Effects of Subgrid Scale Modeling on the Deterministic and Stochastic Turbulent Energetic Distribution in Large-Eddy Simulations of a High-Pressure Turbine Stage
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study focuses on the engine-representative MT1 transonic high-pressure turbine. Simulated by use of wall-modeled large-eddy simulations (LES) with three different subgrid scale (SGS) closures, mean pressure profiles across the blades as well as mean radial profiles at the rotor exit are found to be in good agreement with experimental data with only local differences between models. Unsteady flow features, inherently present in LES, are however affected by SGS modeling. This is evidenced by the relative energetic content of the deterministic to stochastic turbulent contributions evaluated, thanks to the triple decomposition analysis of the simulations. Origins of such differences are found to impact the entire radial distribution of the flow and activity, with deterministic and chaotic contributions distributed differently depending on the SGS model and reference frequency used to extract the deterministic signal. Such flow responses can be attributed to the different SGS capacities to satisfy basic turbulent flow features that translate in different dissipative and turbulent diffusive contributions of the three SGS models.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it