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Crack-Free Welding of IN 738 by Linear Friction Welding

2011· article· en· W1963789516 on OpenAlexafffund
O.T. Ola, Olanrewaju Ojo, Priti Wanjara, M.C. Chaturvedi

Bibliographic record

VenueAdvanced materials research · 2011
Typearticle
Languageen
FieldEngineering
TopicHigh Temperature Alloys and Creep
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLiquationMaterials scienceWeldingMetallurgyIntergranular corrosionFriction weldingGrain boundaryHeat-affected zoneFusion weldingCrackingAlloyInconelMicrostructureComposite material

Abstract

fetched live from OpenAlex

Inconel 738 (IN 738), like other precipitation-hardened nickel-base superalloys that contain a substantial amount of Al and Ti, is very difficult to weld due to its high susceptibility to heat-affected zone (HAZ) cracking during conventional fusion welding processes. The cause of this cracking, which is usually intergranular in nature, has been attributed to the liquation of various phases in the alloy, subsequent wetting of the grain boundaries by the liquid and decohesion across one of the solid-liquid interfaces due to on-cooling tensile stresses. In the present work, crack-free welding of the alloy was obtained by linear friction welding (LFW), notwithstanding the high susceptibility of the material to HAZ cracking. Gleeble thermomechanical simulation of the LFW process was carefully performed to study the microstructural response of IN 738 to the welding thermal cycle. Correlation between the simulated microstructure and that of the weldments was obtained, in that, a significant grain boundary liquation was observed in both the simulated specimens and actual weldments due to non-equilibrium reaction of second phase particles, including the strengthening gamma prime phase. These results show that in contrast to the general assumption of LFW being an exclusively solid-state joining process, intergranular liquation is possible during LFW. However, despite a significant occurrence of liquation in the alloy, no HAZ cracking was observed, which can be partly related to the nature of the imposed stress during LFW

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.301
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations17
Published2011
Admission routes2
Has abstractyes

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