On the Accuracy of Multi-Block Lattice Boltzmann Methods for Aeroacoustic Simulations
Bibliographic record
Abstract
The Lattice Boltzmann Method is emerging as a powerful computational tool in Computational Fluid Dynamics and Computational Aeroacoustics. The disparity of length scales present in any realistic problem often requires the use of multi-block computational grids with dierent resolution. Although the use of multi-block grids allows the accurate computations of the main flow features, previous studies have showen that spurious tones may appear in radiated sound spectra when Aeroacoustic signatures are of interest. These socalled VR tones were hypothesized to be due to spurious wave reflection from the block boundaries. In the present study, VR tone generation was investigated with the purpose of developing numerical methods for their reduction or elimination. The propagation of a canonical cylindrical wave through the boundary between coarse and fine grids was studied using a D2Q9 lattice scheme. It was observed that high frequency waves, which cannot be resolved properly on the coarser grid, were reflected back from the grids interface. A grid overlap with a spatial low-pass filter was developed to remove the spurious reflected waves, thereby eliminating VR tones. The use of successive coarsened blocks along with low-pass filtering was used to construct a sponge-layer boundary condition analogous to the grid stretching technique used by Rai and Moin(1991). The inclusion of such numerical schemes in aeroacoustic simulations based on Lattice Boltzmann methods may improve upon the accuracy of existing multi-block schemes .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".