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Record W2902764623 · doi:10.1142/s1756973718500129

Determination of Secondary Dendrite Arm Spacing for In-738LC Gas-Tungsten-Arc-Welds

2018· article· en· W2902764623 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Multiscale Modelling · 2018
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsYork University
Fundersnot available
KeywordsEquiaxed crystalsMaterials scienceMicrostructureDendrite (mathematics)TungstenMetallurgyWeld poolTemperature gradientGas tungsten arc weldingWeldingSubstructureIngotGrain sizeArc weldingAlloyGeometry

Abstract

fetched live from OpenAlex

Microstructure and defect development in the gas tungsten arc weld process is influenced by the solidification and melt-pool dynamics. Melt-pool geometrical parameters which depend mainly on heat input have profound influence on the dendrite growth velocity and growth pattern in the melt pool. Temperature magnitude and history during the process directly determine the molten pool dimensions and surface integrity. However, due to the transient nature and small size of the molten pool, the temperature gradient and the molten pool size are very challenging to measure and control. The proposed research aims to establish a methodology for characterizing direct energy deposited metals by linking processing variables to the resulting microstructure and subsequent material properties. Secondary Dendrite Arm Spacing (SDAS) optical metallographic measurements of equiaxed solidified IN-738LC gas tungsten arc welds were conducted to find a new expression that links the cooling rate that is imposed on the welding during solidification, and the resultant scale of the grain substructure.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.243
Teacher spread0.222 · 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