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Record W7106815965 · doi:10.14288/cjur.v7i1.195416

The Metallurgical Troubles of Hastelloy -N in Molten Salt Reactors

2021· article· en· W7106815965 on OpenAlexaffabout

Bibliographic record

VenueOpen Collections · 2021
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMolten saltCoolantMolten salt reactorOak Ridge National LaboratoryShut downWork (physics)Liquid fluoride thorium reactorNuclear reactor

Abstract

fetched live from OpenAlex

Many nuclear energy companies, including two based in Canada (Moltex Energy and Terrestrial Energy), have become interested in reactors that use molten salts in place of water as coolant and as a medium to hold the fuel. They draw technical inspiration from the Molten Salt Reactor Experiment (MSRE), a reactor that operated from 1964 to 1969 at the Oak Ridge National Laboratory, Tennessee (ORNL). One of the challenges with molten salt reactors involves metallurgical materials used to manufacture the various reactor components. These materials would have to work in a highly corrosive environments at elevated temperatures. A new alloy named Hastelloy-N was developed for this purpose. This literature review examines at a high level the technical problems associated with using Hastelloy -N as a nuclear construction material. After the MSRE was shut down in 1969, Hastelloy-N was found to be inadequate, because it had developed cracks, leading to a decrease in mechanical properties such as creep strength. Such material deficiencies could have catastrophic results inside a nuclear reactor. These problems have alarming implications for the feasibility of the molten salt reactor designs proposed for Canada.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes2
Has abstractyes

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