OPTIMIZING PROCESS CONDITION OF RESIN TRANSFER MOLDING: DETERMINING MATERIAL PROPERTIES FOR NUMERICAL SIMULATION

C-W. Wang 1, C-T. Heng2, L-J. Bin2, S-P. Sun1, C-H. Hsu1, Y. Yao2, and R-Y Chang1

1CoreTech System (Moldex3D) Co., Ltd., Chupei City, Hsinchu, Taiwan 2Department of Chemical Engineering, National Tsing-Hua University, Hsinchu, Taiwan 30043, R.O.C.

Abstract

Herein, we present the recent development in

permeability measurement by an optical visualization

method. We applied this technique to investigate materials

commonly used in wind turbine industry, such as different

types of fiber mats, distribution medium, PVC core

material. Wind turbine industry utilizes predominately

resin transfer molding (RTM) process to manufacture the

components. The traditional-trail-error method in this case

is not practical due to the high cost of producing the

components. To the best of our knowledge, this is the first

example of using an optical method in conjunction with a

simulation tool to obtain out of plane (K33) permeability.

The results demonstrate the promising potential of

permeability measurement by the optical visualization

method, and great relevance to industrially important

processes such as RTM. The measured material properties

are then used in process simulation to obtain optimal

process conditions of RTM.

Introduction Demand for improved part performance has led to

efforts to produce products that are lighter, stronger, and

more efficient. In the last decade or so, FRP (fiber

reinforced plastic) due to their superior mechanical

performance and light weight characteristics have been

widely used in variety of applications ranging from 3C

products, automotives, shipbuilding, aerospace and wind

energy [1-2]. FRP are not a new class of materials, but

recent advancements have dramatically improved them

and given greater range to their properties. Improvements

in the matrix chemistry have allowed composites to move

into harsher environments. For example, some polyimides

can be use up to temperature range of 260-300C [2]. As

well, changes in reinforcement types and configuration

have yielded improved strength and processing

characteristics. Reinforcements in FRP can range from

short/long fibers, mats, directional fabrics, and braided

structures which allow them versatile for different

processes.

The Resin Transfer Molding (RTM) is one of the

most promising technology available today. It belongs to

one of the liquid composites molding (LCM) process. The

RTM process is used in many applications since it is

capable of making large complex three-dimensional part

with high mechanical performance, tight dimensional

tolerance and high surface finish. Furthermore, RTM is

one of the most efficient and economical process due to

its capabilities such as non-expensive process equipment,

closed mold process, low filling pressures, excellent

control on mechanical properties, incorporation of metal

inserts and attachments, possibility of producing large and

complex parts and low labor costs [3-5].

Wind energy has become an indispensable player in

the worldwide energy production and will play an

ever-increasing role in the 21st century energy market.

Vacuum Assisted Resin Transfer Molding (VARTM) has

replaced the traditional Hand layer-up method used in

producing composite wind turbine blades as the more

superior process method as it eliminates process variables

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such as pressure and speed at which the operator applies

the resin. However, there are still challenges facing

VARTM. For example, it is difficult to accurately predict

the resin flow because of locally high fiber volume in

certain regions can drastically change mold fill behavior.

As such, RTM operators cannot accurately anticipate

these effects, nor can they visually verify whether the part

has reached full saturation before injection process is shut

down. If the part is not 100% impregnated, defects such

as dry spots or voids are introduced, and the part must be

discarded and changes made to the injection geometry

until all dry spots are eliminated. Applying this

trial-and-error methodology to the resin transfer molding

of large structures, i.e. utility grade turbine blades, would

be expensive. However, through successful simulation of

RTM flow, it is possible to predict the flow properties in a

complex structure and eliminate the trail-and-error

approach [6-7].

The traditional measurement of permeability is to

measure the filling behavior by using sensor nodes to

detect melt front time and then use this data to fit out the

permeability. However, the presence of sensor nodes

might interfere with the melt front, leading the inaccurate

melt front data. In this study, we build a robust

visualization system which could improve the accuracy of

the measurements of the permeability. We study different

types of fiber mats and core materials that are common in

wind turbine manufacturing. Currently RTM simulation

software is still very rare, with a huge market demand and

potential customer base, including fiber materials

manufacturers, mold manufacturers, and various

industries that uses RTM as a mean to produce their

products [8-9].

Experimental Section

We have carried out experimental investigation on

two different types of fiber mat, distribution medium and

a core material using the visualization system (Figure 1).

Before experiment the material was trimmed to specific

dimensions (120 mm x 300 mm). Using PVC tubing,

the material being tested was connected to a vacuum

pump on one end, while the other end was connected to

the resin reservoir. Vacuum environment was created by

using high performance vacuum bag and clay. Clay was

carefully applied to the edge of vacuum bag with the

material centered under the high speed video camera.

