EFFECTIVE NUMERICAL ANALYSIS METHOD APPLIED TO THE ROLL-TO-ROLL SYSTEM HAVING A WINDING WORKPIECE
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".