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Effect of Thermal Cycle on Microstructure and Corrosion Behavior of Duplex Stainless Steel SAF 2205 Electron Beam Welded Joint

2018· article· en· W2899753394 on OpenAlex

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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

VenueKey engineering materials · 2018
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsCanadian MPS Society for Mucopolysaccharide and Related Diseases
Fundersnot available
KeywordsMaterials scienceMicrostructureCorrosionMetallurgyVolume fractionAlloyAusteniteBase metalWeldingComposite material

Abstract

fetched live from OpenAlex

It is known that heat treatment (HT) highly affects the properties of base metal (BM) and fusion zones (FZ) of duplex stainless steel (DSS). In fact, it may give unwanted structure changes. Duplex stainless steels SAF 2205 welded joint was subjected to thermal cycle at temperature of 850 ◦ C at holding times 1, 3, 5 and 7 hours. The influence of heating cycles and concentration of corrosive medium on the corrosion properties and microstructure of 2205 alloy was the objective of this work. It was found that process led to noticeable decrease in the corrosion resistance of BM and FZ specimens; moreover the decrease was large in BM than FZ. It was also found that sigma phase (σ) precipitated in the different zones of the structure. σ phase volume fraction was found to increase with increasing the holding time of HT, and its increase is larger in BM. Corrosion resistance was found to be oppositely related to σ phase formation. Secondary austenite phase (γ 2 ) was also precipitated and its volume fraction in FZ was found to increase with increasing the holding time of HT and decreased in BM.

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)0.001
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 score0.007
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.233
Teacher spread0.227 · 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