Zeitschrift Kunststofftechnik Journal of Plastics … Kunststofftechnik / Journal of Plastics

4Autor Titel (gegebenenfalls gekürzt)

© Carl Hanser Verlag Zeitschrift Kunststofftechnik / Journal of Plastics Technology 12 (2016) 3

x(20xx) x

eingereicht/handed in: 15.09.2015 angenommen/accepted: 10.03.2016

Dipl.- Ing Dino Magagnato, Prof. Dr.-Ing Frank Henning Institut für Fahrzeugsystemtechnik, Karlsruher Institut für Technologie (KIT)

RTM molding simulation for unidirectional fiber reinforced composite components considering local fiber orientation and fiber volume fraction

Mold filling simulations provide efficient methods to reduce the cycle times at resin transfer molding (RTM) by an optimized injection strategy. However, for a realistic modelling, it is necessary to consid-er the local fiber orientation and fiber volume fraction resulting from the draping process. This is pos-sible by using a virtual process chain with different computer aided engineering (CAE) software. In this work an experimental method (microwave incineration) assists the CAE chain and so a more de-tailed consideration of the local fiber structure is possible. The present paper works out the ad-vantages of using these methods for the molding simulation of a complexly shaped composite part. This approach competes with a state of the art model by comparing both models with experimental pressure measurements.

RTM Formfüllsimulation für unidirektional ver-stärkte Faserverbundbauteile unter Berück-sichtigung der lokalen Faserorientierung und des Faservolumengehalts

Mithilfe von Formfüllsimulationen können effiziente Methoden zur Verfügung gestellt werden, die da-bei helfen, die Taktzeiten beim RTM-Prozess durch eine optimierte Angussstrategie zu reduzieren. Jedoch muss für eine realitätsgetreue Modellierung die lokale Faserstruktur nach dem Drapierprozess berücksichtigt werden. Dies ist durch die Verwendung einer virtuelle Prozesskette und geeigneter CAE-Software möglich. In dieser Arbeit wird die CAE-Kette von einer experimentellen Methode (Mik-rowellenveraschung) unterstützt. Dadurch konnte die lokale Faserstruktur detaillierter berücksichtigt werden. In dieser Studie werden die Vorzüge der Verwendung dieser Methoden für die Formfüllsimu-lation eines komplex geformten Bauteils aus Faserverbundwerkstoffen vorgestellt. Dieser Ansatz wird mit einem Referenzmodell evaluiert, indem beide Modelle mit experimentell ermittelten Druckmess-kurven validiert werden.

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Journal of Plastics Technology 12 (2016) 3 136

Magagnato, Henning RTM simulation for UD reinforced composites

RTM molding simulation for unidirectional fiber reinforced composite components considering local fiber orientation and fiber volume fraction

D. Magagnato, F. Henning

1 INTRODUCTION

Fiber reinforced composite components are increasingly used in the industry because of their low density combined with good mechanical properties. How-ever the economic production of composite parts in higher quantities is still a big challenge, due to high material and production costs coupled with a low degree of automation. In the industry, various production methods exist for structural composite parts. Because of its high automation possibilities, resin transfer molding (RTM) offers great conditions for mass production of high performance composite structures. To observe the economic boundary, the manufacturing process needs more stability and reduced cycle times. Therefore an important step is to optimize the molding process itself. Simulation software supports the development of the RTM process by substituting time-consuming and cost-intensive real test method [1-3]. For that, it is necessary to ensure the validity of the simulation. A significant precondition for a sufficient simulation is the inte-grated modelling of the entire RTM process chain, where all important process parameters and process results are transferred between the single simulation steps [4-7]. For woven fabrics the interface between draping simulation and molding simulation is already state of the art. For that purpose, Bickerton [8-10] applied a kinematic drape model in combination with different simple curvature models. Louis and Huber [11] extend this approach by the use of homogeneous FE models [12] for the draping simulation. For woven fabrics, the local fiber vol-ume fraction (fvf) can be estimated by using the local shear angle (angle be-tween weft and warp-direction) with the following correlation, as discussed in [13-14]:

