Automated design and optimisation of dynamic mixing and shear elements for single-screw extruder

混合和剪切元件越来越多地用于单螺杆挤出机，因为在保持塑料熔体均匀度的同时，需要更高的产量。混合和剪切元件的任务是在塑料熔体中均匀分散和分布添加剂和填料，并使熔体热均一。到目前为止，混合元件的设计都是基于设计者的经验。相比之下，通过三维模拟可以更详细地了解混合过程。然而，现有的计算挤出机混合操作的方法往往具有很大的局限性，通常仅用于对单个混合元件的示例性评估。一方面，在选择合适的混合指数方面出现了困难。另一方面，在混合元件的数值优化方面的巨大努力是在设计阶段使用流动模拟的障碍。到目前为止，还没有可用的软件来自动优化混合元件。在这种背景下，本项目的目标是开发一个优化框架，使单螺杆挤出机中混合和剪切元件的自动模拟设计和优化成为可能。在这个框架下，将获得关于理想混合单元几何形状的知识，这些知识依赖于混合任务。为此，将对申请CATS的现有内部流动解算器进行修改，以便能够对挤出机熔体区域内的混合过程进行非等温模拟。然后，修改后的求解器将集成到优化例程中。同时，通过将模拟结果与实验参考数据进行比较，IKV将为复杂混合元件的真实三维模拟确定合适的边界条件。在下一步，IKV将模拟比较不同的混合指标，并确定那些特别适合混合元件设计的指标。在优化框架中，这些混合指标被组合成单个目标函数。此外，IKV将模拟分析和描述混合元件几何形状和所产生的流动条件之间的因果关系。这一知识的增长将被纳入优化框架，并有助于识别将能够进行优化的合适的混合元件部分。在成功实施后，IKV和CATS将使用优化框架来设计和优化适用于非常广泛的应用的混合元件序列。开发的混合元件序列最终将被制造出来，并用于优化框架的实际验证。

Mixing and shear elements are increasingly used in single-screw extruders due to the demand for ever higher throughputs while maintaining plastics melt homogeneity. The task of mixing and shear elements is to disperse and distribute additives and fillers evenly in the plastics melt and homogenise the melt thermally. To date, the design of mixing elements is based on the experience of the designer. By contrast, a much more detailed insight into the mixing process can be achieved via three-dimensional simulations. However, available approaches for the computation of mixing operations in extruders often have great limitations and are generally used only for exemplary evaluation of individual mixing elements. Difficulties arise on the one hand in the choice of a suitable mixing index. On the other hand, the high effort in the numerical optimisation of mixing elements is an obstacle to the use of flow simulations in the design phase. So far, there is no software for the automated optimisation of mixing elements available.Against this background, it is the goal of this project to develop an optimisation framework that enables the automated simulative design and optimisation of mixing and shear elements in single-screw extruders. With this framework knowledge about the ideal mixing element geometry in dependence of the mixing task will be acquired. For this purpose, the existing in-house flow solver of the applicant CATS will be modified in order to enable the non-isothermal simulation of the mixing processes in the melt zone of the extruder. The modified solver will then be integrated into an optimisation routine. Meanwhile, the IKV will identify suitable boundary conditions for a realistic three-dimensional simulation of complex mixing elements using a comparison of simulation results and experimental reference data. In the next step, the IKV will simulatively compare different mixing indexes and identify those indexes that are particularly well suited for the design of mixing elements. These mixing indexes are combined into a single objective function in the optimisation framework. In addition, the IKV will simulatively analyse and characterise the cause-effect relationships between the mixing element geometry and the resulting flow conditions. This gain in knowledge will be incorporated into the optimisation framework and facilitate the identification of suitable mixing element sections that will be enabled for the optimisation. Following its successful implementation, the optimisation framework will be used by IKV and CATS in order to design and optimise a mixing element sequence, which is suitable for a very wide range of applications. Thedeveloped mixing element sequence will finally be manufactured and used for the practical validation of the optimisation framework.