Performance of three geogrid-reinforced soil walls before and after foundation failure
Bibliographic record
Abstract
ABSTRACT: This paper reports the results of three 4 m high full-scale instrumented geogrid-reinforced soil walls constructed with different structural facings having a range of stiffness. The walls were seated on a 2 m deep foundation layer that was laterally supported at the base of the wall face by a rigid bulkhead. Following end of construction, the bulkhead was moved outward in stages to simulate loss of foundation support in the vicinity of the wall toe. Bulkhead loads, wall deformations, backfill settlements, reinforcement loads and earth pressures recorded at end of construction and during bulkhead displacement are presented in this paper. Measured reinforcement loads are compared to predicted loads at end of construction using different design methods. The walls demonstrated that there was available reserve load capacity which prevented internal failure mechanisms from developing in the reinforced soil zone even after significant loss of foundation support in the vicinity of the wall toe. At the end of each test the reinforcement layers were shortened in stages by cutting using nichrome heating wires. For the most flexible wall in this programme, the shortening of the reinforcement triggered a composite soil failure mechanism extending from the base of the foundation zone to the surface of the soil backfill. Implications of the analysis results and other observations on wall performance and design are discussed.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".