Evolution of surface roughness and particle breakage with interface shear behaviour of sand-epoxied GFRP against sand under elevated normal stress
Bibliographic record
Abstract
Glass fibre-reinforced polymer (GFRP) composites are interestingly adopted in geotechnical applications, especially in harsh marine environments. However, their inherently smooth surface and relatively low hardness may compromise interface performance with soil. The application of a sand-epoxy coating enhances surface roughness, friction, and hardness, making it essential to assess its behaviour under moderate to large normal loads for reliable offshore deployment. A comprehensive investigation of surface roughness evolution in both uncoated and sand-epoxied GFRP composites is conducted through interface tests, emphasising their interface shear performance when sheared against standard silica sand under moderate to high normal stress. The optimal sand-epoxy coating combination is determined through monotonic testing, while long-term performance is evaluated by cyclic testing combined with measurements of roughness variation. Results show that surface roughness evolution and particle breakage intensify with increasing median particle size, cycle number, and normal stress. Cyclic shearing exhibits higher interfacial friction angles compared to monotonic shearing. This trend results from the synergistic interplay of surface degradation, particle breakage, particle interlocking, and stress redistribution at interface under elevated normal stress. Ultimately, design charts are developed to facilitate the practical deployment of optimised sand-epoxied GFRP composites for durable reinforcement in applications such as foundations and marine structures.
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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) | 0.000 | 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 | 0.001 |
| 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".