Study of Additive Manufacturing of Hastelloy X Using Plasma Arc Welding Technology
Bibliographic record
Abstract
Plasma arc welding (PAW) was implemented for additive manufacturing (AM) of Hastelloy X wire due to its potential to produce thin-wall structures for a high-temperature resistance of Hastelloy X. Single-layer beads were deposited to study and optimize the effects of eight process parameters (arc length, nozzle size, built-in and trailing shielding gas flow rate, wire feed rate, travel speed, current, and linear energy density).In the meantime, an additional trailing shielding mechanism was introduced to reduce surface oxidation while maintaining acceptable geometry for multiple-layer deposition.A multiple regression method was used to determine the influence of these parameters on the extent of oxidation, geometry, height and width of bead.The optimized parameters were then used for multiple-layer depositions where complete fusion without visible voids was achieved.However, some interface separations were found due to the minor surface oxidation between layers.Equiaxed-to-columnar grain structure was also observed along the deposition direction where molybdenum carbides were present.The final samples were further evaluated by hardness test.A superior isotropic hardness (HV 218) was achieved on the multiple-layer sample when compared with wrought Hastelloy X (HV 179).Multiple-layer depositing techniques were satisfactorily developed in this study.The optimized PAW process was proven to prevent overheating during starting and ending portion of the deposition.Heat reduction for each successive layer was also determined to produce a wall structure.
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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".