Analysis of vacuum bag resin transfer molding process

An analytical model is developed to analyze the resin flow through a deformable fiber preform during vacuum bag resin transfer molding (VBRTM) process. The force balance between the resin and the fiber preform is used to account for the swelling of fiber preform inside a flexible vacuum bag. Mold filling through multiple resin inlets is analyzed under different vacuum conditions. The formation of dry spots is demonstrated in the presence of residual air. Molding of a three-dimensional ship hull with lateral and longitudinal stiffeners is simulated to demonstrate the applicability of the model.     

Flow sensing and control strategies to address race-tracking disturbances in resin transfer molding. Part I: design and algorithm development

In the resin transfer molding process for advanced polymer composites manufacturing, the fiber preform is placed in the mold cavity and a thermoset resin is injected into the mold to impregnate the stationary preform. The resin displaces the air in the mold through openings called vents. Once the resin emerges out of the vents, the injection is discontinued. The near net-shaped composite part can be demolded after the resin cures. Ideally, the vents should be placed at the locations where the resin arrives last to ensure the complete saturation of the preform. However, the racetracking phenomenon, in which the resin flows faster along the minuscule channels induced by imperfect fits between the preform edges and the mold walls, can dramatically change the resin infiltration process. The ramifications of racetracking are that the resin may arrive at the vents before completely impregnating the preform and create undesired dry spots, which are fiber regions devoid of resin. The racetracking strength is not repeatable and may vary from one injection trial to next. Hence, the online strategic flow control can be useful in improving the processing reliability and the parts quality by re-directing the flow to arrive last at the vents. In this article, an online strategic flow control system consisting of a flow sensing network and a flow actuation network is proposed. A flow pattern recognition technique, which is based on the dimensionless time vector collected by the flow-sensing network, is developed in order to perform the online flow characterization effectively. Flow simulations are utilized to off-line design the flow control system. An evaluation function is formulated to optimize the flow sensing network design. A multi-tier genetic algorithm is implemented to optimize the locations of vents and gates along with the necessary control actions. A numerical case study for testing the computer-generated flow control solutions is presented. It was found that there was significant improvement in the success rate (fewer dry spot regions) due to the use of the strategic flow control and the automated design approach.     

Efficient Permeability Measurement and Numerical Simulation of the Resin Flow in Low Permeability Preform Fabricated by Automated Dry Fiber Placement

We propose a new experimental method using a Hassler cell and air injection to measure the permeability of fiber preform while avoiding a race tracking effect. This method was proven to be particularly efficient to measure very low through-thickness permeability of preform fabricated by automated dry fiber placement. To validate the reliability of the permeability measurement, the experiments of viscous liquid infusion into the preform with or without a distribution medium were performed. The experimental data of flow front advancement was compared with the numerical simulation result using the permeability values obtained by the Hassler cell permeability measurement set-up as well as by the liquid infusion experiments. To address the computational cost issue, the model for the equivalent permeability of distribution medium was employed in the numerical simulation of liquid flow. The new concept using air injection and Hassler cell for the fiber preform permeability measurement was shown to be reliable and efficient.     

A numerical study of filling process through multilayer preforms in resin injection/compression molding

In resin injection/compression molding (RI/CM), a preform often comprises layers of different fiber reinforcements. Each fiber reinforcement has unique through thickness and in-plane permeabilities as well as compressibility, creating a heterogeneous porous medium in the mold cavity. In the present article, numerical simulation is utilized to investigate the filling process of RI/CM in such a heterogeneous porous medium. The filling stage is simulated in a full three-dimensional space by using control volume/finite element method and based upon an appropriate filling algorithm. The flow in the open gap which may be present in the mold cavity is modeled by Darcy’s law using an equivalent permeability. Numerical simulations of filling process for preforms containing two and three layers of different reinforcements in various stacking sequences are conducted with the aid of computer code developed in this study. Results show that the injection time as well as flow front progression depends on fiber types in the whole preform, fiber stacking sequence and open gap provided in the mold cavity. Simulated results also suggest that the presence of open gap at top of reinforcement can lead to both low injection time and uniform flow pattern.     

