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

机织织物增强聚合物（WFRP）作为纺织结构复合材料的一个特殊类别，由于其易于成型沿着轻质和高强度的组合，在包括航空航天、汽车、建筑、船舶和国防在内的几个领先行业中受到了相当大的关注。尽管这种广泛的兴趣，仍然存在着缺乏知识和标准化的最佳制造条件，应适用于WFRP，以避免重大缺陷，如平面内和/或平面外的皱纹。目前的最新技术水平表明，为了正确捕获和减轻WFRP部件中的褶皱，需要集成的设计和制造方法，由此可以解释褶皱从覆盖阶段一直到最终树脂固化阶段（即，在加工条件下）的演变和残余应力形成。为了解决建模的高度复杂性，以及对捕获高保真和有效缺陷缓解策略的高工业需求，NSERC Discovery研究计划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中的悬垂和加工引起的皱纹。为了增加拟议的织物加工模型的可靠性，不确定性的影响也将通过强大的实验设计技术与织物微观结构的X射线显微断层扫描分析。** 本研究计划的主要实际成果将是（i）提高我们对不同织物性能、成型条件和部件形状下WFRP中褶皱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，可以帮助工业设计师提出最终建议，以实现具有成本效益和效率的减轻磨损战略，以及（iii）培训一批高素质的人员（HQP），他们具有纺织复合材料的高级表征、建模、成形模拟和优化方面的能力。一旦建立和验证，拟议的集成方法沿着的计算机工具，预计将被广泛使用的加拿大公司在复合材料研究网络（CRN）的合作，并解决工艺开发的间接成本（目前高达70%）所承受的制造商由于随机试验和错误。**

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. **