Mechanical Evaluation of Mixed As-Cast and Friction Stir Processed Zones in Nickel Aluminum Bronze
Bibliographic record
Abstract
Abstract The performance of nickel aluminum bronze (NAB) propellers can be limited by the resistance of the alloy to fatigue. Friction stir processing (FSP) is a potential method for improving the fatigue life and fracture toughness of this material through grain structure refinement. As friction stir processing is a surface treatment, as-cast, thermo-mechanically affected zone (TMAZ), and FSP zone microstructures can all occur in components with thick cross sections and when FSP is performed on only selected areas of the component surface. The boundary between modified and unmodified microstructures produced by traditional processing techniques (i.e., heat affected zones produced by welding) are often the source of in-service failures as they can contain defects, residual stresses, deleterious microstructures or any combination thereof. In this paper, the mechanical behavior of FSP nickel aluminum bronze specimens containing as-cast, TMAZ, and FSP microstructures are evaluated using monotonic tensile tests and rotating bending fatigue tests. Analysis of the fatigue specimen fracture surfaces indicate that fatigue cracks initiated and propagated through the as-cast microstructure before penetrating the TMAZ and the FSP microstructures. The tensile specimens failed in the as-cast structure away from the FSP zone and the TMAZ. These results indicate that the as-cast material is weaker than both the FSP and the TMAZ, implying that localized friction stir processing is not detrimental to the mechanical behavior of a NAB component, even in the boundary region.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".