Evaluation of Pervious Concrete Pavement Maintenance Methods at Field Sites in Canada
Bibliographic record
Abstract
Pervious concrete pavement offers sustainable solutions to urban growth challenges by providing a stormwater management alternative. The benefits of pervious concrete pavement are experienced by the environment and community. In order for pervious concrete pavement to have extensive use in Canada, maintenance needs must be understood and proven. Maintenance may not always be required but is often needed to maintain adequate performance of pervious concrete. The Centre for Pavement and Transportation Technology at the University of Waterloo, Cement Association of Canada and industry members have partnered to carry out a Canada wide study to evaluate the performance of pervious concrete pavement in the Canadian freeze-thaw climate. This paper will present the results to date related to the work that has been done in evaluating maintenance methods. Maintenance methods have been evaluated at four of the five test sites that have been constructed across Canada in this project. In general, the results indicate that it is essential to agitate the debris in the voids in order to remove as much as possible. This can be achieved by sweeping either with a stiff broom or street sweeper. Following sweeping, power washing and vacuuming have both been found to be effective. Simply rinsing the surface using a garden hose has also improved the permeability of the field site. An important detail to note is that sites that start with a low permeability cannot generally be renewed to a high level of permeability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".