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Record W4285044524 · doi:10.22215/etd/2022-15090

Study of Additive Manufacturing of Hastelloy X Using Plasma Arc Welding Technology

2022· dissertation· en· W4285044524 on OpenAlexaff
Wei Wang

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsCarleton University
Fundersnot available
KeywordsMaterials scienceMetallurgyEquiaxed crystalsWeldingPlasmaPlasma arc weldingGas tungsten arc weldingHigh-speed steelCarbideComposite materialMolybdenumShielding gasArc weldingAlloy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.016
GPT teacher head0.253
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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