Towards more complete models and improved computer simulation tools for Liquid Composite Molding (LCM)

为液体复合成型 (LCM) 打造更完整的模型和改进的计算机模拟工具

• 批准号: RGPIN-2022-04495
• 负责人: Trochu, François
• 金额: $ 2.84万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=754522
• 关键词: Towards; more; complete; models; improved

The use of advanced composites represents a key issue in many industrial fields facing economic and environmental challenges. Over the last 15 years, "Liquid Composite Molding" (LCM) processes have been used successfully to produce lightweight primary structures in the aerospace and automotive sectors. LCM manufacturing consists of injecting a liquid reactive resin to impregnate a dry fibrous reinforcement contained in a mold cavity. LCM processes can produce high performance composite parts, have a strong potential of automation and offer several possibilities such as the use of 3D woven reinforcements to prevent delamination problems encountered in composite laminates. Several Canadian firms could benefit from the advantages provided by LCM processes, but the development of new products requires more advanced computer predictive tools. The research project aims to fill this gap by developing innovative and more precise numerical models to improve LCM simulation and predict the performance of parts. Three main research topics will be investigated: 1.Create geometrical multiscale models of the 3D architecture of fibrous reinforcements from observations obtained by X ray microtomography. This approach is based on parametric surface interpolation of fiber tows by dual kriging. It allows creating, with controlled accuracy and from a minimum number of data points, a multiscale representation of the fiber architecture of engineering textiles called « Digital Material Twin »(DMT). 2.Using DMT models, simulate flows in fibrous reinforcements of dual scale porosity, namely in fiber tows and through the mesopores between tows. This will make possible to study and visualize air entrapment and transport in engineering textiles. This kind of analysis is required to predict part quality in advanced composite applications (planes, electric cars and trucks, wind blades, etc.). 3.Develop a simple and innovative method to measure the "apparent permeability" of fibrous reinforcements filled through thickness with a "Distribution Medium"(DM). This approach will allow performing 2D flow simulations (instead of full 3D analysis) to fabricate large composite parts by "Liquid Resin Infusion" (LRI) with DM. A significant performance gain is expected by reducing the computational time by a factor of 1000, and even more in the case of complex sandwich composites with grooves and holes in the core such as the ones found in wind blades. Overall, several innovative numerical tools will be progressively developed to simulate key features of LCM processes. They will be implemented to study the LCM fabrication of parts of increasing complexity with the goal of providing practical tools to industry. The long-term objective is to create new applications of high performance composites using virtual manufacturing in process development and scale-up. Finally, the Highly Qualified Personal (HQP) trained under the project will provide a competitive edge to Canadian companies.

先进复合材料的使用是许多面临经济和环境挑战的工业领域的关键问题。在过去的15年里，“液态复合材料成型”（LCM）工艺已成功用于生产航空航天和汽车领域的轻质主要结构。LCM制造包括注入液体反应性树脂以覆盖包含在模腔中的干燥纤维增强材料。LCM工艺可以生产高性能的复合材料部件，具有很强的自动化潜力，并提供多种可能性，例如使用3D编织增强材料来防止复合材料层压板中遇到的分层问题。几家加拿大公司可以从LCM工艺提供的优势中受益，但新产品的开发需要更先进的计算机预测工具。该研究项目旨在通过开发创新和更精确的数值模型来填补这一空白，以改善LCM模拟和预测零件的性能。主要研究内容包括：1.利用X射线显微层析成像技术建立纤维增强体三维结构的几何多尺度模型。这种方法是基于参数曲面插值的纤维丝束的双重克里格。它允许以受控的精度和最少数量的数据点创建工程纺织品纤维结构的多尺度表示，称为“数字材料双胞胎”（DMT）。2.使用DMT模型，模拟双尺度孔隙度的纤维增强体中的流动，即在纤维丝束中和通过丝束之间的中孔。这将使研究和可视化工程纺织品中的空气截留和传输成为可能。在先进复合材料应用（飞机、电动汽车和卡车、风力叶片等）中，需要这种分析来预测零件质量。3.开发一种简单而创新的方法来测量用“分布介质”（DM）填充的纤维增强材料的“表观渗透率”。这种方法将允许执行2D流动模拟（而不是完整的3D分析），以通过DM的“液体树脂灌注”（LRI）制造大型复合材料部件。一个显着的性能增益预计通过减少计算时间的一个因素的1000，甚至更多的情况下，复杂的夹层复合材料的槽和孔的核心，如那些发现在风力叶片。总体而言，将逐步开发几种创新的数值工具，以模拟LCM过程的关键特征。它们将被实施来研究日益复杂的部件的LCM制造，目的是为工业提供实用的工具。长期目标是在工艺开发和规模扩大中使用虚拟制造来创造高性能复合材料的新应用。最后，在该项目下培训的高素质人员将为加拿大公司提供竞争优势。