MétaCan
Menu
Back to cohort
Record W2802348279 · doi:10.1139/tcsme-2015-0048

EFFECTIVE NUMERICAL ANALYSIS METHOD APPLIED TO THE ROLL-TO-ROLL SYSTEM HAVING A WINDING WORKPIECE

2015· article· en· W2802348279 on OpenAlexvenueno aff
Sungham Hong, Juhwan Choi, Sungsoo Rhim, Jin Hwan Choi

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsnot available
Fundersnot available
KeywordsNumerical analysisLine (geometry)AlgorithmPath (computing)Arc (geometry)EngineeringControl theory (sociology)Computer scienceMechanical engineeringMathematicsControl (management)Artificial intelligenceGeometryMathematical analysis

Abstract

fetched live from OpenAlex

The design and development of Roll-to-Roll (R2R) system has been mainly executed by the expert’s experience. There are some important issues in the numerical analysis method about a roller path and the control of the R2R system. This study proposes the efficient R2R system analysis methods. The first one is an Approximated Winding Length Estimation (AWLE) algorithm which can calculate the analytic winded length of a workpiece. The winder can be approximated with line and arc segments at this algorithm. As a result, in the numerical model of the R2R system, we can replace the winder characteristics with the AWLE algorithm. The second one is the contact algorithm between workpiece and rollers. This contact algorithm must be stable and fast for precise analysis. The third one is the flexible workpiece model. The workpiece can be modeled by finite elements. By describing the implementation of these important methods, this paper proposes an efficient R2R system analysis method.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicMechanical stress and fatigue analysisFrench-language works237,207