Multi-scale probabilistic simulation chain for the continuous modelling of the manufacturing process and the structural behavior of disordered fiber-reinforced injection molded components (MeproSi)

由于不仅在航空航天应用中，而且在工业规模大规模生产占主导地位的领域（如汽车行业）中对轻质部件的需求不断增加，不连续纤维增强材料的重要性日益增加。在热固性注射成型中制造的现代长纤维复合材料可能表现出与铝类似的机械性能。然而，在制造过程中消耗的能源明显减少，进一步改善了二氧化碳足迹。一个主要的缺点是它们的随机，无序和工艺依赖的微观结构，导致其宏观材料响应中固有的不可避免的不确定性。这种不确定性是由局部纤维含量、长度和取向分布的不确定性以及组分本身和纤维基质界面的材料响应的不确定性引起的。叠加的是由制造过程施加的微观结构特性的局部变化。在结构应用中，材料响应中不可避免的不确定性导致过度保守的设计，不必要的大安全裕度，从而使材料轻量化潜力的次优开发，该项目的目标是预测与工艺相关的材料响应中的任意不确定性以及在使用条件下注塑成型部件的结构行为。为此目的，将建立沿过程链在所有相关尺度上的集成概率多尺度模拟沿着。起点是不确定的过程，导致不确定的微观结构，从而导致不确定的结构响应。基于概率过程模拟，将推导出局部微观结构及其控制参数的概率分布。使用概率均匀化过程，获得材料行为的随机描述，为材料响应的随机场表示提供输入。必须定义和实施适当的策略，用于确定基于在过程模拟中获得的空间变化的随机特性的随机场的各个表示。通过这种方法，可以从工艺条件开始，以综合的方式预测不确定性对短纤维增强部件的结构响应的影响。通过这种方式，材料和结构响应中的固有不确定性变得可通过计算方法访问和控制。最初的重点是任意的不确定性。在第二阶段，打算扩大范围，包括认识上的不确定性，例如测量或建模不准确。

Due to the increasing demand for lightweight components not only in aerospace applications but also areas dominated by industrial scale mass production such as the automotive sector, discontinuously fiber reinforced materials gain an increasing importance. Modern long fiber composites manufactured in thermoset injection molding might exhibit similar mechanical properties as aluminum. Nevertheless, distinctively lower amounts of energy are consumed during the manufacturing process, further improving the CO2-footprint. A major shortcoming is their random, disordered and process dependent microstructure, causing an inherent inevitable uncertainty in their macroscopic material response. This uncertainty is caused by the uncertainties in the local fiber content, length and orientation distributions as well as by uncertainties in the material response of the constituents themselves and the fiber matrix interfaces. Superimposed are local variations in the microstructural properties imposed by the manufacturing process. In structural application, the inevitable uncertainty in the material response results in over-conservative designs, unnecessarily large safety margins and thus a suboptimum exploitation of the materials lightweight potential.The objective of the proposed project is a prediction of the process-related aleatoric uncertainties in the material response and the resulting structural behavior of injection molded parts under in-service conditions. For this purpose, an integrated probabilistic multiscale simulation along the process chain on all relevant scales will be established. Starting point is the uncertain process, resulting in an uncertain microstructure and thus an uncertain structural response. Based on a probabilistic process simulation, the local microstructure and the probability distributions of its governing parameters will be derived. Using a probabilistic homogenization procedure, a stochastic description of the material behavior is obtained, providing the input for a random field representation of the material response. Appropriate strategies for determination of individual representations of the random fields based on spatially varying stochastic properties obtained in the process simulation have to be defined and implemented. By this means, the effect of uncertainties on the structural response of short fiber reinforced components can be predicted in an integrated manner, starting from the process conditions. By this means, the inherent uncertainties in the material and structural response become accessible and controllable by computational methods. The initial focus is on aleatoric uncertainties. In a second phase, an extension to include epistemic uncertainty, e.g. from measurement or modelling inaccuracies, is intended.