𝑓𝑣𝑓𝛼 =𝑓𝑣𝑓

cos 𝛼 (1)

However for non-crimp-fabrics like unidirectional fabrics (UD) no shear angle can be defined and the estimation of the local fiber volume fraction cannot be applied here. Furthermore the draping simulation requires considerably higher efforts because with the absence of woven nodes a higher degree of freedom arises. This result in a different forming behaviour compared to woven fabrics, which cannot be predicted as precisely by homogenised material models [15]. Therefore mesoscopic models for draping simulation are implemented in the last years to solve that issue [16-17].

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This work deals with the mold filling simulation of a complex formed composite part. The setup of the simulation model is already presented by Magagnato [18]. To transfer the local fiber orientation from a mesoscopic drape simulation to the mold filling simulation a special interface, using Computer Aided Engineering (CAE) methods, is used [5]. Until now this CAE interface is still not able to pro-vide the local fiber volume fraction directly from the draping simulation [6]. So an experimental method to determine local fiber volume fractions in the part is in the focus of this work.

Furthermore the present paper works out the influence of different laminate layups to the RTM molding behaviour. A detailed validation of the different simulation models with experimental measurements is presented exclusive in this work. Therefore six pressure sensors are integrated in the RTM tool trace the flow front during the molding process.

2 FLUID MECHANICS AND MATERIALS

The mold filling process at RTM is an unsaturated flow through porous media and can be modelled by Darcy's law [19]:

𝒗 = − 𝑲

𝜂(𝛻𝒑) (2)

where 𝒗 is the volume-average velocity [m/s] and 𝒑 is the pressure field [Pa] in the cavity. Relevant material parameters are the dynamic viscosity, η [Pas], of the resin and the permeability, K [m²], of the fiber preform. The permeability shows anisotropic behavior and is defined by a second order tensor. In the prin-cipal coordinate system, the three principal permeabilities can be identified as K1, K2 and K3. The direction with the highest in-plane permeability value is K1. K2 is the direction with the lowest in-plane permeability. For unidirectional fab-rics K1 is parallel to the fibers bundles and K2 is perpendicular to fiber direction. Until now, there is yet no standard norm for the experimental determination of the in-plane permeability [21, 22].

In this study an innovative setup [23] is used to measure the preform permeabil-ity. This setup enables a process-oriented determination directly during RTM manufacturing. Figure 1 shows the results of permeability measurements for the used unidirectional fabric (producer: SAERTEX GmbH & Co. KG, area weight: 330 g/m², fiber: Toray T620, fiber density ρf: 1800 kg/m³). The permeability of the fabric strongly depends on fiber orientation and fiber volume fraction.

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Figure 1: Permeability depending on fiber volume fraction

Reproduced from [23], Copyright © 2015 Trans Tech Publications Ltd

The influence of the through-plane permeability, K3, can usually be neglected because of relative small thicknesses of composite parts compared to other di-mensions [20]. For unidirectional fabrics, K3 should be in the same order of magnitude as K2.

The used matrix material for the production of the RTM components is an epoxy resin (type: CR170+CH 105-3, density ρm: 1100 kg/m³)) of the company Sika GmbH. The viscosity of epoxy resin is a function of temperature and curing de-gree. For the experimental validation of the simulation, a non-reactive test fluid called Mesamoll with a nearly constant viscosity of 100 mPas at room tempera-ture is used instead of resin to minimize strong variations of the viscosity.

When Darcy´s law is combined with equation of continuity:

𝛻 𝒗 = 0 (3)

A second order partial differential equation is obtained:

0 = 𝛻 (𝑲

𝜂𝛻𝒑) (4)

This equation can be solved by using numerical methods like finite difference, finite element, finite volume or spectral methods.

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3 VIRTUAL PROCESS CHAIN FOR RTM PARTS

The RTM process comprises different manufacturing steps. First, the fabric is tailored and draped to a dry fiber preform. Then the preform is placed into a heated RTM mold and subsequently a reactive resin (e.g. epoxy resin, polyure-thane) is injected. Finally the cured composite component can be de-molded. A virtual process chain (CAE chain) models each process step by using different simulation software packages.

