Simulation of Injection Molding of Thermoplastics Reinforced with Fibers and Nano-Particles

本研究的目标是模拟模具填充过程的热塑性塑料（TP）熔体增强短纤维和长纤维，并最终纳米颗粒的高纵横比使用本构关系（即应力张量与方向生成表达式耦合），允许耦合之间的流动和颗粒取向，并包括运动学的正面流。 预测的颗粒取向分布将与微观力学模型一起沿着使用，以预测整个注塑部件的刚度变化。 一个关键因素是流变学方法的发展，这将提供基本的材料流动性能的数值模拟包。将进行与注射成型相关的基本流动的预测颗粒取向分布的实验评估，以评估模拟的性能。这项工作有许多社会效益。通过结合其中流动和结构与粘弹性沿着耦合的模型，预期模具的设计和注射成型条件的选择将显著改善和加速增强TP。 这将有助于提高美国汽车制造商在全球汽车市场上的竞争能力，因为设计变更可以更快，更便宜。一旦为注塑成型开发了模拟软件包，它就可以很容易地扩展到其他工艺，如压缩成型和注射压缩成型。 从教育的角度来看，研究生将了解到复合材料零件的性能高度依赖于加工条件，并且存在预测这种关系的潜力。此外，学生将学习合作解决复杂问题的重要性，因为工程专业的学生将学习使用有限元法进行数值模拟，而数学专业的学生将学习运输过程和结构化流体的流变学。 该项目是弗吉尼亚理工大学和能源部实验室（ORNL和PNWL）之间的合作努力，并由NSF和能源部的FreedomCAR计划共同资助。

The goal of this research is to simulate the mold filling process for thermoplastic(TP) melts reinforced with short and long fibers and eventually nano-particles of high aspect ratio using constitutive relations (i.e. stress tensors coupled with an orientation generation expression) which allow coupling between the flow and particle orientation and to include kinematics of frontal flow. The predicted particle orientation distribution will be used along with micro-mechanical models to predict the stiffness variation throughout an injection molded part. A key element is the development of the rheological methodology which will provide basic material flow properties to the numerical simulation package. An experimental evaluation of the predicted particle orientation distribution for basic flows associated with injection molding will be carried out to assess the performance of the simulation. There are numerous societal benefits to this work. By incorporating models in which the flow and structure are coupled along with viscoelasticity, it is expected that the design of molds and selection of injection molding conditions will be significantly improved and accelerated for reinforced TP's. This will help improve the ability of US automakers to compete in the world-wide automotive market as design changes can be made more rapidly and cheaply. Once a simulation package is developed for injection molding, it can easily be extended to other processes such as compression molding and injection-compression molding. From an educational view graduate students will learn that the properties of composite parts are highly dependent on processing conditions and the potential to predict this relation exists. Furthermore, the students will learn the importance of a cooperative effort in solving complex problems as the engineering student will learn about numerical simulation using the finite element method while the mathematics student will learn about transport processes and the rheology of structured fluids. This project is a cooperative effort between Virginia Tech and DOE laboratories (ORNL and PNWL) and is co-funded by NSF and DOE's FreedomCAR program.