Laminar Flame Speed Measurements and Modeling of Pure Alkanes and Alkane Blends at Elevated Pressures
Bibliographic record
Abstract
Alkanes such as methane, ethane, and propane make up a large portion of most natural gas fuels. Natural gas is the primary fuel used in industrial gas turbines for power generation. Because of this, a fundamental understanding of the physical characteristics such as the laminar flame speed is necessary. Most importantly, this information is needed at elevated pressures to have the most relevance to the gas turbine industry for engine design. This study includes experiments performed at elevated pressures, up to 10-atm initial pressure, and investigates the fuels in a pure form as well as in binary blends. Flame speed modeling was done using an improved version of the kinetics model that the authors have been developing over the past few years. Modeling was performed for a wide range of conditions, including elevated pressures. Experimental conditions include pure methane, pure ethane, 80/20 mixtures of methane/ethane, and 60/40 mixtures of methane/ethane at initial pressures of 1, 5, and 10 atm. Also included in this study are pure propane and 80/20 methane/propane mixtures at 1 and 5 atm. The laminar flame speed and Markstein Length measurements were obtained from a high-pressure flame speed facility using a constant-volume vessel. The facility includes optical access, a high-speed camera, a schlieren optical setup, a mixing manifold, and an isolated control room. The experiments were performed at room temperature, and the resulting images were analyzed using linear regression. The experimental and modeling results are presented and compared to previously published data. The data herein agree well with the published data. In addition, a hybrid correlation was created to perform a rigorous uncertainty analysis. This correlation gives the total uncertainty of the experiment with respect to the true value rather than reporting the standard deviation of a repeated experiment. Included in the data set are high-pressure results at conditions where in many cases for the single-component fuels few data existed and for the binary blends no data existed prior to this study. Overall, the agreement between the model and data is excellent.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".