CFD simulations of the wind-induced pressure distribution on double-curvature cable domes: Impact of geometrical parameters
Bibliographic record
Abstract
Double-curvature cable domes exhibit superior stability and rigidity compared to their positive-curvature counterparts. However, their inherent flexibility and lightweight nature make them highly sensitive to wind loads. Given the absence of clear regulations in existing design codes for such innovative structures, this study aims to investigate the impact of three geometrical parameters on wind-induced mean and peak pressures on these roofs: (i) cable and strut arrangement, (ii) structure height, and (iii) saddle-shaped roof curvature. The evaluations are based on high-fidelity Scale-Adaptive Simulations (SAS) computational fluid dynamics (CFD) simulations. The results of mean pressure coefficient show minimal effect from variations in cable and strut arrangement, whereas significant sensitivity is observed in both structure height and roof curvature. Specifically, reducing the structure height from 0.4 to 0.1 of the dome span results in a 0.38 decrease in the negative wind pressure coefficient, while changing the saddle roof height from 0.25 to 0.1 of the span leads to a reduction of 1.5 in the negative wind pressure coefficient at the middle of the roof and an increase of 0.4 at the leading edge. A comparison with the design peak pressure coefficient specified in CNR-DT 207/2018 for hyperbolic-paraboloid roofs shows an underestimation of suction at several locations, with a maximum deviation of 1.5. • A numerical CFD model is developed and validated with wind tunnel experiment. • The pressure distribution on double-curvature roofs is evaluated. • The evaluation is based on Scale-Adaptive Simulations (SAS). • The impact of different geometrical parameters is investigated. • A comparison with peak pressure in CNR-DT 207/2018 is conducted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".