Particle-segregation in chutes, silos, conveyor belts and rotating drums

不同尺寸或密度的颗粒通常在工业流中分离，例如斜槽、筒仓、传送带和旋转滚筒。这是材料不均匀性的最大原因，这给谷物的处理和加工带来了严重的问题，导致工厂停工和产品浪费。最常见的分离形式发生在表面雪崩中，每当静止的颗粒状材料倾斜超过其休止角时，就会发生表面雪崩。例如，在早餐时把牛奶什锦早餐倒入碗中！这些雪崩在按大小分选颗粒方面非常有效，大的上升到表面，小的下降到底部。颗粒的密度可以增强或抵消这种效应。当这些流动停止时，在存款中形成各种各样的颗粒尺寸和密度分布，有时只有一种颗粒类型的大区域。这自然会在应该充分混合的过程中出现一个主要问题。了解隔离过程并能够有效地对其进行建模是能够制定减轻其影响的策略的第一步。该提案旨在使用小规模实验，理论，连续模拟和离散元模拟（其中每个单个颗粒的相互作用被建模）的强大组合来确定分离速率对颗粒特性的函数依赖性，以及施加的剪切速率和压力。由此产生的数学模型将被应用于更复杂的流动，其中表面雪崩和静态或缓慢移动的颗粒之间存在质量传输。这给该项目带来了最大的挑战，因为与流体相比，颗粒材料的流变学仍然知之甚少，这使得模拟筒仓中的流动成为问题。然而，在过去的十年中，在所谓的mu（I）-流变学的发展中取得了重大进展，其在大范围的参数空间上起作用。我们的目标是正则化的模型，包括额外的物理，使它可以应用于所有地区的流动，从而解决体积速度场。这将允许计算不断变化的颗粒尺寸和密度分布，以便我们可以详细了解一种颗粒类型的口袋是如何形成的。我们与工业合作伙伴一起制定缓解策略，利用我们的隔离知识设计巧妙的滑道和筒仓，大大降低其影响。

Particles of differing size or density often segregate in industrial flows such as chutes, silos, conveyor belts and rotating drums. This is the single biggest cause of material non-uniformity, which poses significant problems in handling and processing the grains, leading to plant downtime and product wastage. The most common form of segregation occurs in surface avalanches, which develop whenever a static granular material is tipped above its angle of repose. For example, pouring one's muesli into a bowl at breakfast! These avalanches are very efficient at sorting particles by size, with the large ones rising to the surface and the small ones percolating down to the base. The density of the grains may enhance or counteract this effect. When these flows come to rest a rich variety of particle size and density distributions develop in the deposit, sometimes with large regions of just one particle type. This naturally presents a major problem in processes that are supposed to be well-mixed. Understanding the segregation process and being able to model it effectively is the first step in being able to develop strategies to mitigate its effects. This proposal aims to use a powerful combination of small scale experiments, theory, continuum simulation and discrete element simulations (where the interactions of every single particle are modeled) to determine the functional dependence of the segregation rates on particle properties, as well as the applied shear-rate and pressure. The resulting mathematical model will then be applied to more complex flows, where there is mass transport between the the surface avalanche and the static, or slowly moving, grains beneath. This presents the project with its biggest challenge, because the rheology of granular materials is still very poorly understood, compared to fluids, which makes simulating the flow in a silo problematical. Over the past decade there has however been significant progress in the development of the so called mu(I)-rheology, which works over a large range of parameter space. Our aim is to regularize the model, by including additional physics, so that it can be applied in all regions of the flow and hence solve for the bulk velocity field. This will then allow the evolving particle-size and density distribution to be computed, so that we can understand in detail how pockets of just one particle type form. With our industrial partners we develop mitigation strategies, that use our knowledge of segregation to design clever chutes and silos that greatly reduce its effects.