Sensitivity Study on Species Diffusion Models in Turbulent Combustion of Hydrogen/air Jet in Crossflow Structure
Bibliographic record
Abstract
Abstract CFD approach has been intensively used for novel hydrogen combustion technologies as well as emissions prediction. In order to minimise time and costs, simplified combustion CFD models have been developed to take into account of the effect of turbulence-chemistry interactions, coupled with both RANS and LES models. These models often employ assumptions that have been validated for conventional fuels such as Jet-A1 and natural gas. It is clear that the preferential diffusion and thermal diffusion play a vital role in hydrogen laminar premixed flames. Conventionally, it is believed that for high Re cases, turbulent diffusion is dominant, preferential diffusion and thermal diffusion only have a minor effect. For highly turbulent non-premixed flames, these effects have not been fully investigated. The appropriate modelling of these effects is essential for reaction rate, flame temperature and emissions prediction. There is a need to study the sensitivity of different species diffusion models for hydrogen-air flames. Within the current study, a single micromix injector burning a hydrogen air mixture with an overall equivalence ratio of 0.4 has been simulated in a systematic RANS campaign, and compared with LES. The RANS campaign employs two combustion models: FGM with the kinetic rate closure and Complex Chemistry (CC) with both the laminar flame concept (LFC) and eddy dissipation concept (EDC) closures. The LES employs the same combustion models. The sensitivity of Lewis and Schmidt numbers have been investigated for FGM and EDC model. As expected, FGM is insensitive to the value of Le and Sc whereas for LFC, significant changes have been observed between Le = 0.25 and 0.5, Sc = 0.5 and 0.75. Several species diffusion coefficient models have been used with both LFC and EDC, including: mixture averaged, multi-component and multi-component with thermal diffusion coefficients. All three approaches of modelling molecular diffusivity yielded flame lengths and temperatures of a similar order. The micromix flame was found to be a mixture of both premixed and non-premixed, with jets of strongly premixed and non-premixed originating from the hydrogen injectors. The sensitivity of turbulent Sc and Le numbers has also been studied with LFC models. It was clearly shown that these changes lead to more significant variation in flame length and temperature compared to those caused by different molecular diffusivity models. LES results with various multi-component diffusion models are compared, the results are in better agreement relative to RANS with different models. The similarity in flame length and insensitivity to CC closure type demonstrates the dominance of turbulence in determining flame structure, through turbulent mixing.
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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".