Development of an acoustic design support tool for HVAC ventilation units
Bibliographic record
Abstract
HVAC equipment is one of the main sources of noise inside or outside a building. Furthermore, many people are exposed daily to HVAC noise, which can lead to health-related troubles. Therefore, an HVAC mechanical unit must be selected to provide an acceptable sound level transmitted to the occupied spaces of a building and not disturb the community. This paper presents a prediction tool named Sound Prediction Tool (SPT) developed by MJM Acoustical Consultants Inc. in 2021 that allows the engineer (i) to design an HVAC unit with specific mechanical components (filter, coil, etc.) according to his input parameters and (ii) to predict and optimize the sound levels produced by the selected design through its casing and openings (inlet and outlet air). This tool has been validated firstly with acoustical tests ‘’in situ’’ on several separate Air Handling Units (AHU) manufactured by our customer and secondly with Finite Elements Method (FEM) models using Comsol-Multiphysics. Several examples are presented to demonstrate the usefulness of the proposed tool.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".