An integrated multi-scale approach to modeling and optimization of forming-induced wrinkles in woven fabric composites

机织纤维增强聚合物（WFRP）作为一类特殊的纺织结构复合材料，由于其易于成型以及重量轻和强度高的结合，在航空航天，汽车，建筑，船舶和国防等几个主要行业中受到了相当大的关注。尽管这种广泛的兴趣，仍然存在缺乏知识和标准化的最佳制造条件，应该应用于WFRP，以避免主要缺陷，如面内和/或面外皱纹。目前的先进技术表明，要正确捕获和减轻WFRP部件中的褶皱，需要采用集成的设计和制造方法，从而可以考虑褶皱从悬垂阶段一直到最终树脂固化阶段（即在加工条件下）和残余应力形成的演变。为了解决建模的高度复杂性，以及工业对捕获高保真度和有效缺陷缓解策略的高需求，NSERC Discovery研究项目旨在开发一种新的集成多物理场、多尺度模拟和优化方法，用于WFRP中悬垂和加工引起的褶皱。为了增加所提出的织物加工模型的可靠性，不确定性效应也将通过与织物微观结构的x射线微断层扫描分析相关的稳健实验设计技术来考虑。******该研究项目的主要实际成果将是：(i)增强我们对不同织物性能、成型条件和零件形状下WFRP皱折形成的多尺度机制的基本理解；（ii）开发一种新的机器学习和优化工具，帮助工业设计师对具有成本效益和高效的起皱缓解策略提出最终建议，以及（iii）培训一批具有纺织复合材料高级表征、建模、成型模拟和优化能力的高素质人员（HQP）。一旦建立和验证，拟议的集成方法以及计算机工具预计将被复合材料研究网络（CRN）的加拿大合作公司广泛使用，并解决制造商因随机试验和错误而承受的工艺开发间接成本（目前高达70%）。**

Woven Fabric-Reinforced Polymers (WFRP), as a special class of Textile Structural Composites, have found considerable attention in several leading industries including aerospace, automotive, construction, marine, and defense, owing to their ease of formability along with a combination of light weight and high strength. Despite this wide interest, there still exists a lack of knowledge and standardization in optimum manufacturing conditions that should be applied on WFRP to avoid major defect such as in-plane and/or out-of-plane wrinkles. The current state-of-the-art shows that to correctly capture and mitigate wrinkles in WFRP parts, an integrated design and manufacturing approach is required, whereby the evolution of wrinkles from the draping stages all through to the final resin curing stages (i.e. under processing conditions) and residual stress formations can be accounted for. To address the high degree of complexity in modeling, as well as the high industrial demand for capturing high-fidelity and effective defect mitigation strategies, this NSERC Discovery research program aims at developing a new integrated multi-physics, multi-scale simulation and optimization approach for draping- and processing-induced wrinkles in WFRP. In order to add to the reliability of the proposed fabric processing models, uncertainty effects will also be accounted via robust design-of-experiment techniques linked to X-ray micro-tomography analysis of fabrics microstructure. ******The main tangible outcomes of this research program will be (i) enhancing our fundamental understanding of multi-scale mechanisms contributing to the formation of wrinkles in WFRP under different fabric properties, forming conditions and part shapes; (ii) developing a new machine-learning and optimization tool that can assist industrial designers to make final recommendations toward cost-effective and efficient wrinkling mitigation strategies, and (iii) training a number of highly qualified personnel (HQP) with competencies in advanced characterization, modeling, forming simulation and optimization of textile composites. Once established and validated, the proposed integrated approach along with the computer tools are expected to be widely used by the collaborating Canadian companies at the Composites Research Network (CRN), and address the process development overhead costs (currently as high as 70%) endured by manufacturers due to random trial and errors. **