Design Model for Roughness and Serviceability of Pavements on Expansive Soils
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A model was developed to predict pavement roughness caused by both expansive soils and traffic in terms of the serviceability index (SI) and the International Roughness Index (IRI). The model correlates the roughness analysis to the vertical movement estimated from the Texas A&M University suction-based method. The total vertical movement (including both swelling and shrinking) at the edge of pavement sections, the geometry of the pavement, site conditions, traffic, and the level of reliability were used as model parameters. Total movements calculated at the edge of pavement sections were based on a relationship between moisture content and suction, exponential suction envelopes, volume change coefficients, pavement treatments, and roadside conditions. Pavement treatments included vertical and horizontal barriers, inert soil, and lime-stabilized or cement-stabilized layers. The movements in wheelpaths at a distance from the edge of pavement were estimated on the basis of both field observations and the computed results of a transient finite element analysis. Transverse distribution of vertical movements on a pavement cross section was estimated. A relationship between IRI and SI was developed on the basis of surface profile measurements in several pavement study sections. 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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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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