RCAIDE.Library.Methods.Powertrain.Converters.Rotor.design_prop_rotor
design_prop_rotor#
- design_prop_rotor(rotor, number_of_stations=20, solver_name='SLSQP', iterations=200, solver_sense_step=1e-06, solver_tolerance=1e-05, print_iterations=False)[source]#
Optimizes prop-rotor chord and twist distribution to meet design power or thrust requirements.
- Parameters:
rotor (RCAIDE.Library.Components.Powertrain.Converters.Rotor) –
- Rotor component with the following attributes:
- tagstr
Identifier for the rotor
- hub_radiusfloat
Hub radius of the rotor [m]
- tip_radiusfloat
Tip radius of the rotor [m]
- rotation_ratefloat
Rotation rate [rad/s]
- freestream_velocityfloat
Freestream velocity [m/s]
- number_of_bladesint
Number of blades on the rotor
- design_lift_coefficientfloat
Design lift coefficient
- airfoil_datadict
Dictionary of airfoil data
- optimization_parametersData
- Optimization parameters
- slack_constraintfloat
Slack constraint value
- ideal_SPL_dbAfloat
Ideal sound pressure level [dBA]
- multiobjective_aeroacoustic_weightfloat
Weight for multiobjective aeroacoustic optimization
number_of_stations (int, optional) – Number of radial stations for blade discretization, default 20
solver_name (str, optional) – Name of the optimization solver, default ‘SLSQP’
iterations (int, optional) – Maximum number of iterations, default 200
solver_sense_step (float, optional) – Step size for finite difference gradient calculation, default 1E-6
solver_tolerance (float, optional) – Convergence tolerance for the optimizer, default 1E-5
print_iterations (bool, optional) – Flag to print optimization iterations, default False
- Returns:
rotor – Optimized rotor with updated chord and twist distributions
- Return type:
RCAIDE.Library.Components.Powertrain.Converters.Rotor
Notes
This function optimizes the chord and twist distributions of a prop-rotor to meet either design power or thrust requirements. It uses RCAIDE’s native optimization framework with an objective function that balances aerodynamic performance and acoustic characteristics.
- The optimization process follows these steps:
Set up the optimization problem using the optimization_setup function
Solve the optimization problem using the specified solver
Report optimization results
Update the rotor with the optimized parameters
The objective function is formulated as an aeroacoustic function that considers both efficiency and radiated noise, with the balance controlled by the multiobjective_aeroacoustic_weight parameter.
- Major Assumptions
Prop-rotor design considers both hover and cruise conditions
Either design power or thrust must be specified (not both)
The optimization balances aerodynamic performance and acoustic characteristics