Model 3: 3D 30-DOF Mechanical System

otaf.example_models.models_3_D.model3.eval_credal_set_constraints(x_std, tol=None, capa=None, param_set=1)[source]

Evaluate the normalized credal set boundary conditions.

Parameters:

  • x_std (np.ndarray) – A 1D array containing standard deviation vector values.

  • tol (float, optional) – Tolerance parameter (unused in this configuration).

  • capa (float, optional) – Process capability index (unused in this configuration).

  • param_set (int, default 1) – The active parameter configuration variant index.

Returns:

An array containing the evaluated constraint metrics.

Return type:

np.ndarray

otaf.example_models.models_3_D.model3.eval_scaled_credal_set_constraints(x_scaled, max_std_vect, tracker=None, experiment_key=None, tol=None, capa=None, param_set=1)[source]

Map scaled deviations to real values and evaluate constraints.

Parameters:

  • x_scaled (np.ndarray) – The scaled standard deviation vector inputs.

  • max_std_vect (np.ndarray) – The upper-bound limits for standard deviation mapping.

  • tracker (Any, optional) – Data logging tracker instance. Default is None.

  • experiment_key (Any, optional) – Unique identifier key for tracking logs. Default is None.

  • tol (float, optional) – Tolerance parameter (unused in this configuration).

  • capa (float, optional) – Process capability index (unused in this configuration).

  • param_set (int, default 1) – The active parameter configuration variant index.

Returns:

The calculated constraint evaluation bounds array.

Return type:

np.ndarray

otaf.example_models.models_3_D.model3.get_distribution_params(tol=None, capa=None, param_set=1)[source]

Compute defect distribution parameters based on the parameter set.

Parameters:

  • tol (float, optional) – Tolerance parameter (unused in this configuration).

  • capa (float, optional) – Process capability index (unused in this configuration).

  • param_set (int, default 1) – The parameter set choice determining mean and variance shifts. Options are 1, 2, or 3.

Returns:

  • RandDeviationVect (otaf.distribution.ComposedDistribution) – The joint normal defect distribution model.

  • list of str – The descriptive tracking labels for mid-point variables.

  • sigma_arr (np.ndarray) – A 1D array of calculated standard deviations.

  • mu_arr (np.ndarray) – A 1D array of calculated mean parameter offsets.

Return type:

tuple[Any, list[str], ndarray, ndarray]

otaf.example_models.models_3_D.model3.get_system_of_constraints_assembly_model(L=[100, 40, 30, 30, 20, 20, 120, 50, 40, 50, -30], Nd=64, strategy=LinearizationStrategy.CIRCUMSCRIBED)[source]

Construct the system of constraints assembly model.

Parameters:

  • L (array_like, optional) – Geometric dimensions and parameters of the assembly. The default is [100, 40, 30, 30, 20, 20, 120, 50, 40, 50, -30].

  • Nd (int, default 64) – The number of discretization points for linearization.

  • strategy (LinearizationStrategy, optional) – The linearization strategy applied to circular constraints. Default is LinearizationStrategy.CIRCUMSCRIBED.

Returns:

The initialized assembly model with embedded optimization variables.

Return type:

otaf.SystemOfConstraintsAssemblyModel