MétaCan
Menu
Back to cohort
Record W2887019864 · doi:10.11159/htff18.159

Characterization of Boiling Phenomena during Laboratory-Scale Forced Convection Quenching

2018· article· en· W2887019864 on OpenAlexvenueno aff
Roberto Cruces, Bernardo Hernández, Francisco Novas

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsBoilingQuenching (fluorescence)Forced convectionMaterials scienceThermodynamicsScale (ratio)ConvectionCharacterization (materials science)MechanicsPhysicsNanotechnologyOpticsFluorescence

Abstract

fetched live from OpenAlex

An experimental investigation was conducted to correlate heat extraction with boiling phenomena at the liquid-probe interface during forced convective quenching of a steel probe in a laboratory-scale facility.A conical-end probe made of AISI 304 stainless steel instrumented with two type-K thermocouples was rapidly cooled from 850 °C in water at 60°C, flowing with a free-stream velocity of 0.2 m/s.Bubble formation, growth and detachment at the probe surface was recorded with a high-speed video camera.Using the experimental cooling curves measured with the sub-surface thermocouple, the surface heat flux was estimated by solving a onedimensional inverse heat conduction problem (IHCP) without phase change.The inverse boiling curve obtained showed that the maximum peak on heat extraction was reached during the nucleate boiling stage and is associated with the time at which the wetting front passed though the thermocouple axial location.From image analysis, two regions can be distinguished as the wetting front travels through the probe: the wetting front, formed by small bubbles that grew rapidly and coalesced due to the large bubble population; and a region trailing the wetting front, where the size, population and dynamic behavior of the bubbles was quite different.These bubbles grew conserving a spheroidal shape until they reached their maximum size; when they were decreasing, a concave deformation was observed at the interface due to condensation caused by the quench media rewetting the surface and, finally, the bubble departed from the probe surface, collapsing in the bulk flow near the probe surface.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.003
GPT teacher head0.172
Teacher spread0.169 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Mechanical, Chemical, and Material EngineeringSame topicMetallurgical Processes and ThermodynamicsFrench-language works237,207