Comparison of micromixing models for CFD simulation of nanoparticle formation

Abstract

Reactive precipitation is an important research topic in chemical engineering because of its numerous industrial applications in the formation of nanoparticles. Recently, computational fluid dynamics (CFD) has been successfully coupled with micromixing models and probability density function (PDF) methods to predict the effect of mixing on the particle size distribution. The micromixing model is generally based on the presumed PDF method. The objective of this work is to compare multienvironment-presumed PDFs and a recently proposed direct-quadrature-method-of-moments-interaction-by-exchangewith-the-mean (DQMOM-IEM) micromixing model with transported PDF predictions for the simulation of reactive precipitation, including simultaneous mixing-limited reaction, nucleation, and growth in a plug-flow reactor. DQMOM is applied to

Mixing in a multi-inlet vortex mixer (MIVM) for flash nano-precipitation

“…With increasing Re, the zone of highest kinetic energy moves into the center of the chamber. This observation is in contrast to our previous results for the CIJ mixer in which the kinetic energy dissipation is maximum in the center of the mixing cavity 24 . As a result considerable mixing occurs in the exit region of the MIVM.…”

“…The micromixing parameter γ is modeled by More detailed derivation can be found from Fox's articles as well as others [24][25][26] .…”

“…A CFD model that was previously used to model the CIJ 4 mixer was used to model the MIVM mixer. 24 The CFD results provide additional insights as to the mixing mechanisms in the MIVM mixer.…”

A multienvironment conditional probability density function model for turbulent reacting flows

“…(i) DQMOM can be used with multiple reacting scalars. 16 Thus, the MECPDF model can be extended to multiple reaction-progress variables conditioned on mixture fraction:…”

“…Quadrature-based moment methods are a powerful technique [13][14][15][16] for approximating with controllable accuracy the moments of a distribution function (e.g., transported PDF or number density functions) starting from its transport equation. In recent work on isothermal reacting flows, 16 DQMOM has been shown to yield results for the lower-order scalar moments that are in excellent agreement with transported PDF methods at a fraction of the computational cost. In the present work, we extend DQMOM to treat the conditional PDF of a reaction-progress variable in order to describe nonisothermal reacting flows.…”