Evaluation of Sandwich Panels Strengthened by Different Corrugated Aluminum Cores Under Flexural and Compressive Loadings
Bibliographic record
Abstract
The developed design of sandwich structure and the appropriate selection of its core materials and geometries proven its efficient applications in lightweight structures.This study aims to quantify the best core geometries and positions that can carry a higher stiffness without weight compromising.To do so, the flexural strength applying fourpoint bending test, compressive strength and stiffness of aluminum ( Al) facesheets strengthened by two different aluminum corrugated square and triangle cores, oriented in flatwise and edgewise positions, i.e., flatwise square (FS), edgewise square (ES), flatwise triangle (FT), and edgewise triangle (ET).The results indicated the sandwich panels with ET core had the highest flexural strength of 28 MPa at lower deflections, and the lowest strength of 13 MPa for panels with FT cores.The highest compressive strength of 81 MPa and the highest specific strength of 516 MPa/Kg were obtained with ES core sandwich panels co MPa red to 21 MPa and 120 MPa/Kg for panels with FT core.For all cases, the deformation occurred near surface buckling and core crushing.The sandwich panels with ET and ES cores showing a higher load-carrying capacity under the bending load due to the standing direction of the stiff Al struts, while the sandwich structures with FT and FS cores have totally slipped, bent and destroyed at lower loads.This study provides advice for the development of sandwich structures with various core geometries/orientations used in a range of engineering applications.
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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) | 0.001 | 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".