Experimentally validated models for the prediction of fatigue damage progression and failure of conventional and green polymeric composites in aerospace and biomedical applications

经过实验验证的模型，用于预测航空航天和生物医学应用中传统和绿色聚合物复合材料的疲劳损伤进展和失效

基本信息

批准号：
RGPIN-2015-03944
负责人：
Fawaz, Zouheir
金额：
$ 1.82万
依托单位：
Ryerson University
依托单位国家：
加拿大
项目类别：
Discovery Grants Program - Individual
财政年份：
2019
资助国家：
加拿大
起止时间：
2019-01-01 至 2020-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=680696
关键词：
Experimentally validated models prediction fatigue

项目摘要

The use of polymer matrix composites (PMCs) in modern airplanes has dramatically increased since 2005, leading to changes in aircraft performance and environmental friendliness that have proven to be transformative within the worldwide aerospace industry. Such rapid proliferation, while opening the door wide for many new applications such as the biomedical ones proposed herein, also calls, among other things, for the development of analytical models that can help in the prediction of the long term fatigue failure of those PMCs. The latter is the aim of the proposed research program which will also focus on their emerging biomedical applications. The research effort will aim to confirm the validity of the proposed models by conducting mechanical loading tests and comparing the obtained results with those predicted by the models. The research will focus on two classes of PMCs, namely synthetic fiber-reinforced PMCs used in structural load bearing aerospace applications and bio-based (green) PMCs with a focus on those reinforced with flax fibers. The latter further addresses a pressing need to develop more environmentally friendly PMCs. The specific objectives include the development of generalized micromechanical-based fatigue failure prediction models that combine the concepts of micromechanics with progressive continuum damage mechanics (CDM) and statistical considerations, the development of computational software to implement the proposed fatigue models into Finite Element solutions, and the experimental characterization of various PMC material systems in order to confirm the accuracy and generality of the proposed models. The general approach for modeling is to represent the basic laminate building block (the lamina) through a network of micromechanical representative volume elements (RVE), model the failure of the lamina based on the behaviour of RVE under loading, and predict the property degradation and ultimately failure of the laminate through a continuum damage mechanics scheme. For the flax fiber based composites proposed for use in biomedical applications, the general approach will include the experimental characterization of their unidirectional laminae mechanical response under temperature, moisture, and loading conditions representative of their intended biomedical application. The ability to use accurate predictive models and the availability of the large amount of test data that will be produced through the proposed research will generate the necessary confidence in PMCs performance and pave the way to their wider use in the light weight, fuel efficient and environmentally friendly airplanes of the future, as well as biomedical implants where the advances made through the proposed research program will take this class of advanced materials one step closer to a widespread usage in this burgeoning area of engineering materials application.**

自2005年以来，现代飞机中聚合物基质复合材料（PMC）的使用已大大增加，从而导致飞机性能和环境友好的变化，这些绩效和环境友好已被证明在全球航空航天行业中具有变革性。如此迅速的扩散，同时为许多新应用打开大门，例如本文提出的生物医学应用程序，还呼吁开发分析模型的开发，这些模型可以帮助预测这些PMC的长期疲劳失败。后者是拟议的研究计划的目的，该计划还将重点关注其新兴的生物医学应用。研究工作将旨在通过进行机械载荷测试并将所获得的结果与模型预测的结果进行比较，以确认所提出的模型的有效性。该研究将重点放在两类的PMC上，即用于航空航天应用和基于生物的PMC的合成纤维增强的PMC，重点是将亚麻纤维增强的PMC。后者进一步解决了开发更环保PMC的紧迫需求。具体目标包括开发一般基于微机械的疲劳失效预测模型，这些模型将微力学的概念与渐进式连续性损害力学（CDM）和统计考虑，开发计算软件，以将提议的疲劳模型实施到有限元解决方案中，并将各种PMC材料系统的实验化以确认精确的模型和生成模型。建模的一般方法是通过微机械代表体积元素（RVE）网络来代表基本的层压板构建块（层），基于加载下的RVE的行为对层层的失败进行建模，并预测属性降解并最终通过连续损伤机械方案通过连续性损坏机械方案进行层压板的失败。对于建议用于生物医学应用的基于亚麻纤维的复合材料，一般方法将包括在温度，水分和加载条件下代表其预期的生物医学应用的实验表征其单向层层机械响应。使用准确的预测模型以及通过拟议研究产生的大量测试数据的可用性的能力将产生对PMCS绩效的必要信心，并为它们在轻度，燃油效率和环境友好的未来飞机中的更广泛使用铺平道路，以及该班级的生物医学植入物在此班级中，该材料将在此范围内通过该材料进行培训。工程材料应用。**