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A new perspective on the mechanical behavior of Inconel 617 at elevated temperatures for small modular reactors

2025· article· en· W4407636943 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueScripta Materialia · 2025
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversity of Alberta
FundersNatural Resources Canada
KeywordsInconelMaterials scienceModular designPerspective (graphical)MetallurgyNuclear engineeringMechanical engineeringForensic engineeringEngineeringAlloyComputer science

Abstract

fetched live from OpenAlex

This study investigates the temperature-dependent mechanical properties of Inconel 617, a nickel-based superalloy, for small modular reactor applications. The formation of the sigma phase, driven by high chromium content during prolonged high-temperature exposure, significantly impacts the alloy's strength, creep resistance, stress rupture life, and ductility. The transition temperature for sigma phase formation is predicted to be approximately 1064 C ∘ , with an uncertainty range between 700 C ∘ and 1250 C ∘ , confirmed through an uncertainty analysis of elemental composition. Chromium is identified as the primary element influencing sigma phase stability. Additionally, hot tearing susceptibility during solidification is assessed, revealing that a carbon content of 0.08 wt % minimizes the cracking susceptibility coefficient to 0.425, reducing the risk of solidification cracking. These findings offer critical insights for optimizing the composition and processing conditions of Inconel 617 in laser-directed energy deposition additive manufacturing.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.664

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 head0.015
GPT teacher head0.229
Teacher spread0.213 · 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