Accelerating reaction modeling using dynamic flow experiments, part 2: development of a digital twin

Abstract

In this paper, we describe the development of a digital twin for a Michael addition continuous-flow process using data generated from dynamic flow experimentation. We commenced our investigation by creating a virtual flowsheet representation of the “real-life” continuous-flow system. The residence time distribution (RTD) within the system was assessed using an automated step change protocol which examined the performance at different flow rates. The RTD study generated an understanding of the influence of dispersion on the intrinsic reaction kinetics. The dynamic flow experiments were fitted to a parallel reaction network for the reaction of 1,2,4-triazole with acrylonitrile in the presence of base to form the desired product and a regioisomer. The reaction network comprised of four kinetic parameters (A₁, E_a1, A₂ and E_a2). The fitted model closely corresponded to the experimental data, with R² = 0.974. The model was then further validated with additional dynamic flow experiments and a self-optimization study. The established digital twin was then used to explore the influence of disturbances within the system.