Optimization of a Cyclone Using Multiphase Flow Computational Fluid Dynamics

Abstract

Abstract The US Department of Energy (DOE) National Energy Technology Laboratory’s (NETL) 50 kWth chemical looping reactor has an underperforming cyclone, designed using empirical correlations. To improve the performance of this cyclone, the vortex tube radius and length, barrel radius, and the inlet width and height are optimized using computational fluid dynamics (CFD). For this work, NETL’s open source Multiphase Flow with Interphase eXchange (MFiX) CFD code has been used to model a series of cyclones with varying geometric differences. To perform the optimization process, the surrogate modeling and analysis toolset inside Nodeworks was used. The basic methodology for the process is to use a design of experiments method (optimal Latin Hypercube) to generate samples that fill the design space. CFD models are then created, executed, and post-processed. A response surface (Gaussian process model) is created to characterize the relationship between input parameters and the Quantities of interest (QoI). Finally, the CFD-surrogate is used by an optimization method (differential evolution) to find the optimal design condition. The resulting optimal cyclone has a larger diameter and longer vortex tube, a larger diameter barrel, and a taller and narrower solids inlet. The improved design has a predicted pressure drop 11-times lower than the original design while reducing the mass loss by a factor of 2.3.