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Estimating lags in a kraft mill.

Jerry Ng1, Yuri Lawryshyn1, Nikolai DeMartini2

  • 1Chemical Engineering and Applied Chemistry, University of Toronto Faculty of Applied Science & Engineering, Toronto, Ontario, Canada.

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|August 30, 2024
PubMed
Summary

Autoregressive exogenous (ARX) models quantify time lags in pulp mills, revealing how upstream changes affect downstream measurements. Estimated lags for heating value and boiling point rise align with simulations, indicating imperfect mixing in liquor storage tanks.

Keywords:
black liquorkraft pulpingmachine learningsystem identificationtime series analysis

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Area of Science:

  • Chemical Engineering
  • Process Control
  • Pulp and Paper Industry

Background:

  • Time lags in pulp mills obscure the relationship between upstream operations and downstream measurements.
  • Accurate lag estimation is crucial for optimizing the kraft recovery cycle, particularly in liquor storage tanks.
  • Understanding these lags improves process control and prediction accuracy.

Purpose of the Study:

  • To estimate time lags in a Canadian pulp mill using autoregressive exogenous (ARX) models.
  • To investigate the lagged effects of species change on key liquor properties (heating value, viscosity, boiling point rise).
  • To compare ARX model predictions with autoregressive (AR) and persistence models.

Main Methods:

  • Utilized autoregressive exogenous (ARX) models to simulate and estimate process lags.
  • Applied ARX models to real-world data from a Canadian pulp mill.
  • Compared ARX model performance against autoregressive (AR) and persistence models.

Main Results:

  • ARX models successfully approximated lags in a simulated liquor storage tank system.
  • Estimated lags for heating value (49h) and boiling point rise (41h) after species change align with mill simulations and hydraulic residence times.
  • A lagged effect on viscosity was not identified; ARX and AR models showed slightly better predictions than persistence models.

Conclusions:

  • Liquor storage tanks in pulp mills exhibit imperfect mixing, leading to significant time lags.
  • ARX models provide a reliable method for estimating these process lags.
  • Measurements upstream of units with large residence times offer limited predictive value.