' or 'actual'\n
OUTPUT:\n
... None, but running this function creates a figure which can be displayed by calling plt.plot()
'''
# Import data
static2a = imStat.staticMeas(inputFile,'static2a')
flightCond2a = imStat.staticFlightCondition(inputFile,'static2a')
Weight2a = imWeight.calcWeightCG(inputFile, 'static2a')
# Obtain values from data
VeRed = np.sort( flightCond2a['VeRed'].to_numpy() )
Xcg = np.average(Weight2a['Xcg'].to_numpy())
deltaTr = np.rad2deg(np.average(static2a['deltaTr']))
# Calculation
FeRed = np.sort(calcElevContrForce(inputFile))
# Start plotting
plt.figure('Elevator Force Control Curve',[10,7])
plt.title("Reduced Elevator Control Force Curve",fontsize=22)
plt.plot(VeRed,FeRed,marker='o')
plt.xlim(0.9*VeRed[0],1.1*VeRed[-1])
plt.xlabel(r'$V_{e}^{*}$ [$\dfrac{m}{s}$]',fontsize=16)
plt.ylim(1.2*FeRed[-1],1.2*FeRed[0])
plt.ylabel(r'$F_{e}^{*}$ [N]',fontsize=16)
plt.axhline(0,color='k')
props = dict(boxstyle='round', facecolor='white', alpha=0.5)
plt.text(1.03*VeRed[2],1.05*FeRed[2],'$x_{cg}$ = '+str(round(Xcg,2))+' m\n$\delta_{t_{e}}$ = '+str(round(deltaTr,3))+'$\degree$',bbox=props,fontsize=16)
plt.grid()
return