GSSSS

The Generalized Single Step Single Solve Unified Framework

The GSSSS approach unifies various time integration methods in a single framework.

References

There are quite a few papers on this topic by the same group of authors. Similar contents can be found in a number of papers. The implementation is based on a unified predictor multi-corrector representation. It is sufficiently general so that both elastic and elastoplastic systems can be analyzed. The implementation is documented in details in Section 14.3.4 (Eqs. 14.280 --- 14.296) of the first reference.

It is strongly recommended to give the references a careful read as GSSSS is very elegant if you wish to learn more about the advances in computational dynamics.

Syntax

Both U0 and V0 families are available.

integrator GSSSSU0 (1) (2) (3) (4)
integrator GSSSSV0 (1) (2) (3) (4)
# (1) int, unique integrator tag
# (2) double, spectral radius (order does not matter)
# (3) double, spectral radius (order does not matter)
# (4) double, spectral radius (order does not matter)

The optimal scheme (see table below) only requires one spectral radius, one can use the following command to use the optimal scheme.

integrator GSSSSOptimal (1) [2]
# (1) int, unique integrator tag
# [2] double, spectral radius, default: 0.5

Remarks

The framework has three parameters to be defined, namely ho1,ho_{1,\infty}, ho2,ho_{2,\infty} and ho3,ho_ {3,\infty}. They satisfy the following condition,

0ρ3,ρ1,ρ2,1.0\leqslant\rho_{3,\infty}\leqslant\rho_{1,\infty}\leqslant\rho_{2,\infty}\leqslant1.

The syntax takes three spectral radii in arbitrary order, they are clamped between zero and unity, sorted and assigned to ho3,ho_{3,\infty}, ho1,ho_{1,\infty} and ho2,ho_{2,\infty} to compute internal parameters. Users can thus assign three valid radii without worrying about the order.

A number of commonly known methods can be accommodated in the framework. For example:

Method

Family

Value ho1,ho_{1,\infty}

Value ho2,ho_{2,\infty}

Value ho3,ho_{3,\infty}

Newmark

U0

11

11

00

Classic Midpoint

U0/V0

11

11

11

Generalised Alpha

U0

hoho

hoho

hoho

WBZ

U0

hoho

hoho

00

HHT

U0

hoho

hoho

1ρ2ρ\dfrac{1-\rho}{2\rho}

U0-V0 Optimal

U0/V0

hoho

11

hoho

New Midpoint

V0

11

11

00

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