In-Service Performance Evaluation of Flexible Pavement with Lightweight Cellular Concrete Subbase
Bibliographic record
Abstract
The objective of engineers to improve the long-term performance of road infrastructure in changing global climate has led to the development of alternate materials for pavement construction. Lightweight cellular concrete (LCC) is a viable option for colder climates where pavements undergo several freeze-thaw cycles each year, resulting in faster deterioration of pavements. This is due to LCCs’ excellent freeze-thaw resistance, ease of placement, and potential sustainability benefits such as reduced use of virgin material and industrial by-products. However, there is a need to quantify these benefits and develop unified specifications for using LCC in the pavement structure. Therefore, this study examined the performance of flexible pavement sections that included a subbase layer, unbound granular materials for the control section, and three LCC densities (400, 475, and 600 kg/m3) for the LCC sections. Post-construction evaluation of pavement stiffness and roughness were evaluated using a Lightweight deflectometer and SurPro equipment. The results showed that LCC subbase thickness ≥ 250 mm produced over 22% smoother riding surfaces than unbound granular pavements while increasing pavement stiffness by up to 21%. Finally, this study recommends that LCC subbase thickness should not be thinner than 250 mm when using densities below 475 kg/m3 over weak subgrades.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".