Experimental and analytical behaviour of sandwich composites with glass fiber-reinforced polymer facings and layered fiber mat cores
Bibliographic record
Abstract
This paper presents the results of experimental and analytical studies on the behaviour of sandwich beams fabricated with layered cores and glass fiber-reinforced polymer (GFRP) composite facings. The GFRP facings were fabricated using a unidirectional fiberglass fabric and epoxy resin, and the cores were fabricated using a thin non-woven continuous-strand polyester fiber mat with a thickness of 4.1 mm. A total of 30 sandwich beams with the width of 50 mm were prepared tested with five varying core configurations including cores made with one, two, or three layers of the fiber mat core and with or without the inclusion of intermediate GFRP layers. The specimens were tested up to failure under four-point bending at two different spans to characterize flexural and shear properties of the specimens. Two types of failure were observed, namely crushing of the compression facesheet and core shear. The load-deflection, load-strain, and moment-curvature behaviour were analyzed and using the results the flexural stiffness, shear stiffness, and core shear modulus were calculated. An analytical model was also developed to predict load-deflection behaviour and failure loading of sandwich specimens with varying core layouts. After verification, the analytical model was used for a parametric study of cases not considered in the experimental study, including additional GFRP and fiber mat core layers. It was shown that additional fiber mat core layers and the inclusion of intermediate GFRP layers can increase the strength and overall stiffness of a sandwich beam, while additional GFRP layers can only increase the overall stiffness of the system. The analytical model can be used to optimize the configuration of layered sandwich composites for cost effective rehabilitation techniques of culverts, pipelines, and other curved-shape structures where a thin, flexible core is needed to accommodate the curvature of the existing structure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".