Selectivity in Froth Flotation

泡沫浮选的选择性

• 批准号: 2035231
• 负责人: Gretar Tryggvason
• 金额: $ 40.58万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2035231&HistoricalAwards=false
• 关键词: Selectivity; Froth; Flotation

Separating different materials is important in mineral processing, recycling and many other processing applications. Froth flotation is a separation process in which heterogeneous material is ground up into small grains, so that each grain consists mostly of one constituent. The grains are then suspended in a liquid bath, and gas bubbles rising through the slurry selectively carry (or float) the particles consisting of the desired material to the top. Various chemicals are added to guarantee that only the desired particles stick to the rising bubbles. While some of the individual steps of this process are well understood, their complex interactions make it very difficult to predict the selectivity and effectiveness of the separation. This project will use numerical simulations based on mathematical models of the various process steps to reproduce the dynamics of froth floatation. The modeling allows each step of the process to be modified separately or turned on and off, assessing exactly how the various processes interact and collectively to set the selectivity for different operating conditions. This project is made possible by major advances in direct numerical simulations of multiphase flows over the last two decades, but up to now such simulations have focused on systems with relatively simple physics. The project will develop advanced multiscale strategies to correctly account for several simultaneous physical processes and to quantify the influence of the various control variables. The primary intellectual merit of this project is the development of computational strategies to model complex multiphase, multiphysics and multiscale processes and their use to determine how selectivity in froth flotation depends on the specific configuration and operating conditions. The development is built on a hybrid finite-volume/front-tracking numerical approach, where the governing equations are solved on a fixed structured grid, but the interface between the different fluids and phases is tracked using connected marker particles that form an unstructured moving grid. In addition to accurately track moving fluid interfaces and phase boundaries, the moving interface grid allows wettability to be included in a relatively straightforward way and greatly facilitates the inclusion of multiscale models for small scale interfacial processes, such as mass transfer and draining of thin films. The broader impact of the project include developments of modeling strategies applicable to a wide range of coupled multiscale processes and the education of people in the development and applications of numerical models for complex processes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

分离不同的材料在选矿、回收和许多其他加工应用中非常重要。泡沫浮选是一种分离过程，在这个过程中，非均质物质被研磨成小颗粒，因此每个颗粒主要由一种成分组成。然后，颗粒悬浮在液浴中，气泡在浆液中上升，选择性地将由所需材料组成的颗粒携带(或漂浮)到顶部。添加了各种化学物质，以确保只有所需的颗粒才能附着在上升的气泡上。虽然这一过程的一些单独步骤已经很好地理解了，但它们复杂的相互作用使得很难预测分离的选择性和有效性。该项目将使用基于各种工艺步骤的数学模型的数值模拟来再现泡沫漂浮的动力学。建模允许单独修改过程的每个步骤或打开和关闭，准确地评估各种过程如何相互作用，并共同设置不同操作条件的选择性。在过去的二十年里，多相流的直接数值模拟取得了重大进展，使得这个项目成为可能，但到目前为止，这种模拟主要集中在物理相对简单的系统上。该项目将制定先进的多尺度战略，以正确解释几个同时发生的物理过程，并量化各种控制变量的影响。该项目的主要智力优势是开发了对复杂的多相、多物理和多尺度过程进行建模的计算策略，并使用这些策略来确定泡沫浮选中的选择性如何取决于特定的配置和操作条件。这一发展建立在有限体积/前沿跟踪混合数值方法的基础上，其中控制方程在固定的结构化网格上求解，但不同流体和相间的界面使用连接的标记粒子来跟踪，这些标记粒子形成了非结构化移动网格。除了精确跟踪移动的流体界面和相界外，移动界面网格还允许以相对简单的方式包含润湿性，并极大地促进了小尺度界面过程的多尺度模型的包含，例如薄膜的传质和排出。该项目更广泛的影响包括开发适用于广泛的耦合多尺度过程的建模策略，以及在开发和应用复杂过程的数值模型方面对人们进行教育。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Numerical Studies of Disperse Three-Phase Fluid Flows

• DOI: 10.3390/fluids6090317
• 发表时间: 2021-09
• 期刊: Fluids
• 影响因子: 1.9
• 作者: L. Zeng;D. Velez;Jiacai Lu;G. Tryggvason