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Record W2007923138 · doi:10.1021/ie800254s

Enhancing a Smelter Off-Gas System Using a Plant-Wide Control Design

2009· article· en· W2007923138 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Optimization
Canadian institutionsLaurentian University
Fundersnot available
KeywordsComponent (thermodynamics)Process (computing)Control (management)Hazardous wasteControl systemProcess engineeringProcess controlComputer scienceControl engineeringEngineeringWaste management

Abstract

fetched live from OpenAlex

An off-gas treatment system is a vital component of smelter roaster processes as it ensures operation is in accordance with environmental regulations in terms of hazardous emissions. It is, therefore, paramount that a well-designed control structure be incorporated into the system. Analysis of the off-gas treatment processes for a roaster using a systematic control design procedure to provide the necessary verification to current industrial practices for controlling these processes was carried out. We approached this by conducting a top-down (steady-state) analysis based on an available nonlinear model of the process. The results provide insight into, and potential improvement of, the control of the off-gas system. Through designing the bottom-up structure, a feedback control structure was developed to give robust and effective control in terms of disturbance rejection capabilities. The proposed control structure provides for improved performance in an easy form to implement.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.061
GPT teacher head0.284
Teacher spread0.223 · 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