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ICONE15-10650 UTILIZING NATURAL CIRCULATION IN ACR-1000 DESIGN

2007· article· en· W2111657642 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.

Bibliographic record

VenueThe Proceedings of the International Conference on Nuclear Engineering (ICONE) · 2007
Typearticle
Languageen
FieldMaterials Science
TopicGraphite, nuclear technology, radiation studies
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsNatural circulationCoolantNuclear engineeringDecay heatEnvironmental scienceLoss-of-coolant accidentCirculation (fluid dynamics)Reliability (semiconductor)EngineeringMechanical engineeringThermodynamicsPhysicsAerospace engineering

Abstract

fetched live from OpenAlex

The Advanced CANDU Reactor^<TM> (ACR^<TM>) is a Generation III+ pressure tube type reactor using light water coolant and heavy water moderator. The ACR-1000 reactor design is an evolutionary extension of the proven CANDU reactor design. The ACR-1000 utilizes natural circulation and other passive systems and features for accident mitigation. Natural circulation features may be relied upon to remove heat from the primary coolant when forced circulation is not available, from the lowpressure moderator, and to circulate the atmosphere inside the containment. This paper describes how the use of passive features, including natural circulation, complement and supplement active features, enhancing reliability and improving safety margins.

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 score0.450
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.033
GPT teacher head0.244
Teacher spread0.211 · 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