is generally introduced in a model for a postbuckling
load-displacement analysis;
can be defined as a linear superposition of buckling eigenmodes
obtained from a previous eigenvalue buckling prediction or eigenfrequency
extraction analysis performed with
Abaqus/Standard;
can be based on the solution obtained from a previous static analysis
performed with
Abaqus/Standard;
or
In
Abaqus/Standard
the Riks method (Unstable Collapse and Postbuckling Analysis)
can be used to solve postbuckling problems, both with stable and unstable
postbuckling behavior. However, the exact postbuckling problem often cannot be
analyzed directly due to the discontinuous response (bifurcation) at the point
of buckling. To analyze a postbuckling problem, you must turn it into a problem
with continuous response instead of bifurcation, which can be accomplished by
introducing a geometric imperfection pattern in the “perfect” geometry so that
there is some response in the buckling mode before the critical load is
reached.
Introducing Geometric Imperfections
Imperfections are usually introduced by perturbations in the geometry.
Abaqus
offers three ways to define an imperfection: as a linear superposition of
buckling eigenmodes, from the displacements of a static analysis, or by
specifying the node number and imperfection values directly. Only the
translational degrees of freedom are modified.
Abaqus
will then calculate the normals using the usual algorithm based on the
perturbed coordinates. Unless the precise shape of an imperfection is known, an
imperfection consisting of multiple superimposed buckling modes can be
introduced (Eigenvalue Buckling Prediction).
The usual approach involves two analysis runs with the same model
definition, using
Abaqus/Standard
to establish the probable collapse modes and either
Abaqus/Standard
or
Abaqus/Explicit
to perform the postbuckling analysis:
In the first analysis run perform an eigenvalue buckling analysis with
Abaqus/Standard
on the “perfect” structure to establish probable collapse modes and to verify
that the mesh discretizes those modes accurately. Write the eigenmodes in the
default global system to the results or output database file as nodal data.
In the second analysis run use
Abaqus/Standard
or
Abaqus/Explicit
to introduce an imperfection in the geometry by adding these buckling modes to
the “perfect” geometry. The lowest buckling modes are frequently assumed to
provide the most critical imperfections, so usually these are scaled and added
to the perfect geometry to create the perturbed mesh. The imperfection thus has
the form
where
is the
mode shape and
is the associated scale factor.
You must choose the scale factors of the various modes; usually (if the
structure is not imperfection sensitive) the lowest buckling mode should have
the largest factor. The magnitudes of the perturbations used are typically a
few percent of a relative structural dimension such as a beam cross-section or
shell thickness.
Use either
Abaqus/Standard
or
Abaqus/Explicit
to perform the postbuckling analysis.
In
Abaqus/Standard
perform a geometrically nonlinear load-displacement analysis of the structure
containing the imperfection using the Riks method. In this way the Riks method
can be used to perform postbuckling analyses of “stiff” structures that show
linear behavior prior to buckling, if perfect. By performing a
load-displacement analysis, other important nonlinear effects, such as material
inelasticity or contact, can be included.
In
Abaqus/Explicit
perform a postbuckling analysis on the perturbed structure.
Abaqus
imports imperfection data through the user node labels.
Abaqus
does not check model compatibility between both analysis runs. Node set
definitions in the original model and the model with the imperfection may be
different. Care must be taken for models in which
Abaqus
generates additional nodes (for example, the nodes generated for contact
surfaces on 20-node brick elements). In such cases you have to ensure that the
models for both analysis runs are identical and that the nodal information for
the generated nodes is written to the results file.
If the model is defined in terms of an assembly of part instances, the part
(.prt) file from the original analysis is required to read
the eigenmodes from the results file. Both the original model and the
subsequent model must be defined consistently in terms of an assembly of part
instances.
