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Record W2034816362 · doi:10.1243/09544089jpme172

A piezoelectric force sensor for mill-scale chip refiners

2008· article· en· W2034816362 on OpenAlexaff
Dustin Olender, Peter Wild, Peter Byrnes

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsHerzberg Institute of AstrophysicsUniversity of Victoria
Fundersnot available
KeywordsShear forceBar (unit)MillMaterials sciencePiezoelectricityMechanical engineeringChipProcess (computing)Composite materialComputer scienceEngineeringElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

Refiners are used in the pulp and paper industry to separate wood chips into individual fibres and to develop the morphology of fibres to be suitable for the type and grade of paper to be produced. Within a refiner are discs, at least one of which rotates at high speed and all of which are lined with radial patterns of bars on their opposed surfaces. A mixture of chips and water is accelerated radially through the space between the discs. Compressive and shear forces are applied to chips and fibres as the bars on the opposed discs cross each other. Experiments have shown that certain process variables can greatly affect the forces applied to chips or fibres when bars cross. These findings suggest that the contact mechanics of bar-crossings are a significant factor in the development of fibre properties. To investigate these contact mechanics in operating refiners, a piezoelectric-based sensor has been developed to measure the forces applied to the chips and fibres by the bars. The sensor replaces a small section of a refiner bar and is sensitive to both axial and tangential forces. The current paper describes the evolution of the design of this sensor from a proof-of-concept prototype for a laboratory-scale refiner to the latest generation sensor for a mill-scale refiner. Performance during the most recent mill trials is presented.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.595
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.240
Teacher spread0.229 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations10
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical EngineeringSame topicForce Microscopy Techniques and ApplicationsFrench-language works237,207