Development of adaptive injection flow rate and pressure control algorithms for resin transfer molding

To prevent dry spot formation during fabrication of composite parts by Resin Transfer Molding (RTM), a control interface and four different adaptive control algorithms have been developed and tested with numerical simulations. The interface is capable of controlling the flow pattern of resin as it fills a mold containing a preform of fiber reinforcement, provided that the mold is equipped with multiple inlet gates, a single vent and a spinal sensor system that continuously feeds the interface with the resin flow front locations along the spine lines connecting the inlet gates to the vent. Four different adaptive control algorithms targeting on injection flow rate control, injection pressure control, linearly-corrected pressure control, and the combined flow rate and linearly-corrected pressure control have been proposed and incorporated with the control interface. To provide desirable controllability of the filling process and effective utilization of the resin dispensing equipment, the final formulations were optimized by means of numerical simulations of a rectangular RTM part containing different permeability distributions. The results were compared to investigate the strengths and weaknesses of the spinal adaptive control algorithms in terms of dry spot size, filling speed, and the minimum responding speed of injection pump. Finally, a complex geometry case study was conducted to validate and highlight the spinal adaptive control algorithms’ capability in handling flow disturbance for a complex RTM mold filling process which involves irregular mold geometry, multiple inserts, significant permeability and racetracking variations, and non-straight spinal sensors.     

Flow analysis during compression of partially impregnated fiber preform under controlled force

Compression resin transfer molding (CRTM) is an alternative solution to conventional resin transfer molding processes. It offers the capability to produce net shape composites with fast cycle times making it conducive for high volume production. The resin flow during this process can be separated into three phases: (i) metered amount of resin injection into a partially closed mold containing dry fiber preform, (ii) closure of the mold until it is in contact with the fiber preform displacing all the resin into the preform and (iii) further mold closure to the desired thickness of the part compacting the preform and redistributing the resin. Understanding the flow behavior in every phase is imperative for predictive process modeling that guarantees full preform saturation within a given time and under specified force constraints.     

Analysis of non-isothermal mold filling process in resin transfer molding (RTM) and structural reaction injection molding (SRIM)

In this paper, we present a modeling and numerical simulation of a mold filling process in resin transfer molding/structural reaction injection molding utilizing the homogenization method. Conventionally, most of the mold filling analyses have been based on a macroscopic flow model utilizing Darcy's law. While Darcy's law is successful in describing the averaged flow field within the mold cavity packed with a porous fiber preform, it requires experiments to obtain the permeability tensor and is limited to the case of porous fiber preform-it can not be used to model the resin flow through a double porous fiber preform. In the current approach, the actual flow field is considered, to which the homogenization method is applied to obtain the averaged flow model. The advantages of the current approach are: parameters such as the permeability and effective heat conductivity of the impregnanted fiber preform can be calculated; the actual flow field as well as averaged flow field can be obtained; and the resin flow through a double porous fiber preform can be modelled. In the presentation, we first derive the averaged flow model for the resin flow through a porous fiber preform and compare it with that of other methods. Next, we extend the result to the case of double porous fiber preform. An averaged flow model for the resin flow through a double porous fiber preform is derived, and a simulation program is developed which is capable of predicting the flow pattern and temperature distribution in the mold filling process. Finally, an example of a three dimensional part is provided.     

注射条件对LCM工艺非饱和流动特性影响

双尺度多孔纤维预制体填充过程中延迟浸润的非饱和流动现象,对基于树脂流过区域为完全饱和区域的充模理论及模拟方法提出了挑战。通过控制体/有限单元（CV/FE）法结合沉浸函数实现了液体模塑成型工艺（LCM）中非饱和填充浸润的数值模拟,并对比了恒压下的实验结果,验证了其可靠性。分析讨论了注射口压力、流量和液体黏度对双尺度多孔纤维织物非饱和填充浸润特性的影响。结果表明:在允许误差内,该数值模拟结果可靠,可用于分析讨论各因素对双尺度多孔织物非饱和流动特性的影响;填充浸润过程中,纤维织物内部非饱和区域长度并非保持不变,而是随着填充浸润的进行经历了4个变化过程;不同注射条件下,压力、流量及黏度对非饱和流动特性影响不同。研究结果对合理控制注射条件及流体特性实现双尺度多孔纤维预制件的完全浸润具有指导意义。      

