A Study of the Flow Field and Combustion of Natural Gas-Air inside a Gas Turbine Combustor
Bibliographic record
Abstract
This paper presented a study of the natural gas combustion in a swirl gas turbine combustor. The effect of the primary air swirl number, primary air/fuel mass ratio and the secondary/primary air mass ratios on the flow field and combustion characteristics of natural gas in air is investigated. For this purpose, a test rig was constructed including a vertical test combustor provided with an air swirler mounted at its upstream. Primary air, secondary air, and fuel lines are also included. Four different air swirlers having the same blockage ratio of 0.72 are used for the present investigation. The swirlers have the same hub (inner) diameter of 72 mm and the same outer diameter of 100 mm. The swirlers have different vane angles of 15 o , 30 o , 45 o , and 60 o to generate swirl numbers of different strengths of about 0.23, 0.5, 0.85 and 1.5, respectively. A three dimensional model was used to simulate the non reacting and reacting flows by using the computational fluid dynamics package Fluent 6.3. Comparing the measured test data with the numerical computations, a reasonable agreement is found. The results show that, increasing the primary air/fuel ratio and the secondary/primary air mass ratio leads to decreasing the average flame temperature and consequently the flame size. Increasing the secondary/primary air mass ratio leads to a decrease in the axial CO and CO 2 concentrations and an increase in O 2 concentration at the combustor exit.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".