Numerical evaluation of the effect of multiple roughness changes
Bibliographic record
Abstract
The effect of multiple roughness changes close to a building site was examined through three dimensional computational fluid dynamics (CFD) simulations conducted in a virtual boundary layer wind tunnel (V-BLWT). The results obtained were compared with existing wind speed models, namely ESDU-82026 and Wang and Stathopoulos (WS) model. The latter was verified by wind tunnel tests of sixty nine cases of multiple roughness patches, and also with a simplified 2D numerical model. This work extends that numerical study to three dimensions and also models roughness elements explicitly. The current numerical study shows better agreement with the WS model, that has shown better agreements with BLWT tests, than the ESDU model. This is in contrast to previous results of Wang and Stathopoulos, who concluded that CFD shows better agreement with the ESDU model. Many cases were simulated in a V-BLWT that has same dimensions as BLWT used in the original experiment and also in a reduced symmetrical version (S-BLWT) that takes advantage of regular arrangement of roughness blocks. The S-BLWT gives results almost identical to V-BLWT simulations, while achieving significant reduction on computational time and resources.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".