基于“离位”增韧技术Z向注射RTM成型的浸润研究

针对"离位"增韧技术和Z-RTM成型技术,引入饱和度参数修正Darcy定律,建立描述树脂在纤维预制件中非稳态流动的偏微分方程,研究恒流注射过程中体积流量、树脂黏度和纤维预制件渗透率等工艺参数对非稳态浸润过程注入压力的影响,模拟树脂在层间未增韧和增韧纤维预制件束内和束间的流动。结果表明:数值模拟结果具有可靠性;随着注射时间的增加,纤维预制件内部各点的压力增加;随着体积流量、树脂黏度的增加,注入压力线性增加,而随着纤维渗透率的增加,注入压力减少,符合Darcy定律;实现了树脂在纤维预制件细微观层次浸润的可视化,这种可视化结果为预测树脂在预制件中的宏观流动提供了重要补充,并为实际工艺提供了一定指导作用。     

RTM工艺注模过程边缘效应模拟分析

RTM工艺需将纤维预制体预置到模具中,由于纤维预制体结构不均匀性和模具形状、尺寸等影响,极易产生边缘效应。边缘效应会严重影响树脂流场发展和压力场分布。本文作者采用等效渗透系数方法模拟边缘效应,得到了其影响下的树脂流动前峰曲线和压力场。研究表明:一方面边缘效应可能导致不期望的树脂流场发展而形成工艺缺陷——干斑;另一方面可以利用边缘效应提高工艺效率:常流率注射时减小合模压力和注射压力,常压力注射时可以减少注模时间。      

z向流动RTM工艺树脂的流动浸润行为

研究了层间“离位”附载多孔薄膜结构形式增韧层的大厚度纤维预成型体中等代流体（树脂）沿预成型体厚度方向（z向）的流动行为,通过压力传感器监测z向流动RTM（z-RTM）工艺注射过程中进、出胶口压力的变化规律,进一步反推树脂在层间“离位”增韧与非增韧预成型体中的宏观流动及微观浸润模式。结果表明,在 z-RTM工艺注射过程中,树脂在沿纤维束间z向快速流动的同时完成对纤维丝束内部的浸润。层间“离位”附载的增韧层虽延缓了树脂的宏观流动,但使流动前锋曲面更加平滑。层间“离位”增韧预成型体z向渗透率为3.5×10^-15m²,与非增韧预成型体的z向渗透率2.9×10^-14m²相比,降低约一个数量级。     

In situ measurement and monitoring of whole-field permeability profile of fiber preform for liquid composite molding processes

For liquid composite molding (LCM) processes, such as resin transfer molding (RTM), the quality of final parts is heavily dependent on the uniformity of the fiber preform. However, the conventional permeability measurement method, which uses liquid (oil or resin) as its working fluid, only measures the average preform permeability in an off-line mode. This method cannot be used to create an in situ permeability profile because of fiber pollution. Further, the conventional method cannot be used to reveal preform's local permeability variations. This paper introduces a new permeability characterization method that uses gas flow to detect and measure preform permeability variations in a closed mold assembly before resin injection. This method is based upon two research findings: (1) resin permeability is highly correlated with air permeability for the same fiber preform with well-controlled gas flow, and (2) the whole-field air permeability profile of a preform can be obtained through measuring the pressure field of gas flow.In this study, first the validity of the gas-assisted, in situ permeability measurement technique was established. Then the technique was demonstrated as effective by qualitatively detecting non-uniformities and permeability variations in fiber performs. Finally, a two-dimensional flow model, based on the finite difference scheme, was developed to quantitatively estimate the whole-field preform permeability profile using predetermined pressure distribution. The efficacy of the new method was illustrated through experimental results.     

