Origami-inspired Mechanical Metamaterials
Bibliographic record
Abstract
Folding paper into a repeated, tessellated, origami pattern can increase the paper’s strength. Using these origami patterns as inspiration for the design of structural engineering materials can similarly enhance the materials’ properties. There are multiple aspects of origami-inspired material designs that can affect their strength and performance, such as the chosen origami fold pattern, the dimensions of the pattern, and the material from which the pattern is fabricated. Common patterns that have previously been shown to have advantageous properties include Miura, Ron Resch, Kresling, and Yoshimura origami patterns.In this thesis, three novel origami fold patterns were designed, parameterized, and mechanically tested. The three patterns included a triangular-based pattern, a rectangular-based pattern, and a square-based pattern. The first study parameterized the geometries of the novel triangular and rectangular based origami, and proved the patterns had higher specific strength moduli than a previously tested Ron Resch pattern made from the same material. The rigid polylactic acid samples fractured during impact testing, leading to the second study which used a rubber-like material to fabricate flexible triangular, rectangular, and square-based origami sheets. These sheets were capable of absorbing loads from multiple impacts without fracturing and were more effective than unpatterned sheets at absorbing impact loads. The third study focused on analysing a two-level, full-factorial, parameterization for the triangular origami patterns. The results of this analysis defined how the overall shape and curvature of the origami sheet varied as the fold angle was changed. The fourth study combined flexible and rigid materials to create multi-material origami sheets comparing the triangular, square, and Miura origami patterns. The results showed that the triangular pattern had the highest compression strength, with the Miura pattern being next strongest. The final study creates heat activated shape memory origami tubes that would be ideal for use as space-saving actuators. Overall, three new origami-inspired patterns were created in this thesis: a triangular-based pattern, a rectangular-based pattern, and a square-based pattern. They were shown to have high strength-to-weight ratios and were effective at absorbing impact loads. Consequently, the materials designed in this thesis would be ideal for lightweight structures and protective equipment.
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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 | 0.000 | 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".