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.

在面临经济和环境挑战的许多工业领域，先进复合材料的使用是一个关键问题。在过去的15年里，“液体复合材料模塑”(LCM)工艺已成功地用于制造航空航天和汽车行业的轻质初级结构。LCM制造包括注入液体反应性树脂以浸渍包含在模腔中的干纤维增强体。LCM工艺可以生产高性能的复合材料零件，具有强大的自动化潜力，并提供了多种可能性，例如使用3D机织增强材料来防止复合材料层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，以改进LCM模拟和预测部件的性能。主要研究内容如下：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。该方法基于双克立格法对光纤丝束进行参数曲面插补。它允许以可控的精度从最少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.利用DMT模型，模拟了双尺度孔隙率纤维增强体中的流动，即纤维丝束中的流动和丝束之间的中孔流动。这将使研究和可视化工程纺织品中的空气滞留和传输成为可能。在先进的复合材料应用(飞机、电动汽车和卡车、风叶等)中，需要这种分析来预测零件质量。3.开发了一种简单而创新的方法来测量纤维增强材料的“表观渗透率”，该方法通过“分布介质”(DM)填充厚度。这种方法将允许执行2D流动模拟(而不是全3D分析)，以通过与DM的“液体树脂注入”(LRI)来制造大型复合材料部件。通过将计算时间减少1000倍，预计将显著提高性能，在核心有凹槽和孔的复杂夹层复合材料的情况下，例如在风叶中发现的情况下，性能改善更大。总体而言，将逐步开发几种创新的数值工具来模拟LCM工艺的关键特征。它们将被用于研究LCM制造日益复杂的部件，目的是为工业提供实用工具。长期目标是利用虚拟制造在工艺开发和扩大规模方面创造高性能复合材料的新应用。最后，根据该项目培训的高素质个人(HQP)将为加拿大公司提供竞争优势。