The simulation steps are connected with each other by data flows, which are illustrated by green arrows in Figure 2 and which comprise the transfer of im-portant composite data. If simulation results suggest a change of the design (e.g. due to insufficient feasibility or due to bad structural performance, see red arrows), and the CAE chain starts again. [4-6]

Figure 2: CAE chain for resin transfer molding [4-6]

For the exchange of data between the different simulation software packages a universal data format (vtk) is used. Different command line scripts ensure the type conversion from the software specific data formats to the vtk format [4]. In this work, the transformation scripts for draping simulation (LS-DYNA) and molding simulation (PAM-RTM) are applied. Because different mesh types are used in LS-DYNA and PAM-RTM, the local fiber data has to be transferred from a source mesh (draping simulation) to a target mesh for the molding simulation. Consequently, beside the geometry and the layup that comes directly from the design, the molding simulation receives local information in terms of fiber orien-tation from the draping simulation. The detailed procedure to transfer the local fiber orientation between the difference simulation steps is explained in prelimi-nary work of Kärger et al. [5]. For that purpose the mapping library MpCCI MapLib [24] from Fraunhofer SCAI is used.

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Additionally the molding simulation should get information of local fiber volume fraction and voids. For unidirectional textiles first approaches exist for that pur-pose, but unless draping simulation is not capable to reliably predict both the distance between fiber rovings and the ply thickness after preforming process, it is yet not implemented in the CAE chain [6]. So in this paper the method of mi-crowave incineration assists the CAE chain with local measurements of the fiber volume fraction.

4 RTM MANUFACTURING OF A CC COMPONENT

4.1 Geometry

Within the project “Technology Cluster Composites Baden-Wuerttemberg (TC²)”, a convex-concave (CC) component is designed for the demonstration of the virtual process chain. The CC component represents the big challenges in complexly shaped automotive parts, such as double curved corners and 90° direction changes. To compensate local accumulation of fibers in the preform, different component thicknesses (from 2.7 mm to 6 mm) are used, see Figure 3.

Figure 3: CAD-model of the convex-concave (CC) component

4.2 Experimental setup

For the CC component, an RTM tool was constructed in collaboration with the company Pelz Technik GmbH. The tool was taken into service at the produc-tion-technique laboratory of the KIT. Figure 4 depicts the manufacturing steps for the CC component. First, the preform is draped on the bottom mold half (a, b). Then, the eight parts of the upper mold half are assembled carefully (b, c).

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The upper mold half consists of several parts to prevent a possible shearing of the fibers during assembly. To reach the required counter pressure against the injection pressure, the tool is compressed with a hydraulic press up to 4000 kN. After curing of the reactive epoxy resin, the finished component can be de-molded (d).

Figure 4: Manufacturing of the convex-concave component at KIT

For the infiltration of the preform, the epoxy resin CR170 of the company Sika GmbH is appointed. The CC component is produced in different layups, shown in table 1.

Nomenclature Fiber orientation Number of layers

Layup

CC_0° Unidirectional 0° 8 [0°]8

CC_90° Unidirectional 90° 8 [0°]8

CC_QI Quasiisotropic 8 [0°, 90°,+45°, -45°, -45°,+45°,90°, 0°]

Table 1: Different laminate layups of the CC component

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To record the pressure history and to determine the dispersal behavior of the resin experimentally, six sensors are installed inside the cavity of the RTM tool. Figure 5 shows the local placement of the integrated sensors.

Figure 5: Positioning of the six pressure sensors in the RTM cavity

For experimental validation of the molding simulation the CC preform is infiltrat-ed with the test fluid Mesamoll at room temperature. In this way, a constant vis-cosity can be assumed, and the focus of the examination is exclusive on the fiber structure.

