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

机织物复合材料中成型引起的皱纹的建模和优化的集成多尺度方法

• 批准号: RGPIN-2018-04575
• 负责人: SadeghzadehMilani, Abbas
• 金额: $ 2.84万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=713100
• 关键词: integrated; multi; scale; approach; modeling

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.

作为特殊类别的纺织结构复合材料，编织织物增强聚合物（WFRP）在包括航空航天，汽车，建筑，海洋和防御的多个领先行业中，由于它们的易用性以及光线的结合而引起了极大的关注。重量和高强度。尽管有这么广泛的兴趣，但仍然存在最佳制造条件下应应用于WFRP的知识和标准化，以避免诸如面内和/或平面外皱纹之类的主要缺陷。当前的最新最新表明，要正确捕获和减轻WFRP零件中的皱纹，需要进行集成的设计和制造方法，从而使皱纹从悬垂阶段到最终的树脂固化阶段的演变（即在下面）可以考虑处理条件）和残余应力形成。为了满足建模的高度复杂性，以及捕获高保真和有效缺陷缓解策略的高工业需求，该NSERC发现研究计划旨在开发一种新的集成多物理学，多规模模拟和优化方法用于WFRP中的悬垂和加工引起的皱纹。为了增加所提出的织物加工模型的可靠性，还将通过与X射线微观学微观结构相关的强大实验设计技术来解释不确定性效应。 该研究计划的主要切实结果将是（i）增强我们对在不同的织物特性，形成条件和部分形状下有助于造成WFRP皱纹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，该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高效的皱纹缓解策略，以及（iii）培训许多具有高级表征能力的高素质人员（HQP） ，建模，形成纺织品复合材料的仿真和优化。一旦建立和验证，提议的集成方法以及计算机工具将被合作材料研究网络（CRN）的合作公司广泛使用，并解决流程开发的间接费用（目前高达70％）由于随机试验和错误而由制造商组成。