Simulation of void formation in liquid composite molding processes

Air entrapment within and between fiber tows during preform permeation in liquid composite molding (LCM) processes leads to undesirable quality in the resulting composite material with defects such as discontinuous material properties, failure zones, and visual flaws. Essential to designing processing conditions for void-free filling is the development of an accurate prediction of local air entrapment locations as the resin permeates the preform. To this end, the study presents a numerical simulation of the infiltrating dual-scale resin flow through the actual architecture of plain weave fibrous preforms accounting for the capillary effects within the fiber bundles. The numerical simulations consider two-dimensional cross sections and full three-dimensional representations of the preform to investigate the relative size and location of entrapped voids for a wide range of flow, preform geometry, and resin material properties. Based on the studies, a generalized paradigm is presented for predicting the void content as a function of the Capillary and Reynolds numbers governing the materials and processing. Optimum conditions for minimizing air entrapment during processing are also presented and discussed.     

Application of the level set method to the simulation of resin transfer molding

A new methodology is presented to simulate mold filling in resin transfer molding (RTM) using a combination of the level set and boundary element methods (BEMs). RTM is a composite manufacturing process where a liquid resin is injected in a closed rigid mold containing a dry fibrous reinforcement. Process simulation is motivated by the importance of tracking accurately the motion of the flow front during the mold filling stage. The BEM solves the equation governing the resin flow and the level set method is implemented to track the resin front in the mold. This formulation opens up new opportunities to improve RTM flow simulations and optimize injection molds. The present paper focuses on isothermal resin flow in undeformable porous medium. The implementation of the numerical algorithm is described and several examples of two-dimensional filling with single or multiple injection gates are presented. The robustness of the coupling and the ability to predict accurately the position of the front by this new model are discussed. It is also shown how dry spot formation can be tracked precisely during the simulation and how a generalization of this approach allows predicting resin flow across obstacles.     

液体模塑成型工艺二维径向非饱和流动数值模拟

通过引入沉浸函数建立了双尺度多孔介质非饱和流动模型,并采用有限元/控制体积法实现了恒压及恒流注射条件下液体模塑成型（LCM）工艺二维径向非饱和流动的数值模拟,得到了不同注射条件下纤维织物内的压力场分布及半饱和区域长度随时间的变化规律,并将双尺度非饱和理论结果与单尺度饱和理论结果进行对比。结果表明：非饱和流动过程中,半饱和区域内的压力和压力梯度明显下降;半饱和区域长度随时间逐渐增加随后保持稳定,当流动前沿到达出口后半饱和区域长度开始逐渐减小;当两个主方向渗透率不同时,沿主方向半饱和区域长度也不同,渗透率越大该方向的半饱和区域长度也越大,纤维织物完全浸润时间取决于较小的渗透率。研究结果对合理预测树脂填充过程中压力分布及纤维预制件的浸润具有指导意义。     

基于VOF/PLIC界面追踪方法的RTM工艺充模过程数值模拟

针对基于Darcy定律的树脂传递模塑(RTM)工艺的充模过程数值模拟的局限性,将纤维预制体内的充填流动作为两相流(树脂相和空气相)处理,在动量方程中考虑了惯性项和粘性项,采用有限体积方法(FVM)离散控制方程,并与VOF/PLIC界面追踪方法相结合,发展了求解树脂在纤维预制体内非稳态流动问题的数值模拟方法.在此基础上开发了RTM工艺的充模过程数值模拟程序,其算例的数值模拟结果与解析解或实验结果吻合良好,验证了此数值模拟方法的有效性和可靠性.     

Numerical simulation of injection/compression liquid composite molding. Part 1. Mesh generation

This paper presents a numerical simulation of injection/compression liquid composite molding, where the fiber preform is compressed to a desired degree after an initial charge of resin has been injected into the mold. Due to the possibility of an initial gap at the top of the preform and out-of-plane heterogeneity in the multi-layered fiber preform, a full three-dimensional (3D) flow simulation is essential. We propose an algorithm to generate a suitable 3D finite element mesh, starting from a two-dimensional shell mesh representing the geometry of the mold cavity. Since different layers of the preform have different compressibilities, and since properties such as permeability are a strong function of the degree of compression, a simultaneous prediction of preform compression along with the resin flow is necessary for accurate mold-filling simulation. The algorithm creates a coarser mechanical mesh to simulate compression of the preform, and a finer flow mesh to simulate the motion of the resin in the preform and gap. Lines connected to the top and bottom plates of the mold, called spines, are used as conduits for the nodes. A method to generate a surface parallel to a given surface, thereby maintaining the thickness of the intermediate space, is used to construct the layers of the preform in the mechanical mesh. The mechanical mesh is further subdivided along the spines to create the flow mesh. Examples of the three-dimensional meshes generated by the algorithm are presented.     

