Abstract

This paper presents a mathematical model able to quantify mixing efficiency in supercritical water hydrothermal reactors (SWHR) for the production of different types of nanoparticles. In fact, mixing plays a crucial role in determining the final particle size distribution and therefore the final product quality. In this work, mixing of supercritical water streams is studied with Computational Fluid Dynamics (CFD) by using the Reynolds Averaged Navier Stokes (RANS) approach coupled with an equation of state and a micromixing model, to take into account the effect of molecular mixing. The performance of the model is investigated in three different scenarios, corresponding to very different values of the Richardson number and very different mixer configurations. The main results show how mixing can be quantified by means of a global mixing time and how turbulence enhances the process, leading to better final product characteristics, especially in terms of lower mean particle size and narrower particle size distributions. This confirms previous research on this topic, highlighting the fact that both the mean particle size and the particle size distribution are strongly dependent on the mixing features of the SWHR

中文翻译：

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湍流超临界水热反应堆混合效率的量化

摘要

本文提出了一种数学模型，该模型能够量化超临界水热液反应器（SWHR）中用于生产不同类型纳米颗粒的混合效率。实际上，混合在确定最终粒度分布以及最终产品质量方面起着至关重要的作用。在这项工作中，通过使用雷诺平均Navier Stokes（RANS）方法，状态方程和微混合模型，并考虑了分子混合的影响，利用计算流体力学（CFD）研究了超临界水流的混合。在三种不同的情况下研究了模型的性能，分别对应于理查森数的非常不同的值和非常不同的混频器配置。主要结果表明，如何通过整体混合时间来量化混合，以及湍流如何增强过程，从而导致更好的最终产品特性，尤其是在较低的平均粒度和较窄的粒度分布方面。这证实了以前对此主题的研究，突出了一个事实，即平均粒径和粒径分布都强烈依赖于SWHR的混合特征