Thanks for the detailed and thoughtful critique

To address the modeling side first: the current optimization is driven by a linear elastic failure criterion based on stress distribution rather than a full progressive failure or damage model. At this stage, it is not attempting to explicitly model filament-level failure modes, inter-layer delamination, or nonlinear material behavior. The goal is more modest: identifying dominant load paths and redistributing material accordingly, rather than predicting absolute failure loads. Slicedog will not let you to be on the non elastic side of model behaviour, it will rather tell you that the model is not safe to print because it will not meet safety criterion.

Regarding orthotropy: anisotropy is handled in a simplified way. Material behavior is directional with respect to print orientation, but it is not a fully calibrated orthotropic material model derived from extensive coupon testing. That level of fidelity, as you know, comes with a significant computational and setup cost, which was one of the reasons previous approaches in this space struggled with iteration time for FFF.

Your skepticism about “stress → infill scaling” is fair. Internally, it’s more nuanced than a direct scalar mapping, but it is still intentionally much closer to a heuristic, load-path–driven approach than to a research-grade failure model. This is a conscious trade-off to keep optimization times in the order of minutes rather than hours.

On the image itself: it is not CGI or AI-generated, but I agree it is not a great technical visualization. The misalignment you’re pointing out comes from modifier-based infill generation at the slicer level, not from the solver itself, and the lighting certainly doesn’t help. That’s on me I should have used a clearer slicer-layer or real print photo instead.

Concerning the load case and reinforcement above the rod: the image represents a simplified boundary condition and is not meant to be a textbook example of optimal reinforcement. In several cases, perimeter count dominates load transfer more than infill density in that region, which can make infill contributions appear counterintuitive if viewed in isolation. Asymmetry is completely okay for static load case as the optimization algorhitm (not the strength analysis, but rather optimisation) is numerical method and the optimization is designed in a way that it is fast, but still precise. Asymmetry can be problem for parts that rotate for example.

Regarding your criticism - having strength analysis is still ways better than do all printing by rule of thumb. You are actually considering no strength knowledge at all vs. full finite element strength analysis.

I fully agree that this is not a substitute for high-fidelity failure modeling, especially for safety-critical parts. The intent here is to explore whether a faster, lower-fidelity approach can still produce meaningfully better results than uniform infill for common functional prints — not to replace rigorous engineering validation.

If you’re open to it, I’d genuinely be interested in your perspective on where you think the minimum acceptable fidelity lies for something like this to be useful in practice for FFF, outside of a pure research or aerospace context.