Hello,
I am trying to evaluate stresses on a model which is quite large and I have memory limitations. I've seen cases ( http://www.padtinc.com/blog/submodeling_ansys_mechanical/ ) where people used submodeling and imported displacements from the coarse model to the refined section but this relies on Saint Venant's principle and I do not think that my geometry would be applicable.
I am looking at a heat exchanger with small features (pins), a given temperature profile and want to find the thermal stress. Assuming that I know the critical region that I need to focus on, would there be a way like in submodeling to look at a rough estimate with a coarse mesh and then refine that estimate? (using different body meshing did not quite work for me).
Thank you!
In principle, I would say: yes, submodeling is a possible approach when you have to deal with a big 3D model. But it is difficult to provide an exhaustive answer without details on your problem. Indeed, the use of symmetry, axisymmetry or "defeaturing", or any other clever strategy, often allow a great simplification to models that, at first sight, seem to require a huge computational effort. A FE analysis starts well before switching on the computer with the FE program.
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ANSYS LS-DYNA is a useful tool for those users who need to analyze problems involving contact, large deformations, nonlinear materials, high frequency response phenomena and/or problems requiring explicit solutions.
For me the answer to the requirement of modeling a large model is:
a) Leave the ANSYS workbench
b) Run the large model in batch mode on a real HPC system, no longer on a local workstation. A Linux Cluster for example.
c) With installing a RSM being connected to a supported scheduler on a Linux Cluster one even would not need to leave ANSYS Workbench. But this is rather a rare occurrence in my experience, because operators of large Linux Clusters usually do not care so much about the very specific needs of one particular software like this from ANSYS. Large Linux Clusters are more of general purpose, while ANSYS RSM is a very specific solution being of use only for ANSYS users.
With sufficient parallelization memory bottlenecks can be overcome as well, since each added Linux cluster nodes adds its own amount of memory to the problem solution capability.
Regards,
Dr. Th. Frank.
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