DEVELOPMENT OF THE PERMEABLE DESIGN PRO PERMEABLE INTERLOCKING CONCRETE PAVEMENT DESIGN SYSTEM
Bibliographic record
Abstract
Note: The following is the notation used in this paper: ( . ) for decimals and ( ) for thousands. Summary National, state/provincial and municipal legislation regulating stormwater runoff in the United States and Canada have provided increased incentives for using permeable pavements. In addition, regulatory frameworks for implementation of sustainable design have embraced permeable pavement solutions. These regulations are often called low impact development (LID) or sustainable urban drainage systems (SUDS). A logical and technically sound design process using design software can support design professionals and help permeable pavement achieve full potential in North America. In 2008, the Interlocking Concrete Pavement Institute (ICPI) introduced a non-proprietary software program called Permeable Design Pro that integrates hydrological and structural design solutions for permeable interlocking concrete pavement. The hydrological analysis determines if the volume of water from user-selected rainfall events can be stored and released by the pavement structure. User defined parameters determine how much water infiltrates into the soil subgrade, enters pipe subdrains or flows from the pavement surface. The structural capacity of PICP is determined using the American Association of State Highway and Transportation Officials [AASHTO, 1993] structural design equations for base/subbase thickness to support vehicular traffic. This paper describes the development of the structural and hydrological design methodology with an example of its use.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".