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Record W2801776300

Radiation Damage Effect on Mechanical Properties and Microstructure of X-750 Ni-based Superalloy

2018· dissertation· en· W2801776300 on OpenAlexaboutno aff
P. Changizian

Bibliographic record

VenueQSpace (Queen's University Library) · 2018
Typedissertation
Languageen
FieldEngineering
TopicHigh Temperature Alloys and Creep
Canadian institutionsnot available
Fundersnot available
KeywordsSuperalloyMicrostructureMaterials scienceMetallurgyRadiation hardeningRadiationOpticsPhysics
DOInot available

Abstract

fetched live from OpenAlex

Inconel X-750 is an age-hardened Ni-based superalloy with high mechanical strength and creep resistance. The X-750 alloy is extensively used in the cores of reactors, such as spacers in CANada Deuterium Uranium (CANDU) fuel channels. The recent mechanical tests on the ex-service Inconel X-750 spacers indicate significant embrittlement and reduced load carrying capacity compared to as installed condition. The primary degradation mechanism remains unclear, and thus provides the focus of this investigation. Heavy-ion irradiation was employed as an emulator for neutron irradiation to explore the microstructural evolution and mechanical property degradation in X-750 Ni-based superalloy. The ion-irradiation has been conducted at different temperatures and up to different doses. In addition, helium-implantation prior to heavy-ion irradiation was used to investigate the effect of helium on microstructural changes. The discussion of the microstructural evolution is focused on characterization of irradiation-induced defects, including dislocation loops and cavities along with examination of the stability of strengthening phase γ'-precipitates. A major contribution of this work is to utilize a focused ion beam (FIB) and transmission electron microscopy (TEM) to perform precise defect characterization. The microstructure is correlated to the mechanical properties obtained via nano-hardness test on irradiated materials. In order to estimate the individual contribution of defects in radiation-induced hardening, three different obstacle-hardening models have been applied to fit TEM-obtained microstructural data. The superposition of contributions is made in each model and compared with nano-scale experimental results. This approach is unique to the literature since it demonstrates both the individual and the combined effects of the microstructural features on mechanical behavior. Furthermore, the effect of gamma-prime instability on mechanical properties of irradiated X-750 was investigated and the strength softening raised from disordering and also dissolution of gamma-prime was evaluated.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score1.000

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 integrity0.0010.000
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 head0.003
GPT teacher head0.156
Teacher spread0.153 · 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.

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

Citations1
Published2018
Admission routes1
Has abstractyes

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