An Attempt at Large Eddy Simulation for Combustor Modeling
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
Large eddy simulation (LES) is a promising method for numerical simulation in combustion systems. A LES attempt in a model combustor has been made, and a few important issues related to grid size, inflow condition, wall boundary conditions, physical sub-models and data sampling are discussed. Some of the numerical results are presented and compared with a comprehensive experimental database, which indicates that LES can provide reasonable predictions for the mean axial velocity and temperature distributions inside the combustion chamber. However, in order to make LES a valuable and cost-effective tool in the development of advanced combustion systems, some fundamental questions remain to be addressed and more validation efforts are required. Moreover significant computing power is required for LES to capture both the high and low frequencies of interest in the present turbulent reacting flow.
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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 | 0.001 | 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 | 0.001 |
| 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