A CWE/WT Study of the Flow over High- and Low-Rise Buildings, with Anisotropic Mesh Optimization
Bibliographic record
Abstract
This paper addresses the critical issue of the accuracy of CFD predictions in wind engineering. Flows around both a high-rise building, the Jin Mao Tower, and low-rise (but largespan) buildings from the Pudong International Airport, are computed with the Navier-Stokes solver FENSAP and compared to experiments in a unique academic-architectural collaboration framework (China-Canada Architectural Wind Simulation Center). Computations are carried out for two wind directions, with FENSAP solving the steady-state ensemble-averaged NavierStokes equations and the Spalart-Allmaras turbulence model. Pressure coefficients compare well with wind tunnel experiments. The accuracy of the flow solutions is further improved by using automatic mesh adaptation that dynamically places grid points where the flow physics require them, while keeping the number of unknowns (and hence the solution time) substantially at the same level.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".