def calcElevEffectiveness(inputFile):
'''
DESCRIPTION: This function calculates the elevator effectiveness (Cmdelta), which is a constant value found from the measurements when changing xcg.
========
INPUT:\n
... inputFile [String]: Name of excel file; choose between 'reference' or 'actual'\n
... SI [Condition]: By default set to SI=True\n
OUTPUT:\n
... Cmdelta [float]: Elevator effectiveness
'''
# Import data
param = imPar.parametersStatic()
static2b = imStat.staticMeas(inputFile, 'static2b', SI=True)
aeroCoeff = calcAeroCoeff(inputFile, 'static2b')
static2bWeight = imWeight.calcWeightCG(inputFile, 'static2b')
# Obtain values from data
cbar = param.c
delta = static2b['delta'].to_numpy()
delta1 = delta[0]
delta2 = delta[1]
Cn = aeroCoeff['Cl'].to_numpy()
CnAvg = np.average( Cn )
xcg = static2bWeight['Xcg'].to_numpy()
xcg1 = xcg[0]
xcg2 = xcg[1]
# Calculation
Cmdelta = -1 * ( CnAvg * (xcg2 - xcg1) / cbar ) / ( delta2 - delta1 )
return Cmdelta
def calcElevContrForce(inputFile):
'''
DESCRIPTION: This function calculates the reduced elevator control force for each meassurement taken during the second stationary measurement series.
========
INPUT:\n
... inputFile [String]: Name of excel file; choose between 'reference' or 'actual'\n
... SI [Condition]: By default set to SI=True\n
OUTPUT:\n
... FeRed [Arary]: Numpy array containing the reduced elevator control force
'''
# Import data
param = imPar.parametersStatic()
static2a = imStat.staticMeas(inputFile, 'static2a', SI=True)
static2aWeight = imWeight.calcWeightCG(inputFile, 'static2a')
# Obtain values from data
Ws = param.Ws
Fe = static2a['Fe'].to_numpy()
W = static2aWeight['Weight'].to_numpy()
# Calculation
FeRed = Fe * Ws / W
return FeRed
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 plotElevTrimCurve(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_nonSI = imStat.staticMeas(inputFile,'static2a',SI=False)
Weight2a = imWeight.calcWeightCG(inputFile, 'static2a')
# Obtain values from data
aoa_deg = static2a_nonSI['aoa'].to_numpy()
delta_deg = static2a_nonSI['delta'].to_numpy()
Xcg = np.average(Weight2a['Xcg'].to_numpy())
Weight = np.average(Weight2a['Weight'].to_numpy())
# Calculations
linregress = stats.linregress(aoa_deg, delta_deg)
# Start plotting
plt.figure('Elevator trim curve',[10,7])
plt.title("Elevator Trim Curve",fontsize=22)
plt.scatter(aoa_deg,delta_deg)
plt.plot(np.sort(aoa_deg),np.sort(aoa_deg)*linregress.slope + linregress.intercept, 'k--')
plt.ylim(1.2*max(delta_deg),1.2*min(delta_deg))
plt.grid()
plt.xlim(0.9*np.sort(aoa_deg)[0],1.1*np.sort(aoa_deg)[-1])
plt.xlabel(r'$\alpha$ [$\degree$]',fontsize=16)
plt.ylabel(r'$\delta_{e}$ [$\degree$]',fontsize=16)
plt.axhline(0,color='k')
props = dict(boxstyle='round', facecolor='white', alpha=0.5)
# plt.text(1.03*np.sort(aoa_deg)[1],1.05*delta_deg[1],'$x_{cg}$ = 7.15 m\nW = 59875 kg',bbox=props,fontsize=16)
plt.text(1.03*np.sort(aoa_deg)[1],1.05*delta_deg[1],'$x_{cg}$ = '+str(round(Xcg,2))+' m\nW = '+str(int(round(Weight,0)))+' kg',bbox=props,fontsize=16)
props = dict(boxstyle='round', facecolor='white', alpha=0.5)
plt.show()
return
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
def staticFlightCondition(inputFile, dataSet):
'''
DESCRIPTION: This function calculates flight conditions using the measurement data.
========
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
... staticFlightCond [Dataframe]: Pandas dataframe containing flight condition values that are not measured.
'''
# Import data
meas = staticMeas(inputFile, dataSet, SI=True)
param = imPar.parametersStatic()
staticWeight = imWeight.calcWeightCG(inputFile, dataSet)
# Constant values
pres0 = param.pres0
rho0 = param.rho0
Temp0 = param.Temp0
g0 = param.g
Ws = param.Ws
gamma = param.gamma
lamb = param.lamb
R = param.R
Vi = meas['Vi'].to_numpy()
Vc = Vi - 2 * 0.514444444
TempMeas = meas['TAT'].to_numpy()
hp = meas['hp'].to_numpy()
W = staticWeight['Weight'].to_numpy()
# Calculation
pres = pres0 * (1 + lamb * hp / Temp0)**(-g0 / (lamb * R))
Mach = np.sqrt(
2 / (gamma - 1) *
((1 + pres0 / pres *
((1 + (gamma - 1) /
(2 * gamma) * rho0 / pres0 * Vc**2)**(gamma / (gamma - 1)) - 1))**(
(gamma - 1) / gamma) - 1))
Temp = TempMeas / (1 + (gamma - 1) / 2 * Mach**2)
a = np.sqrt(gamma * R * Temp)
Vt = Mach * a
rho = pres / (R * Temp)
Ve = Vt * np.sqrt(rho / rho0)
VeRed = Ve * np.sqrt(Ws / W)
Tisa = Temp0 + lamb * meas['hp'].to_numpy()
DeltaTisa = Temp - Tisa
staticFlightCond = {}
dataNames = [
'pres', 'Mach', 'Temp', 'a', 'Vt', 'rho', 'Ve', 'VeRed', 'DeltaTisa'
]
for name in dataNames:
staticFlightCond[name] = locals()[name]
staticFlightCond = pd.DataFrame(data=staticFlightCond)
return staticFlightCond