5 MOLD FILLING SIMULATION

5.1 Setup of the simulation model

The software PAM-RTM is used to setup the model for the molding simulation. The RTM mold filling is modelled in PAM-RTM as incompressible flow through porous media and is calculated by Darcy´s law and the equation of continuity. PAM-RTM uses a finite element/ control volume approach [25] for the calcula-tion of the pressure distribution.

Therefore non-conforming finite elements are applied. This kind of elements ensures that the flow rates remain continuous on the inter-element boundary, thus respecting integrally the physical condition for mass conservation of the matrix flow. [26]

Figure 6 shows the finite element (FE) mesh for the CC component. A subdivid-ed channel in the middle corridor of the component (see red points in Figure 6) is used as sprue. The test fluid is injected with a constant pressure difference of 4 bars. The vents are located in the four outer corners (see blue points in Figure 6) of the CC component. The injection and venting strategy was determined before with a simplified simulation model.

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Figure 6: FE mesh with injection (red) and vent strategy (blue)

5.2 Import of local fiber orientation and fiber volume frac-tion

Figure 1 identifies the influence of the fiber orientation and the fiber volume frac-tion on the preform permeability. Because of that it is recommended to transfer these local fiber data from draping simulation to the molding simulation. In this study the ITV Denkendorf performed the draping simulation of the CC compo-nent using a 2,5D- mesoscale approach. Figure 6 shows a virtually draped layer (unidirectional, 90°) of the CC preform. Finite shell elements, which are ar-ranged as stripes, model the single fiber rovings here. Each element deposits a vector with the local fiber orientation, see Figure 7 (zoomed area). Totally eight of those meshes are delivered by the draping simulation, each representing a single layer (compare table 1). The interaction of the different layers during the preform process is considered in the simulation.

Figure 7: Results of the draping simulation of the top layer of the 90° layup

[Draping simulation: ITV Denkendorf]

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For the molding simulation a continuous volume mesh (3D), cf. Figure 8, is more suitable. In thickness direction the mesh is composed of eight elements representing the eight layers. The transfer of the local fiber orientations from the 2,5D draping mesh to the 3D mesh for the molding simulation the method pre-sented in the preliminary work of Kaerger et al. [5] is used. Each element layer of the molding simulation is mapped with the corresponding layer of the draping simulation.

Figure 8: Mapped fiber orientations in the molding mesh (90° layup)

Figure 9 shows a magnified section of the molding mesh, where on the right hand side the fiber orientations are imported from the draping simulation (“CAE model“). Additionally a reference model is created, where the global fiber orien-tation of each layer is projected on the component’s surface, see Figure 9 on the left side. This method is a simple approach to model the fiber orientation, if no draping simulation results are obtainable. By comparing both models in Fig-ure 9, big differences between the two models can be identified in the approxi-mation of the local fiber orientation, especially in the curved areas. In these are-as the reference method is not able to model a flowing transition of the fiber ori-entation, like the way the CAE model do.

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Figure 9: Comparison between the two fiber orientation models: reference model (left) and CAE model (right), the small dashes show the fiber direction (90° layup) in each element

As discussed in Figure 1, the fiber volume fraction is, beside the fiber orienta-tion, a key factor for the preform permeability. Local changes in fiber volume fraction occur because of two reasons: first, because of local variations of the cavity thickness (cf. Figure 3), and secondly, because of local fiber accumula-tions, which result from the preforming process. For unidirectional textiles, cur-rently no robust method exists to determine the local fiber accumulations direct-ly in the draping simulation. The draping simulation is not yet capable to reliably predict both the distance between fiber bundles and the ply thickness. Due to that, the local fiber volume fraction is determined with an experimental proce-dure in this study. Therefore, 18 probes of the cured CC component are cut out with a dremel and the respective fiber volume fraction is analyzed with a micro-wave incinerator of the company CEM (model: Phoenix Standard Unit, max. microwave power: 1400 watts). During this method the matrix material is melted out of the probe. Then the weight of the fibers (mf) and matrix (mm) can be measured. The fiber volume fraction is calculated with equation 3:

𝑓𝑣𝑓 =

𝑚𝑓

𝜌𝑓𝑚𝑓

𝜌𝑓+

𝑚𝑚𝜌𝑚

(3)

As illustrated in Figure 10, there are significant variations in the local fiber vol-ume fraction over the component.

