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Record W2340321910

Improving the broke recirculation strategy in a newsprint mill

2004· article· en· W2340321910 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

VenuePolyPublie (École Polytechnique de Montréal) · 2004
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsNewsprintPaper machinePapermakingDowntimeMillEngineeringUpsetProcess engineeringPulp and paper industryMechanical engineeringReliability engineeringKraft paper
DOInot available

Abstract

fetched live from OpenAlex

HEET BREAKS are a major disturbance in the newsprint process and cause costly paper machine downtime. Fluctuations in the pulp furnish can upset the stability of a paper machine and are one of the causes of breaks. These fluctuations can be the result of the broke recirculation strategy applied at the mill. Specifically, sudden changes to the broke ratio can induce considerable variations in the properties of the mixed pulp at the paper machine headbox [7]. Broke recirculation strategies can be quantified and explored by the application of simulation-based optimization. This technique is increasingly being used in other applications, and has been shown to yield significant economic benefits at low investment cost and little disturbance to the actual process [3,6]. This study focuses on developing a dynamic simulation of the papermaking section of an integrated newsprint mill, and using an objective function to quantify fluctuations at the headbox. Direct search optimization was then applied to identify opportunities for improving the broke recirculation strategy at the mill. The overall goal was to reduce headbox variability caused by adjustments in the broke ratio.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.987

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 head0.011
GPT teacher head0.200
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