Influence of Leveling Pad Interface Properties on Soil Reinforcement Loads for Walls on Rigid Foundations
Bibliographic record
Abstract
A verified numerical Fast Lagrangian Analysis of Continua (FLAC) code is used to investigate the influence of concrete- and granular-block interface properties on reinforcement loads in polyester geogrid-reinforced soil (modular) block walls seated on a rigid foundation. A nonlinear interface model simulating interfaces between concrete blocks and concrete or granular soil leveling pads calibrated against laboratory direct shear tests is implemented within the FLAC code. The code is then used to simulate 3.6-, 6- and 9-m-high block walls constructed in stages. The numerical results show that the increase in wall height during wall construction for the same wall increases the interface tangent stiffness. However, the concrete pad results in higher interface tangent stiffness compared to the granular soil pad case when other conditions are equal. For 3.6-m-high walls, the load carried by the toe when using the granular soil leveling pad is 14% less than for the concrete pad case. For 9-m-high walls, the difference in load carried by the toe for the two different leveling pads is less than 10%. The predicted reinforcement loads at the same elevation over the bottom 1/3 of the wall height for the concrete pad case are smaller than those for the granular soil pad case, but are similar over the remaining height of the wall. The results also show that the predicted reinforcement loads using the K-stiffness Method capture the trend in numerical results for the two leveling pad conditions, but are conservative (i.e. safer for design), particularly for the higher walls.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".