Design and optimization of graded lattice structures with load path-oriented reinforcement
Bibliographic record
Abstract
Lattice structures have been increasingly used in load-carrying applications due to their exceptional mechanical performance. This study presents a novel load path methodology for designing and optimizing functionally graded lattice structures composed of anisotropic unit cells with directional reinforcement struts. Firstly, the optimal density distribution of the lattice structure is obtained by solid isotropic material with penalization (SIMP) topology optimization. Secondly, pointing stress vectors of the structure are calculated to determine the orientations of the unit cells. Lastly, the lattice model is constructed using tapered beams for a smooth transition between struts with different radii. Two examples of a simply supported beam and a 3-dimensional base support structure are provided. The experimental validation showcases that the proposed design improves the specific stiffness by 75 % compared to the uniform body-centered cubic design. Furthermore, the strength-to-weight ratio is increased by 232 % due to a more desirable stress distribution.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".