论文标题
概率的虚拟过程链，用于量化板材成型化合物中过程引起的不确定性
A probabilistic virtual process chain to quantify process-induced uncertainties in Sheet Molding Compounds
论文作者
论文摘要
板材成型化合物（SMC）的制造过程以非确定性的方式影响组件的特性。为了预测对机械性能的影响，我们开发了一个虚拟过程链，该链充当了从复合到失败的SMC标本的数字双胞胎。更具体地说，我们将带有单个字段的结构模拟告知，以根据制造过程的直接捆绑捆绑模拟计算出的方向和体积分数。结构模拟采用插值直接的深层材料网络来高档量身定制的SMC损坏模型。我们评估数百个虚拟标本，并对机械性能进行概率分析。我们估计源自过程诱导的固有随机微观结构以及不同初始SMC堆栈配置的不确定性的贡献。我们的预测结果与实验拉伸测试和热重分析非常吻合。
The manufacturing process of Sheet Molding Compound (SMC) influences the properties of a component in a non-deterministic fashion. To predict this influence on the mechanical performance, we develop a virtual process chain acting as a digital twin for SMC specimens from compounding to failure. More specifically, we inform a structural simulation with individual fields for orientation and volume fraction computed from a direct bundle simulation of the manufacturing process. The structural simulation employs an interpolated direct deep material network to upscale a tailored SMC damage model. We evaluate hundreds of virtual specimens and conduct a probabilistic analysis of the mechanical performance. We estimate the contribution to uncertainty originating from the process-induced inherent random microstructure and from varying initial SMC stack configurations. Our predicted results are in good agreement with experimental tensile tests and thermogravimetric analysis.
