Naturally Ventilated Double Skin Façades: Comparisons Between Different CFD Models
Bibliographic record
Abstract
Double Skin Façades (DSFs) have become widespread solutions commonly employed in new and existing buildings in the last decades. Since its introduction, the multi-layered façade has improved profoundly, assuming more articulate and complex shapes for better energy performances and combining advanced technologies as innovative materials or systems. However, the effectiveness and the thermal behaviour of DSFs should be carefully evaluated since the design phase by selecting proper methodologies, thus avoiding inaccurate results. In fact, the correct estimation of the airflows inside DSF channels is heavily influenced by the simulation settings. Furthermore, the lack of measurements or empirical validations in the field is the primary source of concern for researchers. Considering the available numerical methods for investigating DSFs, Computational Fluid Dynamics (CFD) simulations have proven to be the most appropriate option. The present work compares multiple Double Skin Façade configurations by performing CFD analyses and adopting different turbulence models in bi- and three-dimensional domains. The results underline the capability of 2D models in predicting the fluxes inside the DSF channel and in the domain. Furthermore, comparisons among the velocity profiles estimated by adopting different turbulence formulations highlight only slight variations, especially in proximity to the perturbated areas of the cavity.
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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 | 0.000 | 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 | 0.000 | 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".