The optimization calculates the approximated von Mises stress and shows these stress values in the postprocessing.
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The eleceted elected stress goal is the overall optimization goal for each the optimization and has a big influence on the resulting design. The target is that the material of the part is evenly loaded and the stress uniformly distributed. Thus, the stress goal isn’t the maximum stress , which can occur at design space limits or due to FE singularities, but the value which is a good middle value for a long part life. Not in every case the yield strength of the material is the best value for this parameter, e.g. when the applied loads are too small to result in such stresses. By changing the stress goal, the stiffness of the structure can be influenced as well. Due to uniformly distributed stresses, lower stress goals result in stiffer parts at the most lightweight design.
The used stress goal is dependent on the resolution levels. The optimization runs on different resolution levels and switches between them to achieve the best results. The first iterations are calculated on a coarse resolution level. With rising number of iterations, the resolution gets finer. This means that the first iterations calculate much faster than the last iterations but aren’t as detailed as the last. With the increasing resolution, the size of the output data, the calculation time as well as the surface quality increase.
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The stress calculation is from an FE point of view an estimation. That’s why we recommend a FE reanalysis using Apex Structures/Nastran to verify the results regarding all boundary conditions. For the reanlysis reanalysis the intersected model should be used which will be manufactured and used. The reanalysis can also take dynamic loading & other boundary conditions into consideration that are not considered in the design process. For more information regarding intersection have a look here.
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