Preliminary Development of Cold Spray Procedures for Nickel Aluminum Bronze Casting Repair
Bibliographic record
Abstract
Nickel aluminum bronze (NAB) castings possess favourable combinations of strength and resistance to corrosion, biofouling and cavitation/erosion, and so have long been used in naval applications. Nonetheless, in seawater environments NAB castings are susceptible to selective phase corrosion and so such components periodically require either replacement, which is very costly, or repair. However, repairs involving traditional, high heat input welding operations can lead to distortion and microstructural changes that unacceptably degrade NAB corrosion performance, and so repairs are not commonly performed. In the present work, cold spray is explored as an alternative for NAB (alloy CuAl9Fe5Ni5) repair without excessive distortion or base metal degradation, and preliminary results of its performance reported. Suitable cold spray parameters have been determined using an iterative approach by analyzing deposits in terms of microstructure, porosity and adhesion to the substrate. It is intended that these parameters will later be used to create simulated repairs which can be more thoroughly characterized for strength, toughness and corrosion 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".