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Record W1965106675 · doi:10.1002/pen.21794

Identification of transient responses of a plasticating twin screw extruder due to excitation in feed rate

2010· article· en· W1965106675 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

VenuePolymer Engineering and Science · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceTransient (computer programming)Plastics extrusionExcitationIdentification (biology)Composite materialElectrical engineeringComputer scienceEngineeringBiology

Abstract

fetched live from OpenAlex

Abstract A corotating plasticating twin screw extruder (TSE) was excited by changing feed rate according to predesigned random binary sequence (RBS) and stair type excitation. A high density polyethylene was used as processing material in this study. Empirical models were developed relating two output variables, melt pressure at die ( P m ), and melt temperature at die ( T m ), with feed rate ( F ). Classical linear system identification technique was used to develop models. Models were developed using a data set obtained from RBS excitation. Stair type excitation data were used to validate the developed models. The structure of the obtained models was autoregressive moving average with exogenous input (ARMAX). Models with ARMAX structure and order of 2 were found to be sufficient to capture the dynamic behaviors of P m and T m when F was changed. A delay‐gain model was proposed for P m and was found to capture the response quite satisfactorily. POLYM. ENG. SCI., 2011. © 2010 Society of Plastics Engineers

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)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.034
GPT teacher head0.304
Teacher spread0.270 · 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