Reverberation measurement and prediction in gymnasia with non-uniformly distributed absorption; The importance of diffusion
Bibliographic record
Abstract
As part of a performance verification exercise reverberation times (RT) were measured in several newly constructed school gymnasia, rectangular in plan with two variations in room size, all with similar finishes and constructions. Due to architectural constraints, the rooms have acoustically hard finishes below a height of 3 m. The room finishes are primarily acoustically reflective with the exception of continuous bands of absorptive upper wall paneling around the full perimeter of the rooms (exposed unpainted Tectum over mineral fibre insulation) and painted acoustic metal deck ceilings (fiberglass insulation in the perforated deck flutes). The initial RT measurements exceeded the design targets. Modeling using ODEON room acoustics prediction software was conducted to determine the quantity and placement of additional absorption required to bring the RT into compliance. After installation of an additional continuous band of absorptive paneling in the rooms at a height below the existing panels, the RT were re-measured. The midband average RT increased, with a 0.5 sec RT increase at 1000 Hz in one room and a 1 sec RT increase at 1000 Hz in another. Further investigation lead to the hypothesis of an insufficiently diffuse sound field and uninterrupted standing wave modes in the lower untreated portion of the room contributing to the unexpected results. RT were subsequently re-measured under 5 different conditions; an empty gym, addition of 5 people, and 3 levels of diffusion. Diffusion was varied by adding sheets of plywood (5, 10, 15 sheets) leaned against posts or each other. The addition of as few as 5 people or 5 plywood sheets was found to significantly reduce the measured RT, closer to the modeled predictions, with between a 0.6 sec and 1 sec reduction observed in the mid-band average RT from the empty condition.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 0.001 |
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".