A combined approach towards the understanding of mass transfer in two-phase flow: The integration of numerical modelling with MRI

理解两相流中传质的综合方法：数值模型与 MRI 的集成

• 批准号: EP/C547241/1
• 负责人: Markus Kraft
• 金额: $ 39.21万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2006
• 资助国家: 英国
• 起止时间: 2006 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FC547241%2F1
• 关键词: combined; approach; towards; understanding; mass

Many industrial processes require effective contact between two different liquids, or between a liquid and a gas. These processes include treatment of waste water and fermentation of alcoholic drinks. When these systems are stirred, the result is not a uniform mixture, but a very large number of small bubbles or droplets dispersed through the liquid. The droplets involved are not all the same, and have different sizes, velocities and chemical compositions. This makes it very difficult to accurately measure the important properties of the system. It is also very difficult to predict mathematically how such a system will behave.The proposed investigation has two main aims. The first is to make accurate experimental measurements of droplets within a liquid. The second is to use these measurements to develop mathematical models that can describe the system.Experimental Techniques:Droplets dispersed in a liquid undergo many different processes. Currents within the fluid can cause the droplets to follow convoluted paths. In the course of this flow through the liquid, they can join together to form large droplets, break up to form smaller ones, and their chemical composition can change through diffusion. Experimental measurement of all these processes is not an easy task: even simply visually tracing the path of a single droplet can be impossible if the liquids involved are not transparent.Magnetic Resonance Imaging (MRI) is a technique that involves tagging individual molecules by altering how they behave in a magnetic field. These molecules can then be accurately located in time and space, allowing us to determine the size, velocity and composition of moving droplets. MRI has never before been applied to a system such as this.Mathematical Modelling:The behaviour of large numbers of interacting droplets is described mathematically by using Population Balance Equations (PBEs). These equations can require vast computational power to solve, especially in complicated systems where the behaviour is dependent on many variables: size, shape, concentration profiles etc. Monte Carlo methods are a particular mathematical technique that allow us to solve these equations quickly and efficiently and predict (given the right model parameters) how the droplet-liquid system will behave.Combing Experiments and Models:The crucial aim of our research is to combine our experimental measurements and mathematical analysis. This will enable us to decide which factors have an important, noticeable effect on the system, and which can be ignored. Thus, prediction of the behaviour of complicated systems will be simplified and industrial processes will become more effective and efficient

许多工业过程需要两种不同液体之间或液体与气体之间的有效接触。这些过程包括废水处理和酒精饮料发酵。当这些系统被搅拌时，结果不是均匀的混合物，而是大量的小气泡或液滴分散在液体中。所涉及的液滴并不都是相同的，并且具有不同的尺寸、速度和化学成分。这使得精确测量系统的重要特性变得非常困难。用数学方法预测这样一个系统的行为也是非常困难的。首先是对液体中的液滴进行精确的实验测量。第二种方法是利用这些测量数据建立数学模型，来描述系统。实验技术：分散在液体中的液滴会经历许多不同的过程。流体内的电流可以使液滴沿着盘旋的路径行进。在这种通过液体的流动过程中，它们可以结合在一起形成大的液滴，分裂形成较小的液滴，并且它们的化学成分可以通过扩散而改变。对所有这些过程进行实验测量并不是一件容易的事：如果所涉及的液体不是透明的，即使是简单地在视觉上追踪单个液滴的路径也是不可能的。磁共振成像（MRI）是一种通过改变单个分子在磁场中的行为来标记它们的技术。然后，这些分子可以在时间和空间中精确定位，使我们能够确定移动液滴的大小，速度和成分。MRI以前从未被应用于这样的系统。数学建模：大量相互作用的液滴的行为通过使用群体平衡方程（PBE）进行数学描述。这些方程可能需要大量的计算能力来求解，特别是在行为取决于许多变量的复杂系统中：尺寸，形状，浓度分布等。蒙特卡罗方法是一种特殊的数学技术，使我们能够快速有效地求解这些方程，并预测（给定正确的模型参数）液滴-液体系统将如何表现。我们研究的主要目的是将实验测量和数学分析联合收割机结合起来。这将使我们能够决定哪些因素对系统有重要的、明显的影响，哪些可以忽略。因此，预测复杂系统的行为将被简化，工业过程将变得更加有效和高效

项目成果

Coupling a stochastic soot population balance to gas-phase chemistry using operator splitting

• DOI: 10.1016/j.combustflame.2006.10.007
• 发表时间: 2007-02
• 期刊: Combustion and Flame
• 影响因子: 4.4
• 作者: M. Celnik;R. Patterson;M. Kraft;W. Wagner

A study on the coagulation of polycyclic aromatic hydrocarbon clusters to determine their collision efficiency

多环芳烃簇的凝聚研究及其碰撞效率

• DOI: 10.1016/j.combustflame.2009.10.003
• 发表时间: 2010
• 期刊: Combustion and Flame
• 影响因子: 4.4
• 作者: Raj A

Stochastic weighted particle methods for population balance equations

• DOI: 10.1016/j.jcp.2011.06.011
• 发表时间: 2011-08
• 期刊: J. Comput. Phys.
• 作者: R. Patterson;W. Wagner;M. Kraft

A mechanistic study on the simultaneous elimination of soot and nitric oxide from engine exhaust

• DOI: 10.1016/j.carbon.2010.12.005
• 发表时间: 2011-04
• 期刊: Carbon
• 影响因子: 10.9
• 作者: A. Raj;Z. Zainuddin;Markus Sander;M. Kraft

The simultaneous reduction of nitric oxide and soot in emissions from diesel engines

• DOI: 10.1016/j.carbon.2008.11.043
• 发表时间: 2009-03
• 期刊: Carbon
• 影响因子: 10.9
• 作者: Markus Sander;A. Raj;Oliver Richard Inderwildi;M. Kraft;S. Kureti;H. Bockhorn