Effect of Internal Ribs on Fatigue Performance of Sandwich Panels with GFRP Skins and Polyurethane Foam Core
Bibliographic record
Abstract
This paper investigates the cyclic fatigue behavior of sandwich panels composed of glass fiber reinforced polymer (GFRP) skins connected by longitudinal Z-shape ribs and low-density polyurethane foam core. Eighteen 1,143×635×78-mm panels with ribs of two different flange widths, including three control static tests, were tested in fatigue under fully reversed loading (R=−1) and fully unloaded (R=0) conditions, to maximum loads (Pmax) of 20–70% of their ultimate static strength (Pult). Fatigue life curves were established and compared with those of panels without any ribs. It was shown that internal ribs increased static strength and stiffness by 80 and 66%, respectively, but were only beneficial within the low cycle fatigue range. Under Pmax of 50% Pult, number of cycles to failure (Nf) at R=−1 was only 6% of Nf at R=0 in the ribbed panels. Fatigue failure consistently initiated by flange debonding of the rib from skin. In panels loaded to higher than Pult of their nonribbed counterparts, final shear failure of foam core occurred simultaneously with rib debonding, whereas in panels loaded below this level, additional fatigue life was attained after rib debonding, until core shear failure, but at significantly lower stiffness. To achieve an Nf of 2M cycles, Pmax should not exceed 35 and 21% of Pult at R=0 and −1, respectively. A three-dimensional (3D) failure surface (Haigh diagram) was established for the ribbed panels. It predicts fatigue life for a given mean and amplitude loads.
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".