Balanced noise control design: A case study for co-generation power plant
Bibliographic record
Abstract
Power generation plant generally requires noise mitigation treatment to achieve the specified noise regulations. In this paper, a case study of the noise control design for a cogeneration power plant was presented. Major noise sources included two GE gas combustion turbines, two generators, two heat recovery steam generators (HRSGs), one steam turbine and generator, one 12-cell cooling tower, and other accessory equipment. The acoustic modeling software Cadna/A was used to predict the noise contributions from sources. During the acoustic modeling, alternative noise mitigation measures underwent two specific investigations before they were chosen as a noise solution recommendation. The first was to determine the technical feasibility of attenuating the source equipment. The second was to perform a cost benefit analysis, necessary to find the most cost-effective solution. For example, several acoustic wall and roof assemblies were entered into the acoustic model and the acoustic performance of the ventilation system was varied until we were able to arrive at the most economical acoustic solution. This is the premise on which so called balanced design is based.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".