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Record W4283588069 · doi:10.11159/ffhmt22.128

Characterization of Wick Evaporators through the Behavior of the Specially Designed Condenser

2022· article· en· W4283588069 on OpenAlexvenueno aff
Ella Barakhovskaia, Andrey Glushchuk, I. V. Marchuk, Patrick Queeckers, Carlo Saverio Iorio

Bibliographic record

VenueProceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer · 2022
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsnot available
FundersSiberian Branch, Russian Academy of SciencesEuropean Space Agency
KeywordsCondenser (optics)Characterization (materials science)Materials scienceEvaporatorComputer scienceProcess engineeringMechanical engineeringEngineeringNanotechnologyPhysicsHeat exchangerOptics

Abstract

fetched live from OpenAlex

New concept of the experimental investigation has been proposed and successfully realized during the 73rd ESA parabolic flight campaign 2020. The evaporators' behavior is analyzed by evaluating the liquid level inside and by investigating the external condensation on the designed condenser's surface. Three evaporators made with different techniques have been tested. Analysis of the experimental data shows qualitative differences in considered evaporators. Aluminium foam provided uniform distribution of liquid close to its external surface. The evaporator with 3D-printed wick had a non-uniform distribution of liquid inside. Sintered brass wick showed the longest stabilization time.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.361

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 head0.024
GPT teacher head0.227
Teacher spread0.202 · 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 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
Published2022
Admission routes1
Has abstractyes

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