MétaCan
Menu
Back to cohort
Record W2357668566

No-core-melt assessment for Canadian-SCWR under LOCA/LOECC

2015· article· en· W2357668566 on OpenAlexaboutno aff
Wu Pa

Bibliographic record

Venue核技术(英文版) · 2015
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear engineeringCoolantHeat transferCladding (metalworking)Decay heatMaterials scienceLoss-of-coolant accidentThermal conductionNatural convectionCore (optical fiber)ConvectionEnvironmental scienceMechanicsMechanical engineeringEngineeringComposite materialPhysics
DOInot available

Abstract

fetched live from OpenAlex

The safety analysis code SCTRAN for SCWR(Super Critical Water Reactor) is modified to own the capability to assess the radiation heat transfer with developing a two-dimensional heat conduction solution scheme and incorporating a radiation heat transfer model. The verification of the developed radiation heat transfer model is conducted through code-to-code comparison with CATHENA. The results show that the modified SCTRAN code is successful for that the maximum absolute error and relative error of the surface temperature between results of SCTRAN and CATHENA are 6.1°C and 0.9%, which are acceptable in temperature prediction. Then,with the modified SCTRAN code, the loss of coolant accident with a total loss of emergency core cooling system(LOCA/LOECC) of Canadian-SCWR is carried out to evaluate its no-core-melt concept. The following conclusions are achieved: 1) in the process of LOCA, the decay heat can be totally removed by the radiation heat transfer and the natural convection of the high-temperature coolant, even without an intervention of ECCS(Emergency Core Cooling System); 2) The peak cladding temperature of the fuel pins in the inner and outer rings of the high power group are 1236°C and 1177°C respectively, which are much lower than the melting point of the fuel sheath. It indicates that the Canadian-SCWR can achieve no-core-melt concept under LOCA/LOECC.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score0.999

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 head0.027
GPT teacher head0.240
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

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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venue核技术(英文版)Same topicNuclear reactor physics and engineeringFrench-language works237,207