Numerically Optimizing an Annular Diffuser Using a Genetic Algorithm With Three Objectives
Bibliographic record
Abstract
A genetic algorithm was implemented to determine preferential solutions of a short annular diffuser exhaust system of length 1.5Do (outer annulus diameters). Five free variables defined the centre body shape and two variables determined the outer wall profile. Diffuser performance was evaluated using three objectives—(i) diffuser pressure recovery, (ii) outlet velocity uniformity, and (iii) total pressure loss—that were calculated from steady state solutions obtained using the computational fluid dynamics software FLUENT 13.0 with the realizable k-ε turbulence model and enhanced wall treatment. Inlet conditions were ReDh = 8.5 × 104 and M = 0.23. After thirty-five generations, a paraboloid-shaped centre body with length 0.74Do and initial annular expansion of approximately 14° produced preferential solutions. A configuration with a converging outer wall above the centre body developed greater outlet flow uniformity and lower total pressure loss whereas a straight outer wall followed by the solid diffuser generated more static pressure recovery.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".