def main():
# Define internal combustion engine from Cessna Regression Aircraft
vehicle = vehicle_setup()
# Setup the modified constant speed version of the network
vehicle = ICE_CS(vehicle)
# Setup analyses and mission
analyses = base_analysis(vehicle)
analyses.finalize()
mission = mission_setup(analyses)
# evaluate
results = mission.evaluate()
P_truth = 53734.90184388173
mdot_truth = 0.004721271494265418
P = results.segments.cruise.state.conditions.propulsion.power[-1, 0]
mdot = results.segments.cruise.state.conditions.weights.vehicle_mass_rate[
-1, 0]
# Check the errors
error = Data()
error.P = np.max(np.abs((P - P_truth) / P_truth))
error.mdot = np.max(np.abs((mdot - mdot_truth) / mdot_truth))
print('Errors:')
print(error)
for k, v in list(error.items()):
assert (np.abs(v) < 1e-6)
return
def main():
# Define internal combustion engine from Cessna Regression Aircraft
vehicle = vehicle_setup()
# Setup analyses and mission
analyses = base_analysis(vehicle)
analyses.finalize()
mission = mission_setup(analyses)
# evaluate
results = mission.evaluate()
P_truth = 113274.953368933
mdot_truth = 0.008752685036290996
P = results.segments.cruise.state.conditions.propulsion.power[-1, 0]
mdot = results.segments.cruise.state.conditions.weights.vehicle_mass_rate[
-1, 0]
# Check the errors
error = Data()
error.P = np.max(np.abs((P - P_truth) / P_truth))
error.mdot = np.max(np.abs((mdot - mdot_truth) / mdot_truth))
print('Errors:')
print(error)
for k, v in list(error.items()):
assert (np.abs(v) < 1e-6)
return
def main():
# Define internal combustion engine from Cessna Regression Aircraft
vehicle = vehicle_setup()
# Setup analyses and mission
analyses = base_analysis(vehicle)
analyses.finalize()
mission = mission_setup(analyses, vehicle)
# evaluate
results = mission.evaluate()
h = 0.008757244664175039
P_truth = 54141.22575147851
mdot_truth = 0.004756972043006517
P = results.segments.cruise.state.conditions.propulsion.power[-1, 0]
mdot = results.segments.cruise.state.conditions.weights.vehicle_mass_rate[
-1, 0]
# Check the errors
error = Data()
error.P = np.max(np.abs((P - P_truth) / P_truth))
error.mdot = np.max(np.abs((mdot - mdot_truth) / mdot_truth))
print('Errors:')
print(error)
for k, v in list(error.items()):
assert (np.abs(v) < 1e-6)
return
def main():
# Define internal combustion engine from Cessna Regression Aircraft
vehicle = vehicle_setup()
ice_engine = vehicle.propulsors.internal_combustion.engine
# Define conditions
conditions = Data()
conditions.freestream = Data()
conditions.propulsion = Data()
conditions.freestream.altitude = np.array([[8000]]) * Units.feet
conditions.freestream.delta_ISA = 0.0
conditions.propulsion.combustion_engine_throttle = np.array([[0.8]])
ice_engine.power(conditions)
# Truth values for propeller with airfoil geometry defined
P_truth = 81367.49237183
P_sfc_truth = 0.52
FFR_truth = 0.007149134158858348
Q_truth = 287.7786359548746
P = ice_engine.outputs.power[0][0]
P_sfc = ice_engine.outputs.power_specific_fuel_consumption
FFR = ice_engine.outputs.fuel_flow_rate[0][0]
Q = ice_engine.outputs.torque[0][0]
# Store errors
error = Data()
error.P = np.max(np.abs(P - P_truth))
error.P_sfc = np.max(np.abs(P_sfc - P_sfc_truth))
error.FFR = np.max(np.abs(FFR - FFR_truth))
error.Q = np.max(np.abs(Q - Q_truth))
print('Errors:')
print(error)
for k, v in list(error.items()):
assert (np.abs(v) < 1e-6)
return