Observed Long-Term Performance of Geosynthetic Walls and Implications for Design
Bibliographic record
Abstract
Geosynthetic-reinforced walls have been viewed by the civil engineering profession as a new technology whose acceptable long-term performance is yet to be established. Nevertheless, geosynthetic walls have been in use for almost 25 years. Much of the uncertainty associated with acceptance of geosynthetic-reinforced wall technologies is related to time-dependent deformation. This paper summarizes the creep rates measured in full-scale walls and compares them to creep rates measured in-isolation in the laboratory where the applied load level matches values estimated for the same structures in the field. In the majority of cases, the laboratory in-isolation creep rates were the same as or greater than the measured reinforcement creep rates in full-scale walls, corroborating that reinforcement load levels can be estimated from measured strain data. At the end of wall construction, it appears that the reinforcement is primarily exhibiting creep, with only minor stress relaxation. However, in the long-term, there is a trend toward reinforcement stress relaxation. Furthermore, the long-term behavior observed in the full-scale walls indicates that the reinforcement loads are well below values required to cause creep rupture over the design life of the structures and, in some cases, creep appears to have stopped completely. Finally, the paper offers quantitative guidelines to delineate anticipated poor and good long-term wall performance based largely on level of reinforcement strains and magnitude of post-construction wall deformations.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".