CFD Simulations of the Static Airflow Resistivity of a Perforated Solid: Effects of Size and Flow Velocity
Bibliographic record
Abstract
For acoustic absorbers, the static airflow resistivity is the parameter which has the greatest impact on their acoustic absorption coefficient in the linear amplitude regime. Therefore, its measurement according to ISO 9053 (or ASTM C522) should be conducted with care. This ISO standard gives specifications on the size and mounting of specimens, their location in the measuring cell, minimum and maximum flow velocities, calibration specimens and the measurement procedure. An important requirement is to ensure a stable linear flow so that the resistance is independent of the velocity. Additionally, it specifies the use of a calibration test specimen to ensure proper operation of both hardware and software. The suggested calibration specimen consists of straight cylindrical pores whose value can be calculated theoretically. However, no other specification is given for designing the calibration specimen. Since the airflow resistivity of a perforated low-porosity solid can behave nonlinearly with velocity, it is important to present some additional guidelines for their design. This work presents CFD simulations on the flow resistivity of a cylindrical solid containing a single perforation subjected to an air flow velocity ranging from 0.5 mm/s to 10 cm/s. The simulations replicate a commercial airflow resistivity meter. The results of the simulations are compared with the theoretical formula and the experimental measurements. The results highlight the importance of the size of the perforation (diameter and depth) and the flow velocity to ensure that the measurement aligns to the theoretical value.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".