Parallel Solution Adaptive Scheme for Three-Dimensional Turbulent Diffusion Flames with Detailed Tabulated Chemistry
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Bibliographic record
Abstract
Mathematical modelling of the e ects of turbulence on detailed-chemistry is an important issue in the accurate and reliable numerical prediction of turbulent combustion processes. The highly non-linear nature of both turbulence and chemistry make this extremely challenging. In this study, a Presumed Conditional Moment (PCM) approach, based on a probability density function (PDF), is combined with the Flame Prolongation of ILDM (FPI) tabulation method to model the e ects of turbulence and detailedchemistry for di usion ames. The recently proposed FPI scheme incorporates the e ects of the detailed-chemistry on the local ow eld for laminar ames through the use of two independent scalars: mixture fraction and progress variable and their variances. The Favre-Averaged Navier-Stokes (FANS) equations, based on the two-equation k-! turbulence model, are used herein to model the e ects of the unresolved turbulence on the mean ow eld. The governing partial-di erential equations for mean quantities are solved using a parallel, Adaptive Mesh Re nement (AMR), fully-coupled nite-volume formulation on bodytted, multi-block, hexahedral mesh for three-dimensional ow geometries. Two approaches for coupling the PCM-FPI approach with the parallel AMR nite-volume solution method are considered. The PCM-FPI results are compared to experimental data for both reacting and non-reacting ows associated with a Sydney blu -body burner conguration. The computational cost of the PCM-FPI scheme is compared to the cost of the simpli ed Eddy Dissipation Model (EDM). A full description of the proposed numerical solution scheme for turbulent non-premixed ames is provided along with an evaluation and demonstration of its computational performance and predictive capabilities.
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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