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1. Introduction
Stirred tanks are widely used in the chemical, mineral process-ing, wastewater treatment and several other process industries. Among these operations, the mixing of single and multiphase flu-ids is one of the most common unit operations and is fundamental to most aspects of process performance. The most crucial parame-ter used to evaluate the mixing efficiency is mixing time and typ-ically, the t95 mixing time is used. It is defined as the time required from a non-equilibrium condition to achieve within a value of ±5% of the final concentration. Extensive investigations of the fluid mix-ing in stirred tanks have been carried out over the past several dec-ades based on experimental techniques. Nere et al. [1] reviewed such experimental techniques and pointed out their main features and limitations. Some of these disadvantages, such as the difficult applicability in the case of non-transparent stirred tanks, the se-vere experimental conditions, and the fail to obtain very detailed evolution of the scalar concentration, have confined their applica-tion in the process industries and can only be used in the labora-tory scale experimental measurements.

1引言

搅拌槽广泛应用于化工，矿产加工，污水处理和其他过程工业。在这些操作中，混合的单相和多相流的入侵检测系统是一种最常见的单元操作和过程性能方面是最基本的。最关键的参数用来评估混合效率的混合时间，典型地，T95混合时间的使用。它被定义为从一个非平衡条件在价值的最终浓度达到5%±所需要的时间。搅拌槽中流体混合的广泛的调查已经进行了在过去的几个数量级基于实验技术。神经等。[ 1 ]回顾等实验技术，指出了它们的主要特点和局限性。其中的一些缺点，如非透明的搅拌槽的情况下适用的困难，严重的实验条件，并不能得到的标量浓度非常详细的演化，都限制了他们的应用在工业生产过程中，只能用在实验室规模的实验测量。

In recent years, owing to the great progress in the computer technique, the computational fluid dynamics (CFD) technique is being increasingly used as a substitute for experiments to carry out detailed studies of the mixing process. The accurate prediction of the liquid flow field, including its turbulent characteristics, plays an important role in the numerical predictions of the mixing time [2].

近年来，由于在计算机技术的巨大进步，计算流体动力学（CFD）技术被越来越多地用于实验进行的混合过程的详细研究的替代品。的液流场的准确预测，包括其湍流特性，在混合时间[ 2 ]数值预测中起着重要的作用。

Previous studies have demonstrated that numerical simula-tions based on the Reynolds-averaged Navier–Stokes (RANS) approach can provide satisfactory results of the mean flow in stirred tanks [3–7] . However, it is difficult to obtain accurate pre-dictions of the turbulent quantities and fails to capture the instan-taneous nature of the turbulent structures because of the assumption of isotropy and ‘time-averaged’ modification of the Navier–Stokes equations[4,6–8]. This will certainly affect the pre-dictions of the mixing time in stirred tanks. As a matter of fact, it has been identified that, in the turbulent flow regions, even when the fully predictive simulation strategies, such as the sliding mesh (SM) and multiple Reference frame (MRF) method, were employed, the prediction of mixing time based on RANS approach is not accu-rate when compared with the result determined from experiments or empirical correlations reported in the literature. For example, Osman and Varley[9] studied the mixing time in an unbaffled stir-red tank agitated with a Rushton turbine using the MRF method.

The predicted mixing time was found to be two times higher than the experimental value. Jaworski et al. [10] studied the homogeni-zation in a baffled stirred tank agit本论文由英语论文网提供整理，提供论文代写，英语论文代写，代写论文，代写英语论文，代写留学生论文，代写英文论文，留学生论文代写相关核心关键词搜索。