Instantaneous On-Engine Twin-Entry Turbine Efficiency Calculations on a Diesel Engine
Bibliographic record
Abstract
One-dimensional engine simulation codes are frequently used for engine development where turbine performance is in focus for overall engine performance. Turbocharger performance can today not be accurately simulated without adjustments of the turbine efficiency and mass flow multipliers. In spite of the fact that engine exhausts are dominated by unsteady pulsating flow the performance maps provided by the turbo manufacturers are measured under steady conditions and for a range that does not cover the entire turbine operating range. The scope of this investigation is to calculate instantaneous on-engine turbine efficiency from measured and simulated engine data. These calculations are performed as a step towards generating turbine performance maps that will allow predictive engine simulations with higher accuracy than today. Results show an asymmetric behaviour of the twin-entry turbine. Exhausts from cylinders connected to the outer turbine volute entry give significantly higher turbine efficiency than cylinders connected to the inner entry. This should be taken into consideration to gain higher simulation accuracy and/or to improve the on-engine twin-entry turbine performance.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".