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Record W1916644037 · doi:10.1177/004051750107100105

Real-Time Parameter Identification for a Control-Oriented Model of Continuous Infrared Drying of a Wet Fabric

2001· article· en· W1916644037 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

VenueTextile Research Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicRadiative Heat Transfer Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsProcess (computing)InfraredProcess engineeringComputer scienceLine (geometry)Nonlinear systemIdentification (biology)Biological systemController (irrigation)SimulationMathematicsEngineeringOptics

Abstract

fetched live from OpenAlex

Parameters are determined for a model representing the drying dynamics of a wet fabric continuously passing through an infrared oven using a method involving off-line (batch) data processing, as well as by real-time recursive calculation. Drying trials with the infrared oven under various operational conditions demonstrate the strong nonlinearity of the drying process. Because of this, the model parameters established by off-line (batch) processing do not allow adequate calculation of the observed process responses under other different operating conditions. On the other hand, a method of recursive identification applied to real-time treatment of the readings from the oven provides a model with very satisfactory adaptation to changing operational conditions. The results also show that a simple first-order model represents the dynamic characteristics of the oven just as well as models of higher order, thus providing an important advantage for elaborating an efficient numerical controller for the drying process.

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.049
GPT teacher head0.330
Teacher spread0.280 · 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