A Computational Framework for Predicting Properties From Multifield Processing Conditions in Polymer Matrix Composites
A Computational Framework for Predicting Properties From Multifield Processing Conditions in Polymer Matrix Composites
复制标题
用于根据聚合物基复合材料的多场加工条件预测性能的计算框架
DOI：
10.1115/smasis2020-2390
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Rodriguez, Manuel A.
中科院分区：
文献类型：
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作者：
Widdowson, Denise;von Lockette, Paris;Erol, Anil;Rodriguez, Manuel A.
复合材料可以通过调整工艺变量来适应特定的应用。这些变量包括那些与组成相关的变量，例如组分的体积分数和那些与加工方法相关的变量，这些方法可以影响复合材料拓扑结构。在颗粒基质复合材料的情况下，夹杂物的取向影响所得的复合材料性质，特别是在颗粒可以取向并排列成结构的情况下。在这项工作中，我们研究了耦合电场和磁场处理与外部施加的字段对这些结构的影响，从而对由此产生的材料性能。以产生产生目标材料特性的微结构为目标改变这些加工条件的能力为复合材料特性的设计增加了额外的控制水平。此外，虽然分析模型允许从组分和复合材料拓扑结构预测所得复合材料性质，但这些模型并不从工艺变量向上建立以进行这些预测。这项工作耦合了微尺度结构形成的模拟，微尺度结构形成是由颗粒填充聚合物基质复合材料的耦合电场和磁场处理引起的，通过对这些结构的有限元分析，提供了工艺、结构和性能之间的直接和明确的联系。这项工作表明，这些方法作为一种工具，用于确定复合材料的性能，从成分和工艺参数的实用性。初始的粒子动力学模拟，结合粒子之间的电磁响应和粒子和所施加的领域，包括介电泳，用于随机生成一组给定的过程变量的代表性体积元素。接下来，这些RVE作为周期性结构，使用有限元分析产生散装材料的属性进行分析。结果表明，收敛的模拟尺寸和离散化，验证RVE作为一个适当的表示的复合材料的体积。计算出的材料性能相比，传统的有效介质理论模型。模拟允许映射的复合材料的属性，不仅组成，但也从根本上从加工模拟，产生不同的颗粒配置，一个步骤不存在于传统的或更现代的有效介质理论，如Halpin Tsai或双包理论。
Composites can be tailored to specific applications by adjusting process variables. These variables include those related to composition, such as volume fraction of the constituents and those associated with processing methods, methods that can affect composite topology. In the case of particle matrix composites, orientation of the inclusions affects the resulting composite properties, particularly so in instances where the particles can be oriented and arranged into structures. In this work, we study the effects of coupled electric and magnetic field processing with externally applied fields on those structures, and consequently on the resulting material properties that arise. The ability to vary these processing conditions with the goal of generating microstructures that yield target material properties adds an additional level of control to the design of composite material properties. Moreover, while analytical models allow for the prediction of resulting composite properties from constituents and composite topology, these models do not build upward from process variables to make these predictions.This work couples simulation of the formation of microscale architectures, which result from coupled electric and magnetic field processing of particulate filled polymer matrix composites, with finite element analysis of those structures to provide a direct and explicit linkages between process, structure, and properties. This work demonstrates the utility of these method as a tool for determining composite properties from constituent and processing parameters. Initial particle dynamics simulation incorporating electromagnetic responses between particles and between the particles and the applied fields, including dielectrophoresis, are used to stochastically generate representative volume elements for a given set of process variables. Next, these RVEs are analyzed as periodic structures using FEA yielding bulk material properties. The results are shown to converge for simulation size and discretization, validating the RVE as an appropriate representation of the composite volume. Calculated material properties are compared to traditional effective medium theory models. Simulations allow for mapping of composite properties with respect to not only composition, but also fundamentally from processing simulations that yield varying particle configurations, a step not present in traditional or more modern effective medium theories such as the Halpin Tsai or double-inclusion theories.