fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_max_power module

class fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_max_power.TurboshaftMaxThrustPowerLimit(**kwargs)

Bases: fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_fuel.Turboshaft

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 fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_max_power.DistanceToLimitPowerLimit(**kwargs)

Bases: openmdao.core.implicitcomponent.ImplicitComponent

Store some bound methods so we can detect runtime overrides.

initialize()

Perform any one-time initialization run at instantiation.

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

apply_nonlinear(inputs, outputs, residuals, discrete_inputs=None, discrete_outputs=None)

Compute residuals given inputs and outputs.

The model is assumed to be in an unscaled state.

Parameters

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

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

• residuals (Vector) – Unscaled, dimensional residuals written to via residuals[key].

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

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

linearize(inputs, outputs, jacobian, discrete_inputs=None, discrete_outputs=None)

Compute sub-jacobian parts and any applicable matrix factorizations.

The model is assumed to be in an unscaled state.

Parameters

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

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

• jacobian (Jacobian) – Sub-jac components written to jacobian[output_name, input_name].

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

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

class fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_max_power.TurboshaftMaxThrustOPRLimit(**kwargs)

Bases: fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_fuel.Turboshaft

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 fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_max_power.DistanceToLimitOPRLimit(**kwargs)

Bases: openmdao.core.implicitcomponent.ImplicitComponent

Store some bound methods so we can detect runtime overrides.

initialize()

Perform any one-time initialization run at instantiation.

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

apply_nonlinear(inputs, outputs, residuals, discrete_inputs=None, discrete_outputs=None)

Compute residuals given inputs and outputs.

The model is assumed to be in an unscaled state.

Parameters

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

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

• residuals (Vector) – Unscaled, dimensional residuals written to via residuals[key].

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

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

linearize(inputs, outputs, jacobian, discrete_inputs=None, discrete_outputs=None)

Compute sub-jacobian parts and any applicable matrix factorizations.

The model is assumed to be in an unscaled state.

Parameters

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

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

• jacobian (Jacobian) – Sub-jac components written to jacobian[output_name, input_name].

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

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

class fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_max_power.TurboshaftMaxThrustITTLimit(**kwargs)

Bases: fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_fuel.Turboshaft

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 fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_max_power.DistanceToLimitITTLimit(**kwargs)

Bases: openmdao.core.implicitcomponent.ImplicitComponent

Store some bound methods so we can detect runtime overrides.

initialize()

Perform any one-time initialization run at instantiation.

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

apply_nonlinear(inputs, outputs, residuals, discrete_inputs=None, discrete_outputs=None)

Compute residuals given inputs and outputs.

The model is assumed to be in an unscaled state.

Parameters

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

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

• residuals (Vector) – Unscaled, dimensional residuals written to via residuals[key].

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

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

linearize(inputs, outputs, jacobian, discrete_inputs=None, discrete_outputs=None)

Compute sub-jacobian parts and any applicable matrix factorizations.

The model is assumed to be in an unscaled state.

Parameters

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

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

• jacobian (Jacobian) – Sub-jac components written to jacobian[output_name, input_name].

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

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

class fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_max_power.TurboshaftMaxThrustPropellerThrustLimit(**kwargs)

Bases: fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_fuel.Turboshaft

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 fastga.models.propulsion.fuel_propulsion.basicTurbo_prop.turboprop_components.turboshaft_off_design_max_power.DistanceToLimitPropellerThrustLimit(**kwargs)

Bases: openmdao.core.implicitcomponent.ImplicitComponent

Store some bound methods so we can detect runtime overrides.

initialize()

Perform any one-time initialization run at instantiation.

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

apply_nonlinear(inputs, outputs, residuals, discrete_inputs=None, discrete_outputs=None)

Compute residuals given inputs and outputs.

The model is assumed to be in an unscaled state.

Parameters

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

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

• residuals (Vector) – Unscaled, dimensional residuals written to via residuals[key].

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

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

linearize(inputs, outputs, jacobian, discrete_inputs=None, discrete_outputs=None)

Compute sub-jacobian parts and any applicable matrix factorizations.

The model is assumed to be in an unscaled state.

Parameters

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

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

• jacobian (Jacobian) – Sub-jac components written to jacobian[output_name, input_name].

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

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