Performance Advantages of Turbine Oils Formulated with Group II and Group III Basestocks
Bibliographic record
Abstract
High temperature gas turbine applications, such as GE Frame 7 turbines, place high demands on the thermal and oxidative stability of turbine oils. Successful products not only start with a superior quality basestock, but must also employ a carefully balanced, low volatility, thermally stable additive system. The excellent properties of Group II and Group III basestocks such as high viscosity index, low volatility, superior oxidative resistance, and high thermal stability make them ideal choices for this service. Turbine oils formulated with severely hydrocracked Group II and Group III basestocks offer performance on par with those formulated with synthetic hydrocarbons. A brief review of the role and requirements of modern turbine oils is given together with a more extensive look at current basestock technology versus traditional solvent refined basestocks. Additive selection for high temperature turbine oils is also discussed. In addition, data presenting the impact of poly-cycloparaffin content on the stability of highly saturated Group II and Group III basestocks is presented. The oxidative stability of additized basestocks increases as poly-cycloparaffin content decreases.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".