Reliability-Based Analysis of Internal Limit States for MSE Walls Using Steel-Strip Reinforcement
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Bibliographic record
Abstract
This paper demonstrates reliability-based analysis of tensile strength and pullout limit states for mechanically stabilized earth (MSE) walls constructed with steel-strip reinforcement. Five different reinforcement tensile load models, three different pullout models, and one tensile strength model were examined. The accuracy of each model was assessed probabilistically using bias statistics in which bias was the ratio of the measured value to the predicted value. The tensile limit state included uncertainty in the tensile strength due to variability in original strength of the steel and variability in potential loss of strength due to corrosion. Reliability-based analyses were carried out considering the accuracy of the load and resistance models that appear in each limit state equation plus uncertainty due to the confidence (level of understanding) of the engineer at the time of design. The reliability index was computed using Monte Carlo simulation of the tensile strength limit state and a convenient closed-form solution that is easily implemented in a spreadsheet for the pullout limit state. A MSE wall example was used to demonstrate the general approach and to compare margins of safety using different load and resistance model combinations and reinforcement strips of different initial thickness.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it