Modeling the impact of capillary pressure and air entrapment on fiber tow saturation during resin infusion in LCM

Traditionally, capillary effects have been neglected when modeling the filling stage of Liquid Composite Molding processes. This simplification is justified because the inlet resin pressures are much higher than the capillary pressure. This simplification is also acceptable when impregnating fabrics in which their fiber tows saturate at the same rate as the bulk preform. However, this assumption is questionable for fabrics that exhibit dual scale in which the fiber tows saturate at a much slower rate than the bulk preform. In such cases, the capillary pressure can influence the time to saturate a fiber tow significantly and impact the overall impregnation dynamics. Since the flow front velocity inside the fiber tows is significantly smaller than the flow around them, it is important to include the capillary pressure that may aid the saturation of the tow. In this paper, we modify our existing simulation that can predict the filling of the bulk preform and the saturation of the fiber tows to include the capillary forces at the fiber tow level. Important parameters are identified and grouped in non-dimensional form. A parametric study is conducted to examine the role of these dimensionless parameters on the overall tow saturation levels. The modeling is extended to include the effect of entrapped air inside the tows on the overall saturation of the preform. An experimental technique using the optical properties of vinyl ester and glass fiber was used to qualitatively validate the proposed model.     

Resin flow analysis with fiber preform deformation in through thickness direction during Compression Resin Transfer Molding

Resin flow during Compression Resin Transfer Molding (CRTM) can be best described and analyzed in three phases. In the first phase, a gap is created by holding the upper mold platen parallel to the preform surface at a fixed distance from it. The desired amount of resin injected into the gap quickly flows primarily over the preform. The second phase initiates when the injection is discontinued and the upper mold platen moves down squeezing the resin into the deforming preform until the mold surface comes in contact with the preform. Further mold closure during the final phase will compact the preform to the desired thickness and redistribute the resin to fill all empty spaces. This paper describes the second phase of the infusion. We assume that at the end of phase one; there is a uniform resin layer that covers the entire preform surface. This constrains the resin to flow in through the thickness direction during the second phase. We model this through the thickness flow as the load on the upper mold forces the resin into the preform, simultaneously compacting the preform. The constitutive equations describing the compaction of the fabric as well as its permeability are included in the analysis. A numerical solution predicting the flow front progression and the deformation is developed and experimentally verified. Non-dimensional analysis is carried out and the role of important non-dimensional parameters is investigated to identify their correlations for process optimization.     

On-line strategic control of liquid composite mould filling process

Liquid composite moulding (LCM) processes are used to manufacture high quality and complex-shaped fibre reinforced polymeric composite parts in the aerospace, automotive, marine and civil industries. A thermoset resin is injected into a mould cavity filled with a reinforcing fibrous preform. The composite part is demoulded after the filling is completed and resin has cured. During prototype development, the design engineers may combine their manufacturing experience with simulations to decide which LCM process must be used for the selected part. For complicated mould shapes, the manufacturing engineer has to make decisions about injection pressure, flow rate, location of gates and vents, etc. to achieve a high-quality composite part which is free of dry spots. Inherent variability in the process and the possible errors in characterization of material properties, such as fibre volume fraction and permeability, challenge the manufacturing engineer to reduce the number of unacceptable parts. An on-line strategic controller with in situ sensor data can influence the flow front pattern during mould filling and drive the process towards successful completion. Some of these variabilities are considered in off-line mould filling simulations. By analysing the simulation results, the sensors are placed inside the mould to identify the variabilities and take corrective action(s) to eliminate voids. Sensor data and the control actions are cast in the form of a decision tree. Data acquisition software collects the in situ sensor data and implements the control actions from this decision tree. A case study was included in which various race-tracking and bulk permeability variations can be expected during manufacturing. The proposed controller is described in detail for this selected case study and its usefulness is verified with experiments.