Concave surfaces and acoustics of performance spaces—Part II —Wave analysis
Bibliographic record
Abstract
Conventional wisdom states that having concave surfaces as the envelope of any occupied space does not produce good sound. The focussing effect of concave surfaces can cause high sound pressure levels, coloration, and echoes. However, throughout history there have been many enclosed rooms with large curved surfaces as envelopes that seem to produce good acoustics. Recent research suggested that wave analysis must be undertaken to establish the impact of concave surfaces. In contrast to Part I of the current investigation, evaluation of the sound pressure level distribution, in rooms with concave surfaces, was performed by solving the governing wave equation. The main reason is that the image-ray theory is valid only at frequencies greater than the Schroeder cut-off frequency. The wave theory is used for frequencies lower than 100 Hz. Finite element modelling was applied to solve for the sound pressure level distribution within rooms with concave surfaces. Three spaces, the Paul Crocker Gallery in Ryerson University, Toronto, St. Pauls Anglican Church in Toronto and Wigmore Hall in London were investigated in this study. The results for three low frequencies (25 Hz, 50 Hz, and 100 Hz) as well as their combination will be presented in this paper.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".