two_d_airfoil_model
Module Contents
Classes
Machine learning-based airfoil model based on XFOIL training data. |
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Functions
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Attributes
- class two_d_airfoil_model.TwoDMLAirfoilModel(airfoil_name: str, force_retrain_Cl: bool = False, force_retrain_Cd: bool = False, plot_model: bool = False, tune_hyper_parameters: bool = False, num_trials: int = 500)
Machine learning-based airfoil model based on XFOIL training data.
Cl and Cd are functions of AoA and Reynolds number with Mach assumed to be 0.
- evaluate(alpha, Re, Ma)
- class two_d_airfoil_model.TwoDMLAirfoilModelCustomOp(Cl_model, Cd_model, X_min, X_max)
Bases:
csdl_alpha.CustomExplicitOperation- compute(input_vals, output_vals)
- compute_derivatives(input_vals, outputs, derivatives)
- evaluate(alpha, Re, Ma)
- two_d_airfoil_model.build_model_from_parameters(params_dict, X_train, X_test, y_train, y_test, data_directory_path, type_, train=True)
- two_d_airfoil_model.define_model(trial)
- two_d_airfoil_model.get_ml_model(input_data, output_data, data_directory_path, type_='Cl', tune_hyper_parameters=False, num_trials=500)
- two_d_airfoil_model.train_two_d_airfoil_model(airfoil_name: str, force_retrain_Cl: bool = False, force_retrain_Cd: bool = False, tune_hyper_parameters: bool = False, num_trials: int = 500, plot_model: bool = False)
- two_d_airfoil_model.device
- two_d_airfoil_model.recorder