Using Field Data to Evaluate Bottom Ash as Pavement Insulation Layer
Bibliographic record
Abstract
A common problem in cold regions is the penetration of frost into susceptible subgrade soils. This study investigated the application of bottom ash in comparison with polystyrene boards as an insulation layer at a test road in Edmonton, Alberta, Canada. The adjacent normal section was used as the control section. All sections were instrumented at various depths to monitor temperature variation. On the basis of temperature measurements in the base and subgrade layers from October 2012 to June 2013, frost depth and freezing and thawing periods were analyzed for each section. R-values for thermal resistivity were calculated for each layer, considering its thickness and thermal properties, and were used for justifying and comparing the temperature trends. R-values were established at 1.4 and 16.7 m 2 • °C/W for the bottom ash and polystyrene board, respectively. The base layer in the polystyrene section experienced higher temperatures in the summer and lower temperatures in the winter in relation to the bottom ash and control sections. On the basis of temperature measurements at depths of 1.61 to 3.27 m, the subgrade in the polystyrene section showed the lowest variation in temperature with respect to time and depth, followed by the bottom ash and then the control section. This behavior indicated that the insulation layers obstructed the heat transfer between the surface and the lower layers. The use of polystyrene boards and bottom ash as insulation materials decreased the frost depth by at least 40% and 28%, respectively, compared with the control section.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".