Dynamics and control of retention and formation on a paper machine using a microparticulate retention aid system
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Bibliographic record
Abstract
Control strategies for retention and formation processes are developed in order to stabilize the wet end operation and to reduce variations in the machine direction properties of paper without deteriorating formation of paper. The papermaking process using a microparticulate retention aid system is focused. The main factors affecting retention and formation were investigated with a CPAM (cationic polyacrylamide)/bentonite retention aid system and on a Fourdrinier pilot paper machine. The deposition efficiency model and the bridging strength model were developed to express the effects of the dosages of microparticulate retention aids on retention and paper formation, respectively. Effects of the pulp mass flow and the filler addition on first-pass retention and formation are also discussed. Dynamic models of a retention process of a paper machine were developed from first-principles (mass balances). To describe the wet end chemistry effect, first-pass retention was included into the model as a parameter dependent on operating conditions. In addition, it was attempted to simulate dynamics of formation by developing an empirical model of formation and coupled with the dynamic models for the retention process. Transfer functions were derived from the models. It was found that the two major factors affecting the dynamics of the retention process are the first-pass retention of solids and the parameters related to the white water circulation such as the volume of the wire pit and the residence time at the wire pit. Several control strategies were studied through simulation. The study showed that controlling the pulp mass and the filler mass in paper instead of basis weight and paper ash content can reduce the interactions without using decouplers. To reduce the variations in formation, the headbox pulp consistency control and the ratio control of a microparticle flow to a polymer flow are suggested. The problem concerning the set-points of white water consistency during grade changes was solved. Multivariable control of basis weight, ash content, white water consistency and headbox pulp consistency is also discussed.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it