A comparison of two design methods for unpaved roads reinforced with geogrids
Bibliographic record
Abstract
The design of geosynthetic-reinforced unpaved roads is based on a limit equilibrium analysis of bearing capacity at the ultimate limit state. Two semiempirical design methods are shown to be predicated on a common fundamental relation, but differ in the parameterization of input groups. Degradation of subgrade strength with repeated loading is well characterized by each design method and is believed to be of primary importance in obtaining good agreement between the result from analysis and the observed response to field trafficking. The two design methods were found to require different values for the undrained shear strength of the subgrade, which is partly attributed to the significantly different load spread angles used to model the effect of the base course. Selection of the initial undrained shear strength deserves careful consideration in sensitive soils. In order to use one of the design methods, it is important to select this value so that it is consistent with the other parameter groups being used.Key words: bearing capacity, geogrid, unpaved road.
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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 | 0.001 | 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".