Comparison of Field Performance of Conventional and Recycled Drainage Systems using Non Destructive Structural Asset Management
Bibliographic record
Abstract
The severity of the climatic and loading circumstances to which roads are subjected will necessitate the structural rehabilitation of many urban roads in the near future. Specifically, many urban roads have substructures that are wetted-up and are prone to structural failure. On account of both increased climatic effects and increased heavy traffic loading, drainage systems are an integral component of road systems. While conventional virgin crushed rock can be used for drainage layers, virgin aggregate sources have become increasing scarce in many cities, leading to higher costs involved to obtain these materials. Recycled Portland cement concrete (PCC), which has been stockpiled by the City of Saskatoon for the past five years, offers an alternative to conventional materials. The purpose of this study was to investigate and compare the field performance of both conventional and recycled drainage systems. Laboratory testing and heavy weight deflectometer (HWD) testing were employed to determine the structural performance of four roads with four different drainage layers. Drainage layers examined included conventional jaw and cone crushed PCC, virgin crushed rock, impact crushed recycled PCC, and impact crushed PCC with a sand drainage layer underneath. It was found that impact crushed recycled PCC is a viable alternative to virgin crushed rock, as its structural integrity was comparable to that of virgin crushed rock. The performance of conventional crushed PCC was inferior to impact crushed PCC and inferior to virgin crushed rock. Also, the addition of a sand drainage layer significantly improved the performance of the road structure.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".