Defining an Imperfection Based on Eigenmode Data
To define an imperfection based on the superposition of weighted mode
shapes, specify the results (.fil) file or an output
database (.odb or .sim) file and step
from a previous eigenfrequency extraction or eigenvalue buckling prediction
analysis. The file extension is optional. However, if both a results file and
output database file exist, the results file is used. If there is no results
file but both the .odb and .sim files
exist, the .odb file is used. Optionally, you can import
eigenmode data for a specified node set.
Defining an Imperfection Based on Static Analysis Data
To define an imperfection based on the deformed geometry of a previous
static analysis (Unstable Collapse and Postbuckling Analysis),
specify the results (.fil) file or an output database
(.odb or .sim) file and step (and,
optionally, the increment number) from a previous static analysis. (If the
increment number is not specified,
Abaqus
will read data from the last increment available for the specified step in the
results or output database file.) The file extension is optional. However, if
both a results file and output database file exist, the results file is used.
If there is no results file but both the .odb and
.sim files exist, the .odb file is
used. Optionally, you can import modal data for a specified node set.
Defining an Imperfection Directly
You can specify the imperfection directly as a table of node numbers and
coordinate perturbations in the global coordinate system or, optionally, in a
cylindrical or spherical coordinate system. Alternatively, you can read the
imperfection data from a separate input file.
Imperfection Sensitivity
The response of some structures depends strongly on the imperfections in the
original geometry, particularly if the buckling modes interact after buckling
occurs. Hence, imperfections based on a single buckling mode tend to yield
nonconservative results. By adjusting the magnitude of the scaling factors of
the various buckling modes, the imperfection sensitivity of the structure can
be assessed. Normally, a number of analyses should be conducted to investigate
the sensitivity of a structure to imperfections. Structures with many closely
spaced eigenmodes tend to be imperfection sensitive, and imperfections with
shapes corresponding to the eigenmode for the lowest eigenvalue may not give
the worst case.
The imperfect structure will be easier to analyze if the imperfection is
large. If the imperfection is small, the deformation will be quite small
(relative to the imperfection) below the critical load. The response will grow
quickly near the critical load, introducing a rapid change in behavior.
On the other hand, if the imperfection is large, the postbuckling response
will grow steadily before the critical load is reached. In this case the
transition into postbuckled behavior will be smooth and relatively easy to
analyze.
Input File Template
The following example illustrates a postbuckling analysis
of a structure with an imperfection defined by a linear superposition of the
buckling eigenmodes and involves two analysis runs with the same model
definition.
The initial analysis run performs an eigenvalue
buckling analysis with
Abaqus/Standard
to establish the probable collapse modes and writes them to the results
file.
HEADINGInitial analysis run to write the buckling modes to the results fileNODEData lines to define initial “perfect” geometry
…
**
STEPBUCKLEData lines to define the number of buckling eigenmodesCLOAD and/or DLOAD and/or DSLOAD and/or TEMPERATUREData lines to specify the reference load, NODE FILE, GLOBAL=YES, LAST MODE=n
U
END STEP
The second analysis run introduces the imperfection and
performs a postbuckling analysis employing the modified Riks method in
Abaqus/Standard.
HEADINGSecond analysis run to define the imperfection and perform the postbuckling analysisNODEData lines to define initial “perfect” geometry
…
IMPERFECTION, FILE=results_file, STEP=stepData lines specifying the mode number and its associated scale factor
…
**
STEP, NLGEOMSTATIC, RIKSData line to define incrementation and stopping criteriaCLOAD and/or DLOAD and/or DSLOAD and/or TEMPERATUREData lines to specify reference loading,
END STEP
An alternative second analysis run introduces the
imperfection and performs a postbuckling analysis with
Abaqus/Explicit.
HEADINGSecond analysis run to define the imperfection and perform the postbuckling analysisNODEData lines to define initial “perfect” geometry
…
IMPERFECTION, FILE=results_file, STEP=stepData lines specifying the mode number and its associated scale factor
…
**
STEPDYNAMIC, EXPLICITData line to define the time period of the step.CLOAD and/or DLOAD and/or DSLOAD and/or TEMPERATUREEND STEP