fastoad_cs25.models.weight.cg.cg_components.load_cases.compute_cg_loadcases module

Computes and aggregates CG ratios for load cases.

class fastoad_cs25.models.weight.cg.cg_components.load_cases.compute_cg_loadcases.CGRatiosForLoadCases(**kwargs)

Bases: Group

Aggregation of CG ratios from load case calculations.

Set the solvers to nonlinear and linear block Gauss–Seidel by default.

setup()

Build this group.

This method should be overidden by your Group’s method. The reason for using this method to add subsystem is to save memory and setup time when using your Group while running under MPI. This avoids the creation of systems that will not be used in the current process.

You may call ‘add_subsystem’ to add systems to this group. You may also issue connections, and set the linear and nonlinear solvers for this group level. You cannot safely change anything on children systems; use the ‘configure’ method instead.

Available attributes:

name pathname comm options

class fastoad_cs25.models.weight.cg.cg_components.load_cases.compute_cg_loadcases.MaxCGRatiosForLoadCases(**kwargs)

Bases: ExplicitComponent

Maximum center of gravity ratio from load cases.

Store some bound methods so we can detect runtime overrides.

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

setup_partials()

Declare partials.

This is meant to be overridden by component classes. All partials should be declared here since this is called after all size/shape information is known for all variables.

compute(inputs, outputs, discrete_inputs=None, discrete_outputs=None)

Compute outputs given inputs. The model is assumed to be in an unscaled state.

An inherited component may choose to either override this function or to define a compute_primal function.

Parameters:

• inputs (Vector) – Unscaled, dimensional input variables read via inputs[key].

• outputs (Vector) – Unscaled, dimensional output variables read via outputs[key].

• discrete_inputs (dict-like or None) – If not None, dict-like object containing discrete input values.

• discrete_outputs (dict-like or None) – If not None, dict-like object containing discrete output values.