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Furthermore, the measurements show that the choice of laminate layup change the local distribution of fiber accumulations during the preform process, and subsequently the fiber volume fraction.

Figure 10: Determination of loc. fiber volume fraction via microwave incineration

For consideration of the local fiber volume fractions in the CAE model, the vol-ume mesh is subdivided into 18 zones, see Figure 11. In these zones the re-spective values of the experimental determination are assigned.

In contrast, the reference model assumes an average fiber volume fraction. The average value is calculated by using the known preform weight, the fiber and matrix density and the cavity volume.

Figure 11: Distribution of the CC component in zones with different fvf

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5.3 Molding simulation results, validation and discussion

For the molding simulation the material and process parameters are imple-mented in the simulation model, as discussed in chapter 2 and 5.1. Furthermore the injection and ventilation strategy is adapted from the experiment (cf. Figure 6). As illustrated in section 5.2, a reference and a CAE model are created for the different layups. To obtain a better overview, the different simulation models are compiled in table 2.

Simulation Model

Fiber orientation Fiber volume fraction

Layup

CC_QI_FS_global Globally defined (projection method)

Constant 47 % Quasi-isotropic

CC_QI_FS_local Locally defined (draping simulation)

Locally determined (microwave incineration)

Quasi-isotropic

CC_UD_0_FS_global

Globally defined (projection method)

Constant 47 % Unidirectional 0°

CC_UD_0_FS_local

Locally defined (draping simulation)


Unidirectional 0°

CC_UD_90_FS_global

Globally defined (projection method)

Constant 46 % Unidirectional 90°

CC_UD_90_FS_local

Locally defined (draping simulation)


Unidirectional 90°

Table 2: Different models for molding simulation of the CC component

To illustrate the influence of the laminate layup and fiber structure, the flow fronts at an injection time of 15 seconds are compared in Figure 12. For the quasi-isotropic layup the flow front moves with the same velocity in every direc-tion. For the two unidirectional layups the flow spreads out quickly in fiber direc-tion. Perpendicular to fiber direction the flow spreads out slowly. By considering of local fiber structure in the CAE models the flow front is changing substantially compared to the reference models.

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Figure 12: Comparison of the flow front 15 seconds after injection start for dif-ferent simulation models, compare Tab.3

a) CC_QI_FS_global, b) CC_QI_FS_local, c) CC_UD_0_FS_global, d) CC_UD_0_FS_local, e) CC_UD_90_FS_global, f) CC_UD_90_FS_local

For validation of the simulation results, experimentally measured pressure curves, recorded by integrated sensors cf. Figure 5, are compared against the pressure curves of virtually created sensors in the simulation.

In Figure 13 the pressure curves of the quasi-isotopic layup are plotted in one diagram. For the reference model, the agreement with experiment is good for the three sensors close to the injection channel (sensors 1, 2 and 3). For the sensors 4-6, which are located far from injection channel, the agreement is sig-nificantly worse. For the CAE model, a good agreement between simulation and experiment can be identified for all the sensors. It can be concluded, that the consideration of the local fiber structure is worth in this case.

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Figure 13: Comparison of pressure curves for the quasi-isotropic laminate, see Figure 6 for the positions of the sensors 1-6

Figure 14 shows the pressure curves for the unidirectional layup with a pre-ferred orientation of 0°. Here the molding behavior is different. According to the 0° layup, the flow spreads out very fast parallel to the injection channel. So sen-sor 6, for example, is reached very quickly, whereas sensors 4 and 5 are cap-tured by the flow front only after 100 seconds. Like in the case of the quasi-isotropic layup, the prediction quality is better for the CAE model, which consid-ers the local fiber structure.

