ExpressNewtonAlgorithm

ExpressNewtonAlgorithm(iter_count: int = 2, k_multiplier: float = 1.0, initial_tangent: bool = False, current_tangent: bool = True, factor_once: bool = False)

Bases: Algorithm

Express Newton nonlinear solution algorithm.

ExpressNewtonAlgorithm executes a fixed number of Newton-Raphson iterations and accepts the solution regardless of convergence status, speeding up dynamic simulations where approximate equilibrium is tolerable.

Tcl form

algorithm ExpressNewton <iterCount> <kMultiplier> [-initialTangent] [-currentTangent] [-factorOnce]

Example

from femora.core.model import Model

model = Model()
algo = model.analysis.algorithm.expressnewton(iter_count=2, k_multiplier=1.2)

Create an Express Newton solution algorithm.

Parameters:

Name	Type	Description	Default
`iter_count`	`int`	Constant number of iterations to perform.	`2`
`k_multiplier`	`float`	Multiplier factor for system stiffness.	`1.0`
`initial_tangent`	`bool`	If True, uses initial stiffness matrix.	`False`
`current_tangent`	`bool`	If True, uses current tangent stiffness matrix.	`True`
`factor_once`	`bool`	If True, factors system stiffness only once.	`False`

Raises:

Type	Description
`ValueError`	If iter_count is not positive, or if both initial_tangent and current_tangent are set to True.