Multi-material topology optimization considering both isotropy and anisotropy with fibre orientation optimization
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research on multi-material topology optimization (MMTO) considering both isotropic and anisotropic materials as candidate materials is limited. Previous studies required researchers to preselect the anisotropic material fibre orientations, which are not subject to change during the optimization. As the preselected orientations cannot change, better MMTO solutions may be overlooked. To address this issue, a novel MMTO algorithm incorporating the anisotropic material fibre orientation as a design variable is proposed, eliminating the need to preselect fibre orientations and leading to better MMTO solutions. A numerical approximation method named the carry-through method is also proposed. This allows the compliance sensitivity over anisotropic material fibre orientation to be calculated without the need for the strain–displacement matrix information, simplifying the MMTO method implementation. Comparative studies on three models demonstrate that the proposed MMTO method outperforms the existing MMTO method, achieving improvements of 7%, 10% and 14% on the objectives in these models.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it