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Record W2119992387 · doi:10.1002/cjce.5450830411

Simulation of Radiation Field in Multilamp Photoreactor Using the LSDE Model

2005· article· en· W2119992387 on OpenAlexvenueno aff
Quan Yang, Simo O. Pehkonen, Madhumita B. Ray

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2005
Typearticle
Languageen
FieldChemistry
TopicChemistry and Stereochemistry Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRadiationOpticsRadiant intensityShadow (psychology)Intensity (physics)Light intensityMaterials scienceLight fieldNuclear engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Abstract Determination of a radiation field in a multilamp photoreactor is rather difficult due to the blockage of light by the neighbouring lamps in the reactor. Shadow zones in the photoreactor caused by the lamp blockage vary according to the different lamp arrangements. In addition, the reactor shape also has an effect on the average light intensity, since light is absorbed by the reactor wall if it reaches the wall. In this study, selected aspects of reactor configuration and lamp arrangement were investigated in order to achieve the maximum average light intensity. A line source with a diffused emission (LSDE) model, which shows sufficient accuracy and simplicity, was selected to simulate the light field in the test reactor. Simulation indicates that the square and cylindrical reactors with two and four lamps installed symmetrically exhibited superior performance to elliptical and rectangular reactors. For a multilamp reactor, a triangular pitch of lamp arrangement with 33° is recommended for maximum average light intensity.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.230
Teacher spread0.213 · 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 designSimulation or modeling
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
Published2005
Admission routes1
Has abstractyes

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