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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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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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