Bibliographic record
Abstract
This paper describes the results of modelling the performance of several indirectly fired gas turbine (IFGT) power generation system configurations based on four gas turbine class sizes, namely 5 kW, 50 kW, 5 MW and 100 MW. These class sizes were selected to cover a wide range of installations in residential, commercial, industrial and large utility power generation installations. Because the IFGT configurations modelled consist of a gas turbine engine, one or two recuperators and a furnace; for comparison purpose this study also included simulations of simple cycle and recuperated gas turbine engines. Part-load, synchronous-speed simulations were carried out with generic compressor and turbine maps scaled for each engine design point conditions. The turbine inlet temperature (TIT) was varied from the design specification to a practical value for a metallic high-temperature heat exchanger in an IFGT system. As expected, the results showed that the reduced TIT can have dramatic impact on the power output and thermal efficiency when compared to that in conventional gas turbines. However, the simulations also indicated that several configurations can lead to higher performance, even with the reduced TIT. Although the focus of the study is on evaluation of thermodynamic performance, the implications of varying configurations on cost and durability are also discussed.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".