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Record W3006104414 · doi:10.1002/cjce.23726

Study on the uniformity of water film in a transpiring wall reactor for supercritical water oxidation

2020· article· en· W3006104414 on OpenAlexvenueno aff
Fengming Zhang, Jianan Ma, Chuangjian Su

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicSubcritical and Supercritical Water Processes
Canadian institutionsnot available
FundersYouth Innovation Promotion Association of the Chinese Academy of SciencesNational Natural Science Foundation of China
KeywordsNozzleOverheating (electricity)PorosityMaterials scienceSupercritical fluidTube (container)Composite materialMechanicsChemistryThermodynamics

Abstract

fetched live from OpenAlex

Abstract A three‐dimensional computational fluid dynamic model of a transpiring wall reactor for supercritical water oxidation has been built to optimize the uniformity of water film. Results show that the temperature and species distributions at the nozzle outlet deviate from the reactor centre. The inner wall of the porous tube near the transpiring water injection tube displays low temperatures, while high temperatures are recorded far from the injection tube. The circumferential temperature distribution on the inner wall of the porous tube is uneven. This phenomenon is due to the uneven injection of the transpiring water, leading to the uneven protection of the water film and local overheating of the porous wall. The injection velocity of the transpiring water significantly decreases when the number of injection tubes is increased, and the circumferential velocity and temperature distributions on the porous wall gradually become even. Moreover, high pressure drops across the porous wall at low porosities are useful for the uniform injection of the transpiring water. This characteristic is also conducive to obtaining a more uniform water film protection.

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 score0.008
Threshold uncertainty score0.277

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 head0.203
Teacher spread0.179 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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