Axial Crushing Behavior of Aluminum Square Tube with Origami Pattern
Bibliographic record
Abstract
The study of axial crushing behavior is important in designing crashworthy structures especially in automotive applications. The axial crushing of thin-walled tube has better energy absorption capability. Thus, introducing milled geometrical shapes on thin-walled tube may improve the energy absorption performance. The improvement of the crush response is determined through the reduction of the Initial Peak Force (IPF) and the increase of the Specific Energy Absorption (SEA). This was done by employing origami pattern milled on the surface of thin-walled square tube which was investigated experimentally and numerically. The material used for the tube was aluminum alloy 6063-T5. The simulation results were validated by experiments which were conducted using Instron 3382 Universal Testing Machine and Instron Dynatup 8250 Drop Hammer Machine. The numerical simulation then progressed by varying parameters such as dimensions and configurations of the origami pattern on the square tube. ABAQUS finite element (FE) software was used to conduct the numerical simulation. The result of employing the origami square pattern on square tube is expected to improve the crush response by lowering the IPF and increasing the SEA. The obtained results were then compared with the conventional square tube where the origami pattern on square tube enhanced the crush performance.
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) | 0.002 | 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".