Probabilistic Analysis of a MSE Wall Considering Spatial Variability of Soil Properties
Bibliographic record
Abstract
The results of probabilistic analyses of a mechanically stabilized earth (MSE) wall with geosynthetic reinforcement are presented. The analyses consider spatial variability of reinforced and foundation soil properties using the 2D non-circular random limit equilibrium method (RLEM). In this study, it is assumed that the reinforced soil is a purely frictional soil, while the foundation is a cohesive-frictional (c-ϕ) soil. A negative cross-correlation between cohesion and friction angle and a positive cross-correlation between cohesion and unit weight, and between friction angle and unit weight are also assumed. It is shown in this study that, considering only random variability of soil properties results in an overly-conservative probability of failure for design. However, considering spatial variability of soil properties plus cross-correlation between soil input parameters provides an estimate of probability of failure which is in better agreement with the margin of safety implied using a deterministic factor of safety.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".