Reactor modeling and recipe optimization of polyether polyol processes: Polypropylene glycol

Abstract

The reactor modeling and recipe optimization of conventional semibatch polyether polyol processes, in particular for the polymerization of propylene oxide to make polypropylene glycol, is addressed. A rigorous mathematical reactor model is first developed to describe the dynamic behavior of the polymerization process based on first‐principles including the mass and population balances, reaction kinetics, and vapor‐liquid equilibria. Next, the obtained differential algebraic model is reformulated by applying a nullspace projection method that results in an equivalent dynamic system with better computational performance. The reactor model is validated against plant data by adjusting model parameters. A dynamic optimization problem is then formulated to optimize the process recipe, where the batch processing time is minimized, given a target product molecular weight as well as other requirements on product quality and process safety. The dynamic optimization problem is translated into a nonlinear program using the simultaneous collocation strategy and further solved with the interior point method to obtain the optimal control profiles. The case study result shows a good match between the model prediction and real plant data, and the optimization approach is able to significantly reduce the batch time by 47%, which indicates great potential for industrial applications. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2515–2529, 2013

Output feedback stochastic nonlinear model predictive control of a polymerization batch process

“…1. A complex model for this process has been proposed in [40], which was employed in [41] for NMPC and in [42] Fig. 1.…”

“…The missing parameter values including the vaporliquid equilibrium equations and temperature correlations can be found in [40]. The aim of the control algorithm is to minimize the required remaining batch time (t f [s]) to achieve a specified number average molecular weight (NAMW[g/mol]) of the final product of 350g/mol and ensuring that the amount of monomer (PO) at the end of the batch does not exceed 1000ppm.…”

Integrated Dynamic Optimization and Scheduling of Polymerization Processes with First Principle Models

“…In the population balance equations for the polymer chains were reformulated to eliminate stiffness due to the fast exchange reactions. To overcome this, a nullspace projection method was applied to isolate the fast equilibrium reactions from differential balance equations and to model their quasi‐steady states with algebraic equations. As a result of the reformulation procedure, two pseudo‐species X and Y are introduced: …”

“…In [30] the population balance equations for the polymer chains were reformulated to eliminate stiffness due to the fast exchange reactions. To overcome this, a nullspace projection method [32] was applied to isolate the fast equilibrium reactions from differential balance equations and to model their quasi-steady states with algebraic equations. As a result of the reformulation procedure, two pseudo-species X and Y are introduced:…”

Use of Online Spectroscopy to Control Polymerization in Industrial Processes

“…In a semibatch reactor, the contents of the reactor change throughout the batch, so the on-line NIR can monitor the changes and help determine the completion of the batch. For semibatch reactors, Dow [25] will utilize offline modeling of the process built on kinetics and thermodynamic properties developed on the lab scale. These offline models are used to set the recipe for safe and efficient operations.…”