Noise mapping and acoustic evaluation of different pavements in the city of Fortaleza, northeast Brazil.
Bibliographic record
Abstract
The Climate Action Plan developed by the Brazilian city of Fortaleza has encouraged active mobility aiming pedestrians' prioritization, thermal and drainage benefits, which has led to replacement of Asphalt Concrete (AC) surface layers by Interlocking Concrete Pavers (ICP) and Porous Friction Course (PFC). This work aims to evaluate the impact of these infrastructure changes on environmental noise levels. As a case study, 25 measurements on an urban avenue were made in 6 road sections with AC, ICP and PFC pavement surfaces. It was modeled in CADNA-A software and some scenarios with different traffic conditions were compared. The results showed that the use of PFC led to a noise attenuation of 3 dB(A) in LAeq when compared to AC. A reduction in the maximum speed limit from 60 kmph to 50 kmph led to a noise attenuation of 1.2 dB(A). In the section with ICP, measured data showed reduction in speed and traffic flow when compared to other pavements. Thus, despite the higher tire/road noise caused by the ICP, its application on urban roads led to a similar LAeq. The authors conclude that the application of these alternative pavements, when accompanied by traffic calming strategies, can reduce road traffic noise.
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 | 0.003 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".