Prediction of Roughness of Pavements on Expansive Soils
Bibliographic record
Abstract
A model was developed to predict pavement roughness due to both expansive soils and traffic in terms of serviceability index (SI) and international roughness index (IRI) by correlating the roughness analysis to the vertical movement estimated from a vertical movement model. The total vertical movement, including both swelling and shrinkage, at the edge of pavement sections, the geometry of the pavement, and site conditions were used as model parameters. Total movements calculated at the edge were based on exponential suction envelopes, volume change coefficients, pavement treatments and roadside conditions. Pavement treatments include vertical and horizontal barriers, inert soil and lime- or cement-stabilized layers. The movements in wheel paths at a distance from the edge of pavement are estimated based upon both field observations and the computed results of a transient finite element analysis. A relationship between IRI and SI was developed. The design equations that were developed for both flexible and rigid pavements include the effects of traffic and expansive soil and permit the selection of the desired level of reliability.
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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".