Investigation into the sediment accumulation processes that occur in permeable interlocking concrete paving systems in Australia
Bibliographic record
Abstract
One of the guiding principles of water sensitive urban design (WSUD) is centred on mitigating adverse effects of urban stormwater runoff such as increased urban flooding and deteriorating receiving water quality. In WSUD, permeable interlocking concrete paving (PICP) systems are known to be an effective source control measure to reduce stormwater flows and pollution loads. However, little is known about the effective lives of PICP systems in Australian practice because of their relatively recent emergence as a WSUD technology. There is a perception that PICPs that are used as source control devices, and designed to infiltrate runoff, will tend to clog quickly and result in high maintenance and replacement costs. This paper presents interim results from a forensic investigation into the sediment accumulation processes that occurred in a PICP that has been in service for over eight years. Previous research literature on the clogging processes of PICPs is reviewed and the various methodologies used are examined. The main aim of this study, which included both laboratory and field work components, was to examine and quantify the sediment accumulation processes that take place within the various aggregate layers used in typical PICP systems under rainfall and runoff Australian conditions. Initial results of the forensic investigation are presented in the paper. The final results of this research will have significant long term implications for stormwater management in Australia. The research will provide the answers to various important questions relating to future implementations of PICPs and alleviate many of the perceived problems associated with these systems.
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 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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".