Pulp and paper production processes are complex and cover most of the unit opera­tions known in chemical engineering. Due to the large amount of water and the low efficiency of most of the separation steps, many recycling streams are required in the process. This is true for water, fibres and fillers, air, and energy. Due to this, the effort to produce a simple steady-state balance can be very high. Over the past two decades, heat balances have been handled with varying success, as have contami­nant balances such as, for example, chemical oxygen demand (COD) or macro-stick – ies. More difficult problems—for example, the simulation of the effects of various contaminants, such as the deposition of pitch and stickies—have not yet been han­dled successfully within the industry. Simulation of pulping processes has further advanced and can contribute some experience in handling multicomponent balances including complex chemical reactions. Still, an improved steady-state modelling is the key to a better design of pulping and paper production processes.

The paper production process is highly dynamic and although many academic papers have been published in relation to dynamic simulation and paper machines, only a few approaches to the dynamics of the paper machine at an industrial scale have been published. Some studies focus on the dynamics of white water (Orccotoma et al., 1997) and on the dynamics of the wet end at the paper machine (Hauge, Slora, and Lie, 2005). Wet end can be considered as one of the most complex combinations of hydrodynamics and colloidal chemistry. No simulation model has yet been able to fully describe the processes taking place in the wet end. Process simulation is an optimisation tool and only if the dynamics is understood can the dynamic optimisa­tion of the paper production process be addressed (Laperriere and Wasik, 2002).

The activities within this scientific area cover all topics concerning the model­ling and simulation of the entire paper production process. This includes the modi­fications of fibre properties in the stock preparation, the modelling of the complex wet end chemistry, and the modelling of water loops, including chemical reactions and energy balances. Special attention is given to use of dynamic process simulation, real-time simulation tools, and model validation tools.

Updated: October 10, 2015 — 9:01 pm