Thermal insulation of flexible pavements utilizing foam glass aggregates to mitigate frost action in cold regions — Development of design tools
Bibliographic record
Abstract
This manuscript focuses on the use of foam glass aggregates (FGAs) as insulator to protect pavements against frost action. The ultimate objective of the paper was to develop design tools for the thermal design of pavements insulated with FGAs. A mathematical model was outlined to describe the complex thermal behavior of FGAs and calculate temperature levels within a domain representing a pavement insulated with FGAs. The formulation is based on the one-dimensional heat equation which was discretized with a forward finite-difference technique and subsequently coded in Fortran90. This code was executed to successfully replicate temperature measurements collected within an experimental pavement insulated with FGAs, enabling the validation of the model. The model was then re-executed to perform three different sensitivity analyses and investigate the effects of the pavement geometry, layers humidity, and FGAs’ effective particle size on the maximal frost front penetration. Compared to a pavement without insulation, utilizing FGAs reduced the maximal frost front depth. The sensitivity analyses were summarized in design charts to guide the utilization of FGAs for the thermal design of pavements. The code utilized to generate these charts is freely available on GitHub.
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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".