Bibliographic record
Abstract
Many paper mills have replaced their paper machine airpad headboxes with high speed hydraulic headboxes to increase production rate and also to improve the operational stability. However high speed hydraulic headboxes can contribute to higher Machine Direction (MD) basis weight variation. The wider bandwidth of the headbox may allow pulsations generated in the approach system to pass through it and to influence the jet velocity. This thesis is devoted to the analysis of one of such case where the replacement has resulted higher MD basis weight variation. There could be several reasons for the MD basis weight variation. The most likely sources are hydrodynamic pressure pulsations generated in the approach system and hydrodynamic disturbances produced within the headbox. A comprehensive study of the approach system has been carried out by recording pressure data from the major pieces of wet end equipment simultaneously. The thesis explains the experiments in detail highlighting the features of the sensors and data acquisition system. To study the possible generation of pulsations within the headbox^ and also to analyze the effectiveness of the headbox in suppressing pulsations from the approach system, a theoretical nonlinear dynamic model representing a typical Sym-Flo headbox has been derived. The headbox is a multivariable system, and so a multivariable Linear Quadratic Gaussian (LQG) controller has been used to control the level and the total head optimally. As there are constraints that should be imposed on the inputs and outputs, LQG has drawbacks, therefore a Model Predictive Controller (MPC) is investigated to accommodate input/output constraints. The resulting controllers are simulated for various situations and results are included in the thesis. The headbox model includes the slice hp opening as one of its manipulated variables and so it is possible to simulate grade change events. From the simulation results it is quite clear that the grade change can be achieved smoothly using a multivariate controller. The decoupling effect and marked reduction in interaction among the variables are achieved through multivariate control and are illustrated through various simulations.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".