Optimal design of graded particle packings based on multiscale models

基于多尺度模型的分级颗粒填料优化设计

• 批准号: 493700036
• 负责人: Professor Dr.-Ing. Heiko Briesen
• 金额: --
• 依托单位: Lehrstuhl für Systemverfahrenstechnik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/493700036?language=en
• 关键词: Optimal; design; graded; particle; packings

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 However, manufacturing methods have at least for porous media superseded the understanding of what one actually wants to manufacture and which pore scale properties are actually desirable for different applications.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.

与材料科学中的功能梯度材料类似，开发了一种用于工艺工程应用的最佳梯度颗粒填料的策略。这种方法的动机是观察到近年来出现了多种制造选择，例如，现在在许多科学和技术分支中使用的增材制造。这种新的可能性使多孔介质的定义精确到以前难以想象的程度。然而，至少对于多孔介质的制造方法已经取代了人们对实际想要制造的东西以及不同应用中实际需要的孔隙尺度特性的理解。在这个项目中，我们希望通过解决具有局部变化性质的多孔介质，特别是颗粒填料，来解决这个普遍问题。我们研究了最优控制作为一种合适的方法来预测理想的局部变化的颗粒填料性质基于预定义的总体目标。基于模型的预测将使用实验测试系统进行验证。