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Record W3105028021 · doi:10.1115/1.4049096

Experimental and Numerical Investigation of Solidification of Gallium in an Initially Emptied Horizontal Pipe Flow

2020· article· en· W3105028021 on OpenAlexaff
Shawn Somers‐Neal, Alex Pegarkov, Edgar Matida, Vinh Tang, Tarik Kaya

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2020
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsCarleton University
Fundersnot available
KeywordsCoriumMaterials sciencePenetration (warfare)MechanicsLiquid metalHeat sinkReynolds numberHeat transferComputer simulationThermodynamicsMetallurgyTurbulencePhysicsEngineering

Abstract

fetched live from OpenAlex

Abstract In a reactor core meltdown under postulated severe accidents, the molten material (corium) could be ejected or relocated through existing vessel penetrations (cooling pipe connections), thus potentially contaminating other locations in the power plant. There exists, however, a potential for plugging of melt flow due to its complete solidification, providing the availability of an adequate heat sink. Therefore, a numerical model was created to simulate the flow of molten metal through an initially empty horizontal pipe. The numerical model was verified using a previously developed analytical model and validated against experimental tests with gallium (low melting temperature) as a substitute for corium. The numerical model was able to predict the penetration length (length of distance traveled by the molten metal) after a complete blockage occurred with an average percent error range of 9%. Since the numerical model has been verified and validated, the model was updated to predict the penetration length in the cooling pipe in case of a severe accident. The model was used to predict the penetration length for different Reynolds numbers and pipe diameters, which resulted in the range of penetration length from about 0.33 m to 0.93 m.

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.015
GPT teacher head0.227
Teacher spread0.212 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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