Geosynthetic reinforcement stiffness characterization for MSE wall design
Bibliographic record
Abstract
Reinforcement stiffness is a key parameter that influences the magnitude of tensile loads in geosynthetic mechanically stabilized earth (MSE) walls under operational conditions. An estimate of reinforcement creep stiffness at 2% strain and 1000 h is required to carry out internal stability design using the Simplified Stiffness Method. This paper provides equations that can be used to estimate the reinforcement creep stiffness based on the tensile strength for different reinforcement product types. The paper also explores how the tensile strength values of a product can vary depending on the population of tests used to compute strength values. The differences in choice of nominal tensile strength based on lot-specific and minimum average roll value (MARV) are discussed. The paper demonstrates that the Simplified Stiffness Method soil failure limit state will usually control the selection of the reinforcement and not the tensile strength limit state. While the primary motivation for this study is to find creep stiffness values for the Simplified Stiffness Method, the stiffness-strength equations are useful in other applications such as numerical modelling of geosynthetic-reinforced structures where a reinforcement stiffness value corresponding to post-construction low tensile strain conditions is required.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".