Industrial Trent Dry Low Emissions Gas Fuel Control System
Bibliographic record
Abstract
Regulations are requiring that the emissions from land-based gas turbines be tightly controlled. To limit emissions, the Industrial Trent turbine controls flame temperature through a premixed multi-stage combustor. This requires a multi-path fuel delivery system that provides accurate and repeatable metering of the fuel. There are also requirements that the fuel system quickly stop the flow of fuel and vent appropriate lines in the case of a load rejection or an emergency shutdown. The gas system is a four-path fuel metering system that incorporates shutoff and vent capabilities in addition to high accuracy multi-path flow metering. One of the fuel paths is dedicated to the ignition torch and is significantly smaller and flow accuracies are less demanding than for the three main metering legs. The concentration of work was dedicated to providing highly accurate and repeatable flow metering for the three main fuel legs. There was also a drive to minimize cost and provide commonality of parts between each of the three legs. Current fuel schedules require metering through a 20:1 turn down ratio. Flow through each metering leg is measured in the same manner as flow measurement is performed across an orifice flow meter. The metering valve is a primary element for which the flow characteristics are well known under a large number of valve positions and flow conditions. Analysis and testing has been conducted to define flow accuracy and repeatability. Further work has been conducted to minimize pressure drop across the system and to reduce the number of sensors required.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.021 |
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".