Bibliographic record
Abstract
The latest version of ShipIR/NTCS (v4.3) includes a more generalized 4-point (quad) element type that not only reduces the total number of surface elements in the ShipIR model, but also delivers a higher-quality coarse wall boundary mesh on which to construct the coupled CFD wall boundary and volume meshes for use in CFD analysis. The objective of the current paper is to explore the impact of these improvements on the coupled ShipIR / ANSYS Fluent CFD model solutions previously discussed for both naval ships (Vaitekunas et al, 2011) and aircraft (Vaitekunas 2022). In the case of the naval ship, methods and inputs used to characterize the exhaust gas plume trajectory and associated risk of plume impingement on specific areas of the superstructure are described and applied to a coupled ShipIR / ANSYS Fluent CFD model of the CFAV Quest. These techniques are used during the detailed design phase of a new warship to help further reduce the risk of combat system equipment failure and/or elevated thermal IR signatures associated with exhaust gas impingement heating.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.212 | 0.102 |
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".