Shape Design of Periodic Cellular Materials Under Cyclic Loading
Bibliographic record
Abstract
This paper presents a method to improve the fatigue strength of 2D periodic cellular materials under a fully-reversed loading condition. For a given cell topology, the shape of the unit cell is synthesized to minimize any stress concentration caused by discontinuities in the cell geometry. We propose to reduce abrupt geometric changes emerging in the periodic microstructure through the synthesis of a cell shape defined by curved boundaries with continuous curvature, i.e. G2-continous curves. The bending moments caused by curved cell elements are reduced by minimizing the curvature of G2-continuous cell elements so as to make them as straight as possible. The asymptotic homogenization technique is used to obtain the homogenized stiffness matrix and the fatigue strength of the synthesized cellular material. The proposed methodology is applied to synthesize a unit cell topology described by smooth boundary curves. Numeric simulations are performed to compare the performance of the synthesized cellular solid with that of common two dimensional lattice materials having hexagonal, circular, square, and Kagome shape of the unit cell. The results show that the methodology enables to obtain a cellular material with improved fatigue strength. Finally, a parametric study is performed to examine the effect of different geometric parameters on the performance of the proposed cellular geometries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".