Comparison of dealiasing schemes in large-eddy simulation of neutrally-stratified atmospheric boundary-layer type flows
Bibliographic record
Abstract
Abstract. Three dealiasing schemes for large-eddy simulation of turbulent flows are inter-compared for the canonical case of pressure-drive atmospheric boundary-layer type flows. Aliasing errors arise in the multiplication of partial sums, such as those encountered when integrating the non-linear terms of the Navier–Stokes equations in spectral methods (Fourier or polynomial discrete series), and are detrimental to the accuracy of the numerical solution. This is of special relevance when using high-order schemes. In this work, a performance/cost analysis is developed for three well-accepted approaches: the exact 3/2 rule, the Fourier truncation method, and a high order Fourier smoothing method. Tests are performed within a newly developed mixed pseudo-spectral collocation - finite differences large-eddy simulation code, parallelized using a two-dimensional pencil decomposition. The static Smagorinsky eddy-viscosity model with wall damping of the model coefficient is used. A series of simulations are performed at varying resolution and key flow statistics are inter-compared among the considered dealiasing schemes. The numerical results validate the numerical performance predicted by theory when using the Fourier truncation and Fourier smoothing methods. In terms of turbulence statistics, the Fourier Truncation method proves to be over-dissipative when compared against the Fourier Smoothing method and the traditional 3/2-rule, leading to an enhanced horizontal integrated mass flux and to higher dispersive momentum fluxes. Its use in large-eddy simulation of atmospheric boundary-layer type flows is therefore not recommended. Conversely, the Fourier Smoothing method yields accurate flow statistics, comparable to those resulting from the application of the 3/2 rule, with a significant reduction in computational cost, which makes it a convenient alternative for use in the studies related to the atmospheric boundary layer.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".