Large Eddy Simulations of a Pressurized, Partially-Premixed Swirling Flame With Finite-Rate Chemistry
Bibliographic record
Abstract
Finite-rate chemical effects at gas turbine conditions lead to incomplete combustion and well-known emissions issues. Although a thin flame front is preserved on an average, the instantaneous flame location can vary in thickness and location due to heat losses or imperfect mixing. Post-flame phenomena (slow CO oxidation or thermal NO production) can be expected to be significantly influenced by turbulent eddy structures. Since typical gas turbine combustor calculations require insight into flame stabilization as well as pollutant formation, combustion models are required to be sensitive to the instantaneous and local flow conditions. Unfortunately, few models that adequately describe turbulence-chemistry interactions are tractable in the industrial context. A widely used model capable of employing finite-rate chemistry, is the Eddy Dissipation Concept (EDC) model of Magnussen. Its application in large eddy simulations (LES) is problematic mainly due to a strong sensitivity to the model constants which were based on an isotropic cascade analysis in the RANS context. The objectives of this paper are: (i) To formulate the EDC cascade idea in the context of LES; and (ii) To validate the model using experimental data consisting of velocity (PIV measurements) and major species (1-D Raman measurements), at four axial locations in the near-burner region of a Siemens SGT-100 industrial gas turbine combustor.
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 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".