Continuous reactor network design for multi-product rigid polyols under uncertainty

Differential-algebraic optimization models for rigid polyol production from our previous work are able to generate optimal reactor configurations along with the optimal operation recipe. However, their performance could degenerate when uncertainty comes into play. In this study, we apply a multi-scenario (MS) strategy to analyze the impact of kinetic uncertainty on reactor network design. Our approach first identifies scenarios that are worst-case violations of inequality constraints. Then, we solve the MS problem with current number of scenarios and obtain the optimal common (or first-stage) decision profiles (q). Next, we apply an iterative scenario sampling and updating strategy, where the uncertainty range is sampled for fixed q to discover constraint violations that determine the need for additional scenarios. This process continues until no further violations are detected. We adopt the MS method to three continuous reactor networks that were optimized in our previous work: CSTR in series, single differential sidestream reactor (DSR) and CSTR followed by a DSR. Among these, the DSR reactor is found to be the most economical and robust with respect to uncertainties.