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Record W2045381443 · doi:10.5539/mas.v8n1p59

Volumetric Mass Transfer Coefficient of SO2 Gas Absorption into Aqueous Sodium Sulphite Solution in Plate Column

2013· article· en· W2045381443 on OpenAlexvenueno aff
J.G. Majeed

Bibliographic record

VenueModern Applied Science · 2013
Typearticle
Languageen
FieldEngineering
TopicIndustrial Gas Emission Control
Canadian institutionsnot available
Fundersnot available
KeywordsAqueous solutionDimensionless quantityMass transfer coefficientMass transferChemistryVolumetric flow rateInletAbsorption (acoustics)Analytical Chemistry (journal)ChromatographyThermodynamicsMaterials sciencePhysics

Abstract

fetched live from OpenAlex

The volumetric mass transfer coefficient (KG.a) for SO2 removal from gas mixture into aqueous Na2SO3 solution was studied in a plate column at constant temperature ( 25 , and liquid holdup. The KG.a values were evaluated over ranges of operating independent variables: gas flow rate (QG), SO2 concentration in inlet gas (CSO2, in), and concentration of aqueous Na2SO3 solution (CNa2SO3). The experimental results showed that KG.a decreased with increasing of CSO2, in, increased with increase of QG, and CNa2SO3. The influence of gas flow rate on KG.a is more than the influence of SO2 concentration in inlet gas, and concentration of aqueous Na2SO3 solution respectively. Computer program Statgrhaphics/Experimental design was used to find the linear fitted models of the KG.a in terms of the dimensional and dimensionless of independent operating variables. The QG, CSO2, in, and CNa2SO3 have significant effects on KG.a, while the interactions of them have no significant effects on it, and could be neglected. The R-squared statistic indicates that the model as fitted explains 90.4949% of the variability in KG.a.

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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.199
Teacher spread0.189 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

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