当前位置: X-MOL 学术Compos. Sci. Technol. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Random field generation of stochastically varying through the thickness permeability of a plain woven fabric
Composites Science and Technology ( IF 9.1 ) Pub Date : 2018-05-01 , DOI: 10.1016/j.compscitech.2018.02.035
Min-young Yun , Pavel Simacek , Christophe Binetruy , Suresh Advani

Abstract In the Vacuum Assisted Resin Transfer Molding (VARTM) process to manufacture composites, woven or stitched fabrics are stacked on top of a tool surface and resin is introduced into this porous network by drawing a vacuum. For large parts, to reduce the time for filling, highly permeable distribution media (DM) is placed on top of the fabric layers to accelerate the in-plane filling process. Many factors such as the manufacturing process, handling, variation in fabric manufacturing and placement of fabric cause heterogeneity in the permeability of fibrous materials. Due to the presence of the DM, the heterogeneous through the thickness permeability (Kpin) of a fabric can dramatically affect the flow of resin and cause air pockets or voids which are mechanical flaws resulting in the rejection of the composite as scrap. Statistical characterization of Kpin is crucial for understanding the (i) effect of heterogeneity in Kpin and its interaction with DM permeability and void formation and (ii) for generating the field of random numbers (Kpin), which can be used for simulations to predict resin flow and void formation for such materials that exhibit stochastic variability. The novelty of this study is that the observed random field (Kpin) is generated for numerical simulation through statistical analysis. First, in this study, the heterogeneity in Kpin was statistically characterized by spatial correlation with Moran's I index and semi-variogram. Then the random field of Kpin was generated by transforming the normal numbers from Karhunen–Loeve (KL) expansion to gamma numbers. A numerical flow simulation of the VARTM process with the generated random fields was performed using Monte Carlo method for three types of Distribution Media (DM). The outcome is compared with experimental results and to simulation results that used experimentally determined Kpin data as an input.

中文翻译:

通过平纹织物的厚度渗透率随机变化的随机场生成

摘要 在制造复合材料的真空辅助树脂传递模塑 (VARTM) 工艺中,将机织或缝合织物堆叠在工具表面的顶部,然后通过抽真空将树脂引入该多孔网络中。对于大型零件,为了减少填充时间,将高渗透性分布介质 (DM) 放置在织物层的顶部,以加速面内填充过程。许多因素,例如制造过程、处理、织物制造的变化和织物的放置,都会导致纤维材料渗透性的不均匀性。由于 DM 的存在,织物的厚度渗透率 (Kpin) 的异质性会显着影响树脂的流动并导致气穴或空隙,这些机械缺陷导致复合材料被视为废料。Kpin 的统计表征对于理解 (i) Kpin 中的非均质性及其与 DM 渗透率和孔隙形成的相互作用以及 (ii) 生成随机数场 (Kpin) 至关重要,可用于模拟预测树脂表现出随机可变性的此类材料的流动和空隙形成。本研究的新颖之处在于通过统计分析生成了观测随机场(Kpin)用于数值模拟。首先,在本研究中,Kpin 的异质性通过与 Moran's I 指数和半变异函数的空间相关性进行统计表征。然后通过将正常数从 Karhunen-Loeve (KL) 扩展转换为伽马数来生成 Kpin 的随机场。使用蒙特卡罗方法对三种类型的分布介质 (DM) 进行了具有生成的随机场的 VARTM 过程的数值流动模拟。将结果与实验结果和使用实验确定的 Kpin 数据作为输入的模拟结果进行比较。
更新日期:2018-05-01
down
wechat
bug