TAGGED: non-linear-buckling
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June 14, 2021 at 5:52 pm
Superted
SubscriberHello:
 I have a question regarding performing a non-linear buckling analysis on a steel cylindrical shell (fixed at the base) with varying internal pressure in Mechanical APDL. Below are the steps that I have performed so far:
a) Model the geometry, apply internal pressure, and apply boundary conditions
b) Perform linear (eigen value) buckling analysis. Mode extraction is block lanczos and expanded 10 mode shapes. Obtained load factors for all the extracted modes.
c)Imperfections are added to the geometry based on the modes extracted in step b. Used UPGEOM command.
UPGEOM, 0.1, 1, 1, file.rstd
)Perform non-linear buckling analysis.
/SOLU
ANTYPE,STATIC
NLGOEM,ON
OUTRES,ALL,ALL
NSUBST,100,1000,50
AUTOTS,ON
SOLVE
FINISH
I see that the nonlinear analysis is complete. I understand that nonlinear buckling is conservative and will give lower load factors.
When I tried to look at the results (General Postproc -> Read results -> By Pick (picked a set) -> Plot Results -> contours plot -> nodal solu ), the load factors were observed to be higher than the load factors obtained in step b.
The applied load is a varying load and I would like to see the buckling behavior of the entire cylinder and get the buckling load by performing the non-linear analysis. Is this the correct approach to find the load factors in the nonlinear buckling analysis? Â
I would greatly appreciate your input on this. Thanks
June 24, 2021 at 10:47 am1shan
Ansys EmployeeIs the cylinder subjected to an axial load and an internal pressure or is it only internal pressure without an axial load? You need an axial compressive load to give realistic load factors for a linear buckling analysis.
Regards Ishan.
June 25, 2021 at 3:06 pmSuperted
SubscriberThanks for your reply. The cylinder is only subjected to internal pressure and self weight. I could get the load factors in linear analysis. I am having difficulty in interpreting the nonlinear analysis results and obtain the load factors in APDL. Thanks!
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