Design, Heat Transfer, and Visualization of the Milli-Reactor by CFD and ANN

Abstract

This paper proposes a milli-reactor design method incorporating reactor runaway criteria. Based on Computational Fluid Dynamic (CFD) simulation, neural networks are applied to obtain the optimal reactor structure according to the target reaction requirements. Varma’s theory, the critical Nusselt number for stable operation of the flow reactor, is derived. Inserts of the multi-blade structure are designed and investigated to enhance mixing and heat transfer performance. The flow field and heat transfer capacities are obtained by CFD calculations in the range of Re 50–1800. The internal components increase the heat transfer performance up to 21 times, and the pressure drop up to 16 times. The inclined angle of the blade is recommended to be 45°, which can effectively improve heat transfer without generating excessive pressure drop. By partial least squares regression (PLS) analysis, Re and the number of blades are the most critical factors affecting heat transfer, and the five blades and smaller tilt angles are recommended. The CFD calculation results are in good agreement with the Particle Image Velocimetry (PIV) experimental results.