Zero-staging the Aero-derivative Marine Gas Turbine for a Step-Change Increase in Power Rating.
Bibliographic record
Abstract
Navies that sought to upgrade their fleet?s mission capability and increase their on-board load usually resorted to increasing the ship?s propulsive power. When the ship?s prime mover was a gas turbine, this could be done by zero-staging the existing gas turbine compressor. An aero-derivative gas turbine for marine propulsion was a prime candidate for zero-staging because it retained its original attributes of high power-to-weight ratio, compactness, fast start-up, and variable power output. A successful zero-staged compressor gave a step-increase in power with minimal changes to the original inlet while keeping the remainder of the installation intact. As a result, the development costs were relatively less when compared to a new replacement design with a higher power rating. The purpose of this paper is to discuss a zero-staged design method for an aero-derivative marine gas turbine for an improvement in performance and an increase in power output. Here, a sequential approach was taken when carrying out the synthesis, with the completion of each sequence serving as a gate keeper prior to proceeding to the next sequence. This resulted in the formulation of a method that assessed the feasibility of zero staging the gas turbine at the initial design phase by applying basic calculations. The simplicity of the proposed method permitted the sole use of a spreadsheet instead of the established practice of complex numerical analyses with extensive batch data processing on a computer server. The intent was to ensure the viability of the zero-stage design at the preliminary investigative phase in a simplistic manner prior to committing to a fully-fledged design project of significant cost. This approach was used as a case study on an existing medium-size aero-derivative gas turbine suitable for marine use, namely the Rolls-Royce Trent 60 Siemens SGT-A65 gas turbine. Zero-staging gave a 17% increase in power output, from 77,000 shp to 90,000 shp.
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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 | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".