Experimental and numerical simulation of permeability variation induced by nesting effect in resin transfer molding
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摘要: 树脂传递模塑成型工艺(RTM)中最重要的变形模式之一是厚度方向压缩。厚度方向压缩减小了织物预成型体的厚度，使织物预成型体局部结构形式发生改变从而引起嵌套效应。嵌套效应不仅会减少织物预成型体的厚度，增加纤维的体积分数并改变孔隙率，而且相邻织物层嵌套效应具有一定的空间分散性，从而使得织物预成型体渗透率具有变异性。本文针对低黏度树脂设计了一种实验装置用以测量局部渗透率的空间分散性，随后建立了随机嵌套单胞模型，利用ANSYS/CFX有限元软件实现了单胞填充浸润的数值模拟，通过流量分析获得局部渗透率，并研究了渗透率的统计分布。通过实验结果与数值模拟结果相对比，验证数值模拟结果的可靠性。最后，基于渗透率的统计分布建立了随机渗透率场，并进行填充浸润的数值模拟，通过与传统恒定渗透率的方法进行比较，证明该方法具有更高的先进性。研究结果可以对未来RTM工艺的稳健性优化提供依据。
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关键词:
- 树脂传递模塑成型工艺(RTM) /
- 嵌套 /
- 渗透率变异性 /
- 压缩 /
- 数值模拟
Abstract: One of the most important deformation modes in resin transfer molding (RTM) of manufacturing processes is compression along thickness direction, which reduces the thickness of the textile preform and causes the change of the fabric structure, causing the nesting effect. Nesting reduces the laminate thickness, increases the fibre volume fraction, and changes the porosity pattern. The effect of adjacent fabric layer nesting has a certain spatial dispersion. This makes the fabric permeability variable. In this work, an experimental device was designed to measure the spatial dispersion of local permeability for low viscosity resins. Then, a random nested monocyte model was established, ANSYS/CFX finite element software was used to realize the numerical simulation of single cell, and the local permeability was obtained by flow analysis. The statistical distribution of permeability was then studied. The experimental results were compared with the numerical simulation results. The reliability of the numerical simulation results was verified. Finally, the random permeability field was established based on the statistical distribution of permeability, and the numerical simulation of resin filling was carried out. The results show that this method is more advanced than traditional method based on constant permeability. The results can provide a basis for the robustness optimization of RTM process in the future.-
Key words:
- liquid composite molding (RTM) /
- nested /
- permeability variability /
- compression /
- numerical simulation
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图 3 多层织物平均每层厚度与压力曲线
Figure 3. Average thickness of multilayer fabric per layer and pressure curves
图 4 多层织物纤维体积分数与压力曲线
Figure 4. Volume fraction and pressure curves of multilayer fabric fibers
图 9 两层纤维织物单胞模型计算云图
Figure 9. Unit-cell model computes the cloud image of two layers fabric
图 10 两层织物实验与仿真值渗透率及其分布
Figure 10. Experimental and simulated values of permeability and distribution of two-layer fabric
图 11 多层织物实验流动图像和数值模拟填充浸润图像
Figure 11. Experimental flow diagram of multi-layer fabric and numerical simulation of filling and infiltration diagram
图 12 两层传统数值模拟填充浸润图像
Figure 12. Two layers of traditional numerical simulation of filling infiltration map
图 13 不同时刻下双层织物填充浸润模拟与实验流动前沿进程
Figure 13. Simulation and experimental flow front process of two layers at different times
图 14 双层织物模拟与实验入口压力曲线
Figure 14. Simulation and experiment inlet pressure curve of two layers
表 1 平纹玻璃纤维织物的初始参数
Table 1. Initial parameters of plain glass fabric
Parameter Value Areal density/(kg·m−2) 0.731 Porosity of fabric 0.67 
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表 2 两层织物实验与仿真渗透率分布基本参数
Table 2. Experiment and simulation of permeability distribution of two-layer fabric
Parameter Average value/
10−10 m2Standard deviation/
10−10 m2Way Kx 4.43 1.12 Experiment Ky 4.31 1.06 Experiment Kx 4.24 0.97 Simulation Ky 4.17 0.91 Simulation Notes: Kx—Permeability in x direction; Ky—Permeability in y direction.
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表 3 多层织物实验渗透率分布基本参数
Table 3. Basic parameters of permeability distribution of multilayer fabrics
Parameter Average value/
10−10 m2Standard deviation/
10−10 m2Layer
numberKx 4.43 1.12 2 Ky 4.31 1.06 2 Kx 4.05 0.94 4 Ky 4.14 0.92 4 Kx 3.92 0.85 6 Ky 3.97 0.83 6
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