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Record W4210863708 · doi:10.1016/j.jmrt.2022.02.022

Low cycle fatigue behavior of Inconel 706 at 650 °C

2022· article· en· W4210863708 on OpenAlexaff
Hojun Oh, Soyoung Kim, Jung Gi Kim, Firooz Taleghani, Sangshik Kim

Bibliographic record

VenueJournal of Materials Research and Technology · 2022
Typearticle
Languageen
FieldEngineering
TopicHigh Temperature Alloys and Creep
Canadian institutionsLockheed Martin (Canada)
FundersMinistry of Trade, Industry and Energy
KeywordsMaterials scienceAlloyCarbideMetallurgyInconelAcicularMicrostructureIntergranular corrosionGrain boundarySuperalloy

Abstract

fetched live from OpenAlex

Low cycle fatigue (LCF) behavior of 2- and 3-step-aged Inconel 706 (IN706) specimens that were prepared from the center and the periphery of forged disc was examined at 650 °C and an R ratio of −1. The resistance to LCF of IN706 alloy was greater in approximately half order at 650 °C than that of IN718 alloy for the same aging condition. Elevated temperature Coffin–Manson relationship between 2- and 3-step-aged IN706 specimens was similar with each other, despite a considerable difference in microstructure. The fractographic analysis suggested that cluster of carbides provided the sites for crack initiation for both 2- and 3-step-aged specimens. The mode of fatigue crack growth for each specimen was intergranular and transgranular, but with different magnitude for each mode. Depending on the location of specimen preparation form the forged block of IN706 alloy, no notable difference in LCF resistance was found. The role of grain boundaries, clusters of carbides and bands of acicular η platelets on the initiation and propagation mechanism of IN706 alloy was discussed based on detailed fractographic and micrographic analyses.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.021
GPT teacher head0.291
Teacher spread0.270 · 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.

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

Citations18
Published2022
Admission routes1
Has abstractyes

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