Figure 14: Comparison of pressure curves for the 0° unidirectional laminate

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Figure 15 compares the pressure curves for the unidirectional laminate with a 90° layup. Here the flow has a big resistance parallel to the injection channel. So in this case, sensor 6 does not measure a rise of pressure, which implies that this sensor is not reached at all. Perpendicular to the injection channel the flow increases rapidly, whereupon the sensors 4 and 5 are reached in a relative short time. Like for the two other layups, the prediction quality of the simulation improves, if the local structure of the fibers is regarded in the simulation model.

Figure 15: Comparison of pressure curves for the 90° unidirectional laminate

6 SUMMARY AND CONCLUSIONS

In the present work, the RTM molding process for a complexly shaped compo-site component is investigated numerically and experimentally. Due to the pre-forming process, local inhomogeneities of fiber orientation and fiber volume fraction arise in the component. With the help of a CAE-chain the local fiber ori-entation is transferred layer by layer from the draping simulation to the molding simulation. The local fiber volume fraction is determined experimentally with the method of microwave incineration. By comparison of simulation and experi-mental data, a better prediction quality of the simulation is reached, by consider-ing local fiber structure in the simulation model. Generally a reasonable agree-ment between simulation and experiment can be identified, if local fiber struc-ture is considered after the preforming process. The results also show that the approach to model the permeability layer by layer seems to be acceptable for unidirectional fabrics. Furthermore the influence of different laminate layups to draping and flow behavior is discussed in this work.

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The results of the microwave incineration show that the laminate layup has a massive influence on the distribution of the local fiber volume fraction in the component. Subsequently this results in different flow behavior during the mold-ing process.

In future research further validation of this simulation approach on other parts is planned. Furthermore the local fiber volume fraction should be included directly from draping simulation, to consider this information already in the preceding design and dimensioning process.

7 ACKNOWLEGDEMENTS

The presented work has been performed as part of the R&D activities in the framework of the “Technology Cluster Composites Baden-Wuerttemberg TC²”. The title of the involved research project is “RTM CAE/CAx – Establishment of a continuous CAE/CAx chain for the RTM technology, against the background of manufacturing high-performance composite materials”. This project is funded by the state government of Baden-Wuerttemberg in Germany and the Baden-Wuerttemberg Stiftung GmbH. The authors are grateful to the ITV Denkendorf for providing the results of the draping simulation for the CC component. The authors also like to thank Fraunhofer SCAI for freely providing MpCCI MapLib and for supporting the research activities in terms of mapping. Furthermore, the help of the student assistant Lukas Ast is gratefully acknowledged. Parts of this work were presented at the 20th International Conference on Composite Mate-rials (ICCM20) in July 19-24th 2015.

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Keywords: Resin transfer molding (RTM), Simulation, Mold filling, CAE chain, fiber struc-ture

Stichworte: Resin transfer molding (RTM), Simulation, Formfüllung, CAE Kette, Faserstruk-tur

Autor/author:

Dipl.-Ing. Dino Magagnato Prof. Dr.-Ing. Frank Henning Karlsruher Institut für Technologie Institut für Fahrzeugsystemtechnik Lehrstuhl für Leichtbautechnologie Rintheimer Querallee 2 76131 Karlsruhe

E-Mail-Adresse: [email protected] Webseite: http://www.fast.kit.edu/lbt/ Tel.: +49 (0)721/608-45384 Fax: +49 (0) 721/608-945905

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Europa/Europe Prof. Dr.-Ing. Dr. h.c. Gottfried W. Ehrenstein, verantwortlich Lehrstuhl für Kunststofftechnik Universität Erlangen-Nürnberg Am Weichselgarten 9 91058 Erlangen Deutschland Phone: +49 (0)9131/85 - 29703 Fax.: +49 (0)9131/85 - 29709 E-Mail-Adresse: [email protected]

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Dr.-Ing. Eva Bittmann Dipl-Ing. Susanne Messingschlager, [email protected] Beirat / Advisory Board:

38 experts from science and industry listed at www.plasticseng.com

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Zeitschrift Kunststofftechnik Journal of Plastics … Kunststofftechnik / Journal of Plastics