A study on the anchoring orientations of foam and sandwich composites with metal
Bibliographic record
Abstract
Abstract Metallic anchors are used as the load transfer components for foam and sandwich composites when they are used as structural elements in design applications. The traditional method of fixation of these components is by gluing and fastening. The anchors are in the form of inserts and are imbedded in the foam during the foaming process. In this study, flexural testing was conducted on different metal anchor/foam configurations to establish typical interaction trends. The load‐deflection response, mode of failure, and fracture stresses of the structures were elucidated. Tests were conducted on foam and sandwich composites having rectangular, cylindrical, and taper geometries with different lengths. Leaf inserts were designed, manufactured, and tested inside foam and sandwich composites. Comparisons between the taper and leaf inserts are presented. Leaf inserts had better results compared with taper inserts in terms of adhesion and failure stresses. Finite element analysis (FEA) of the interactions between the inserts and the foam and sandwich composites under different loads was carried out. The FEA modeling results were very similar to the experimental results, thus validating the model. Simulations were also run with foam and sandwich composites with closeout configuration. Foam–sandwich with inserts had better adhesion and load‐bearing properties compared with same structures with closeouts. POLYM. COMPOS., 2011. © 2011 Society of Plastics Engineers
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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 | 0.001 |
| 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".