Time-dependent pullout behavior of glass fiber reinforced polymer (GFRP) soil nail in sand
Bibliographic record
Abstract
Glass fiber reinforced polymer (GFRP) materials are gaining increasing use in geotechnical engineering applications in recent years. The long-term performance of reinforced geostructures may be influenced by the rheological properties of GFRP soil nails or anchors. However, a clear understanding of this effect is lacking. This work aims to investigate the interaction between GFRP soil nail and sand under pullout conditions considering the time-dependent effect. A time-dependent model was proposed to describe the load–deformation characteristics of a GFRP soil nail during pullout. Laboratory pullout tests were performed using a load-controlled pullout apparatus to verify the effectiveness of the proposed model. Quasi-distributed fiber Bragg grating (FBG) optical fiber sensors were adhered on the pre-grooved GFRP soil nail to capture the variations of axial strain during testing. The test results are presented, interpreted, and discussed. It is shown that there is good agreement between the simulation results and the experimental data under low stress levels. Additionally, the impacts of model parameters on the predicted time-dependent pullout behavior of a GFRP soil nail were examined through parametric studies. The results indicate that the distributions of tensile force and GFRP–sand interfacial shear stress along the nail length are highly time dependent. The creep displacement of a GFRP soil nail is significantly influenced by the rheological parameters of the proposed model.
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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) | 0.000 | 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) | 0.000 | 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 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".