Thermal stability criterion of complex reactions for batch processes

Abstract

Thermal stability of batch processes is a major factor for the safe and efficient production of polymers and pharmaceutical chemicals. The prediction of the thermal stability for such processes was shown in Kähm and Vassiliadis (2018d) to be unreliable with most stability criteria found in literature also presenting a novel criterion, K, which was shown to give reliable stability predictions for single reactions of higher order. This work provides a detailed derivation for the generalization of thermal stability criterion K applied to reaction networks of arbitrary complexity, consisting of parallel and competing reactions of both exothermic and endothermic nature. The generalized thermal stability criterion K is then applied to Model Predictive Control (MPC) frameworks to intensify batch processes in a safe manner, reducing the time required to reach the target conversion. Several illustrative computational case studies are presented, highlighting the proposed methodology and verifying its validity.

Robust thermal stability for batch process intensification with model predictive control

“…Compared to the deterministic results for the intensification of nitration of toluene with initial temperature of 450 K shown in Kähm and Vassiliadis (2019), the average processing time to reach the target concentration is 0.4 h larger if using a single scenario with MPC with thermal stability criterion K. In Kähm and Vassiliadis (2018b) it is further shown that constant temperature MPC results in processing times of approximately 13 h. Hence, even with 10 scenarios and criterion K, a 2-fold reduction in processing time can be achieved. Therefore, the conservative nature of scenario-based MPC does not hinder the ability to intensify processes.…”

“…If the value of K becomes positive, an unstable process is identified. More detail on the derivation of criterion K and the correction function E can be found in Kähm and Vassiliadis (2019).…”