On the experimental validation of combustion simulations in turbulent non-premixed jets
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Bibliographic record
Abstract
A Reynolds averaged Navier–Stokes (RANS) based combustion model, which incorporated the conditional source-term estimation (CSE) method for the closure of the chemical source term and the trajectory generated low-dimensional manifold (TGLDM) method for the reduction of detailed chemistry, was applied to predict the OH radical distribution in a combusting non-premixed methane jet. The results of the numerical prediction were compared with the results of a complementary experimental study in which the OH radical fields of combusting non-premixed methane jets were visualized using planar laser induced fluorescence (PLIF). It is well known within the modelling community that RANS based models are unable to capture the stochastic nature of turbulent combustion and autoignition, and are therefore unable to predict individual realizations of the flame. In this study, the agreement between the predicted OH field and a well-converged ensemble average of the experimental results was also shown to be poor. The lack of agreement between the numerical results and the ensemble averaged experimental results expose the potential significance of the known weakness in the RANS method. A statistical analysis of the experimental results was also performed. The results of the analysis showed that a minimum of 100 individual realizations was required to provide a well-converged average OH field for the combusting non-premixed jet under investigation. The significance of this result with respect to the validation of large-eddy simulations (LES) of combusting jets is discussed.
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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 | 0.000 | 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