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Record W2295661647 · doi:10.1115/icone24-60876

New IAEA Coordinated Research Project on Thermal-Hydraulics of Supercritical Water Cooled Reactors

2016· article· en· W2295661647 on OpenAlexaff
Katsumi Yamada, L.K.H. Leung, Walter Ambrosini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsCanadian Nuclear Laboratories
FundersNuclear Power Institute of China
KeywordsThermal hydraulicsHydraulicsScheduleBenchmark (surveying)Nuclear engineeringSystems engineeringEngineeringNeutron transportEngineering managementComputer scienceMechanical engineeringOperations researchHeat transferAerospace engineeringNuclear physicsPhysicsOperating systemNeutron

Abstract

fetched live from OpenAlex

In view of the high interest among a number of Member States in the Supercritical Water Cooled Reactor (SCWR) concept, the IAEA launched the second Coordinated Research Project (CRP) on thermal-hydraulics of SCWRs, entitled “Understanding and Prediction of Thermal-Hydraulics Phenomena Relevant to SCWRs” in 2014 to foster international collaboration. The key objectives of this new CRP are to (i) improve the understanding and prediction accuracy of thermal-hydraulics phenomena relevant to SCWRs and (ii) benchmark numerical toolsets for their analyses. At present, 12 institutes participate in the CRP from 10 IAEA Member States, and the OECD/NEA is in cooperation, based on a special agreement with the IAEA, to host a database housing experimental and analytical results contributed from the CRP participants. The expected outcomes from this CRP include (i) enhancement of the understanding of thermal-hydraulics phenomena, (ii) sharing of experimental and analytical results, and the prediction methods for key thermal-hydraulics parameters, and (iii) cross-training of personnel between participating institutes through their close interactions and collaboration. This paper describes the plan of the new CRP: overall and specific research objectives; tasks and sub-tasks; schedule; and expected outcomes and outputs. It also introduces briefly other IAEA activities to facilitate and support R&D for SCWR technology in Member States, which include technical meetings and training courses.

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 categoriesInsufficient payload (model declined to judge)
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 score0.110
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 integrity0.0000.000
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 head0.051
GPT teacher head0.312
Teacher spread0.261 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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