Evaluation of the Use of Solar Assisted Buoyancy Driven Natural Ventilation of Smaller Theatres in Canada
Bibliographic record
Abstract
The possibility of using stored hot water generated during the day by using solar energy to assist in the provision of adequate buoyancy driven natural ventilation flow rates through small theatres during the evening hours has been numerically investigated in a very basic manner. The hot water would be used to heat the air using a plate type heat exchanger system mounted in a roof-top chimney-like air discharge system. A simple building with a given cross-sectional design has been considered. Two-dimensional steady flow has been assumed to exist and the flow has been assumed to be symmetrical about the vertical centre-line through the building. The Boussinesq approximation has been adopted, i.e., the air properties have been assumed constant except for the density change with temperature that gives rise to the buoyancy forces, this being treated assuming a linear relation between the density changes and the temperature change. Radiant heat transfer effects have been neglected. The standard k-epsilon turbulence model with buoyancy effects being fully accounted for has been used. The heat generation from the audience has been treated as a uniformly distributed heat flux over the floor, the smaller the audience, the lower being this heat flux. The solution has been obtained using the commercial CFD solver FLUENT©. The results, while of a very preliminary nature, indicate that the proposed system could provide an adequate natural ventilation flow rate.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".