Multiscale modeling and control of Kappa number and porosity in a batch‐type pulp digester

This work proposes a multiscale modeling and model‐based feedback control framework for the delignification process in a batch‐type pulp digester. Specifically, we focus on a hardwood chip in the digester and develop a multiscale model capturing both the evolution of microscopic properties such as the pore size and shape distributions in the solid phase and the dynamic changes in the temperature and component concentrations in the liquor phase. While the macroscopic model adopts the continuum hypothesis based on the Purdue model, a novel microscopic model is developed using a kinetic Monte Carlo algorithm, accounting for the dissolution of lignin, cellulose, and hemicellulose contacting the liquor phase. A reduced‐order model was built to design a Luenberger observer for state estimation, which is then used to develop a model‐based control system. The simulation results demonstrated that the proposed methodology was able to regulate both the Kappa number and porosity to desired values.