Challenges with Construction of Portland Cement Concrete Pavement at Calgary International Airport
Bibliographic record
Abstract
In preparation for construction of a parallel runway at the Calgary International Airport in the spring of 2011, concrete pavement had to be constructed to realign Gates A1–A10. Concrete mixes were developed for central batch production for both paver and hand placement methods. In addition, winter conditions required concrete delivery from a local concrete ready-mix supplier. The construction schedule required the paved sections to be open to aircraft traffic three weeks after pavement construction. A maturity method was developed to estimate early age compressive/flexural strength of the concrete pavement. This paper presents the process utilized in developing the concrete mix design to meet the project requirements for Cement Stabilized Base (CSB) and the Portland cement concrete mix, the development of the plant mix, and the construction methodology. Additional challenges with pavement construction in winter conditions are highlighted, including CSB and concrete placement, curing conditions, control joint construction, and instrumentation for maturity of concrete determination. The verification process for final acceptance of the product is described, including durability testing and pavement design review. This project demonstrated that concrete pavement can be constructed under accelerated schedule and during adverse weather conditions with the quality of the pavement not compromised and the construction schedule successfully managed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".