Experimental analysis of large-scale pullout tests conducted on polyester anchored geogrid reinforcement systems
Bibliographic record
Abstract
The pullout resistance of reinforcement, such as geogrids in mechanically stabilized earth (MSE) walls, includes the skin friction between the soil and solid geogrid surfaces. It also includes the bearing resistance against the transverse ribs, which has a greater influence on the production of pullout resistance. Taking the current limitations involved in producing woven polyester geogrids into consideration (i.e., the limited thickness of the transverse ribs), the amount of bearing resistance developed in front of transverse ribs is limited in the pullout mechanism. Thus, along with introducing an innovative and applied system, this research has endeavoured to demonstrate the effective performance of this new system in increasing the passive resistance — and thereby the pullout resistance — of standard geogrids. This new system, which is formed by adding steel transverse elements (a set of steel equal angles) to the ordinary polyester geogrids by means of nuts and bolts, is called an anchored geogrid (AG). The experimental results show that a spacing-to-height ratio of transversal elements equal to 5 gives the maximum pullout resistance for a polyester AG system in sandy soil used in the study. With an optimum arrangement, this system is capable of increasing the pullout resistance of the ordinary geogrid system by 65%. In addition, based on the plasticity solution, the pullout bearing failure mechanisms of a single isolated transverse element in the polyester AG system depend on overburden pressures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".