Discovery of mixing characteristics for enhancing coiled reactor performance through a Bayesian Optimisation-CFD approach

TL;DR

This paper presents a data-driven method combining Bayesian optimization and CFD to identify flow parameters that enhance plug flow performance in coiled tube reactors, improving efficiency and product quality.

Contribution

It introduces an integrated Bayesian optimization-CFD approach to discover flow features that optimize reactor performance, a novel application in flow chemistry.

Findings

Optimal oscillatory flow conditions limit axial dispersion.

Flow reversal and Dean vortices improve plug flow quality.

The method is adaptable to other reactor types.

Abstract

Processes involving the manufacture of fine/bulk chemicals, pharmaceuticals, biofuels, and waste treatment require plug flow characteristics to minimise their energy consumption and costs, and maximise product quality. One such versatile flow chemistry platform is the coiled tube reactor subjected to oscillatory motion, producing excellent plug flow qualities equivalent to well-mixed tanks-in-series 'N'. In this study, we discover the critical features of these flows that result in high plug flow performance using a data-driven approach. This is done by integrating Bayesian optimisation, a surrogate model approach, with Computational fluid dynamics that we treat as a black-box function to explore the parameter space of the operating conditions, oscillation amplitude and frequency, and net flow rate. Here, we correlate the flow characteristics as a function of the dimensionless Strouhal, oscillatory Dean, and Reynolds numbers to the reactor plug flow performance value 'N'. Under conditions of optimal performance (specific examples are provided herein), the oscillatory flow is just sufficient to limit axial dispersion through flow reversal and redirection, and to promote Dean vortices. This automated, open-source, integrated method can be easily adapted to identify the flow characteristics that produce an optimised performance for other chemical reactors and processes.