Optimal design of graded particle packings based on multiscale models

类似于材料科学中的功能梯度材料，开发了一种策略来获得用于过程工程应用的最优梯度颗粒填料。这种做法的动机是注意到近年来出现了各种制造选择，例如加法制造，现在许多科学和技术分支都使用这种制造方法。这种新的可能性使得对多孔介质的精确定制达到了以前无法想象的程度。然而，至少对于多孔介质来说，制造方法已经取代了人们对实际想要制造什么以及对于不同应用实际上需要哪些孔尺度特性的理解。通过这个项目，我们希望通过解决具有局部不同性质的多孔介质，特别是颗粒填充，来解决这个一般问题。我们研究了最优控制作为一种合适的方法，用于基于预定义的总体目标来预测颗粒堆积属性中所需的局部变化。基于模型的预测将使用实验测试系统进行验证。

In analogy to the functionally-graded materials in materials science, a strategy to derive optimally-graded particle packings for process-engineering applications is developed. This approach is motivated by the observation that diverse manufacturing options became available in recent years, e.g., additive manufacturing, which are now used in many branches of science and technology. Such new possibilities allow the well-defined tailoring of porous media to a previously unimaginable degree. However, manufacturing methods have at least for porous media superseded the understanding of what one actually wants to manufacture and which pore scale properties are actually desirable for different applications. With this project we want to contribute to this general problem by addressing porous media with locally varying properties, in particular particle packings. We investigate optimal control as a suitable method for predicting desirable local variations in particle-packing properties based on predefined overall goals. The model-based predictions will be validated using an experimental test system.