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Record W4220873209 · doi:10.18280/ejee.240106

Comparative Study and Experimental Optimization of Ozone Generators by Cylindrical Surface Dielectric Barrier Discharge (DBD)

2022· article· en· W4220873209 on OpenAlexvenueno aff
Rachida Hedara, Saïd Nemmich

Bibliographic record

VenueEuropean Journal of Electrical Engineering · 2022
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsOzoneDielectric barrier dischargeMaterials scienceElectrodeDielectricVoltageOxygenGenerator (circuit theory)Analytical Chemistry (journal)OptoelectronicsPower (physics)ChemistryElectrical engineeringChromatographyThermodynamicsPhysicsEngineering

Abstract

fetched live from OpenAlex

The dielectric barrier discharge (DBD) is a more efficient medium of ozone production, which requires voltages of the order of several kV and frequencies of a few tens of kHz. The principal objective of this study is to model and optimize a cylindrical-shaped ozone generator with a surface DBD that will be used in a water treatment plant. By playing on the electrical parameters (voltage, oxygen flow) and geometric parameters (the nature and diameter of the dielectric, the length of the electrode), to achieve high ozone efficiency and minimum energy consumption. It is recommended to use cylindrical surface discharge reactors with reduced diameter and electrode length and with the smallest possible oxygen circulation interval to achieve satisfactory ozone concentrations, with reduced power consumption.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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
Published2022
Admission routes1
Has abstractyes

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