Solution convergence in Generative Design
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Hello,
I'm having issues understanding how Generative Design works... Based on a model, I ran 2 studies differing only from their objective type :
- Stiffness increase objective ; Constraints : safety factor (SF)=1 and mass target = M
- Mass reduction objective ; Constraint : SF=1
The same geometry results from both cases with a mass of ~4*M and a minimal SF of ~10. Firstly, I understand that all constraints cannot always be verified. However, in the case of Study 1., none has even been reached (in other words, the stresses are "low" and the mass in "high").
Anyway, I decided to investigate what happens if I reduce the SF in order to bring the stresses closer to the elastic limit. Since it is not possible to set SF<1, I left it set to 1 and manually increased the elastic limit. It should be equivalent, right ? However it had no effect on the results.
I thought about setting a maximum thickness constraint to force reducing the mass but the solution did not converge at all.
So could anyone please help me understand what's happening here ? How can I manage to reduce the mass closer to my target ? How could I possibly impose a maximum thickness constraint and make it converge ? Why do both objective types provide the same results in my case ? Are some constraint types prioritized with respect to others ?
Thanks a lot and best regards
Raphael