The influence of facing stiffness on the performance of two geosynthetic reinforced soil retaining walls
Bibliographic record
Abstract
Current limit equilibrium-based design methods for the internal stability design of geosynthetic reinforced soil walls in North America are based on the American Association of State Highway and Transportation Officials (AASHTO) Simplified Method. A deficiency of this approach is that the influence of the facing type on reinforcement loads is not considered. This paper reports the results of two instrumented full-scale walls constructed in a large test facility at the Royal Military College of Canada. The walls were nominally identical except one wall was constructed with a stiff face and the other with a flexible wrapped face. The peak reinforcement loads in the flexible wall were about three and a half times greater than the stiff-face wall at the end of construction and about two times greater at the end of surcharging. The stiff-face wall analysis using the Simplified Method gave a maximum reinforcement load value that was one and a half times greater than the measured value at the end of construction. Furthermore, the surcharge pressure required to reach the creep-limited strength of the reinforcement was about two times greater than the predicted value. The results demonstrate quantitatively that a stiff facing in a reinforced soil wall is a structural component that can lead to significant reductions in reinforcement loads compared to flexible facing systems.Key words: geosynthetics, retaining walls, reinforced soil, wrapped face, structural facings.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".