arXiv Machine Learning September 11, 2026 By Yongmin Kwon, Namwoo Kang

Zero-shot rib design: merging training-free generative prior with topology optimization

Read the original on arXiv Machine Learning →

The paper introduces a method that integrates a frozen text‑to‑image diffusion model into density‑based topology optimization via score distillation sampling. By converting a natural language prompt into a generative gradient, the approach lets physics decide which design features survive, achieving significant compliance reductions across multiple domains and physics regimes. An automated pipeline then transforms the optimized density fields into CAD‑ready geometries.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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