Vertical Facing Panel-Joint Gap Analysis for Steel-Reinforced Soil Walls
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Bibliographic record
Abstract
This paper reports the results of a numerical parametric study focused on the prediction of vertical load distribution and vertical gap compression between precast concrete facing panel units in steel-reinforced soil walls ranging in height from 6 to 24 m. The vertical compression was accommodated by polymeric bearing pads placed at the horizontal joints between panels during construction. This paper demonstrates how gap compression and magnitude of vertical load transmitted between horizontal joints are influenced by joint location along the height of the wall, joint compressibility, and backfill and foundation soil stiffness. The summary plots in this study can be used to estimate the number and type (stiffness) of the bearing pads to ensure a target minimum gap thickness at the end of construction, to demonstrate the relative influence of wall height and different material component properties on vertical load levels and gap compression, or as a benchmark to test numerical models used for project-specific design. The paper also demonstrates that although the load factor (ratio of vertical load at a horizontal joint to weight of panels above the joint) and joint compression are relatively insensitive to foundation stiffness, the total settlement at the top of the wall facing is very sensitive to foundation stiffness. This paper examines the quantitative consequences of using a simple linear compressive stress–strain model for the bearing pads versus a multilinear model that is better able to capture the response of bearing pads taken to greater compression. The study demonstrates that qualitative trends in vertical load factor are preserved when a more advanced stress-dependent stiffness soil hardening model is used for the backfill soil as compared with the simpler linear elastic Mohr–Coulomb model. Although there were differences in vertical loads and gap compression with the use of both soil models for the backfill, the differences were small and not of practical concern.
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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) | 0.000 | 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