LabVIEW was used for instrument control, process

automation and data acquisition. Industrial motor oil was

used for filling experiment and the viscosity before each

experiment was measured using a viscometer. In order to

calculate the true permeability of the fiber mat, the

porosity of the fiber needs to be measured. The thickness

of fiber mat layer is carefully measured by placing the

stacked fiber mat in between two metal plates and sealed

under vacuum with using high performance vacuum bag

Figure 2). In total, thickness from 6 different areas were

measured and averaged. The density of fiber mat was

measured using a high precision density balance.

Furthermore, we also carried out experimental

investigation on flow information in the thickness

direction. The melt front data is obtained using radial flow

method where the melt is injected in the center, and

spreads in a circular or elliptical pattern. The melt front

data is recorded on both sides of the fiber mats using high

speed camera, one on the top and one at the bottom.

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Results and Discussion Fluid flow in porous medium can be described by

Darcys Law (Eq1)

LPKVDD

=

1

where P is pressure difference and in this case 1atm

(1.013 x 105 Pa), V is the fluid velocity, L is the distance

that the fluid travel in unit time, and is fluid viscosity.

Thus the permeability K can be obtained using equation 1.

Before we can begin to process the data, one must

understand the difference between Seepage Velocity and

Darcian Velocity. The flow in fiber mat is through porous

medium, and therefore the effective area (A) is much

smaller than the cross-sectional area (A) and can be

described by the equation 2.

fAA = 2

If A is incorporated into Darcys Law, we can define a

new velocity Seepage Velocity, and Q the volumetric

flow rate from Equation 3 can be written into Equation 4.

PAKQ -=

! 3

PAKQ -=f'!

4

The Darcian (V) and seepage velocity (V)can be obtain

from equation 5 and 6

PkAQV -=-=

f'

!!

5

fV

AQV

!!!

=-='

6

What is observed in experiment (Figure 3) is not the

velocity term (V ) described in the Darcys Law, but

rather is the seepage velocity (V). The porosity is less

than 1, and therefore A< A. From Mass balance, Q =VA

=VA, one can see that V> V. In order to bring the

observed melt front into Darcys Law for calculation, we

need to convert the Seepage Velocity to Darcian Velocity,

and can be described by the following equation (7)

PKVVd -

==

f'!!

7

Equation 7 can be further simplified to give 1D scalar

form (Equation 8)

LPKVVd

D-==

f'!!

8

After replacing the velocity term by dL/dT, and

integration on both sides, we obtain Equation 9.

tPKL

fD

=22

9

The flow front data L is recorded as a function of time.

After plugining P (pressure difference), (viscosity)

and (the porosity of medium), the permeability can be

obtained.

From the permeability data obtained for biaxial

(-45/+45), we note that the average K11 and K22 are

within 5% difference, indicating that there is no

preferential flow directional for this type of fiber mat. For

large structure such as wind turbine where fiber mat

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layers can go up to 20-30 layers in certain area, flow

information in the thickness direction is critical, and

therefore we carried out experimental investigation on

permeability in the out of plane direction (K33). Out of

plane data from both the top and bottom surface was fitted

simultaneously using Moldex3D RTM module to derive

the out of plane permeability (K33 = 2.20E-13 m2). Most

experimental investigations on K33 relies on using sensors

of some sort, which could potentially interfere the melt

front as the melt travels in the thickness direction. In this

study, we present an alternate method to derive the

permeability data in the thickness direction without any

interference. We further carried out investigations on the

permeability behavior of different systems, including

uni-axial fiber mat, distribution medium and PVC core

material. The results are summarized in table 1. We note

that the filling behavior for uni-axial shows strong

directionality along the fiber direction as is the case with

distribution medium along principal filling direction.

Permeability and porosity result is summarized in table 1.

Since PVC core material is a closed cell foam material,

fluids only travels through the pre-opened channels. The

out of plane permeability data (K33 = 4.95 E-10 m2) is

derived using empirical formula assuming the

fully-developed average velocity in a channel resembles

the Darcy equation [10].

In this study, we use the Moldex3D RTM to simulate

the filling behavior of the core material. The simulation

geometry shows in Figure 6, and the dimension of the

cavity is 30cm in length, 15 cm in width, and 3cm in

thickness. The material parameters are set according to

the Table 1. The PVC core material is anisotropic with a

porosity = 0.002 and in-plane permeability of K11 = K22

=4.95 E-13 m2, out of plane permeability K33 = 4.95 E-10 m2.

In this experiment we used constant viscosity oil h=0.157 Pa s to fill the core under a constant inlet pressure

P = 1 atm. The experimental data for PVC core material

and simulation flow front time results is shown in Figure

7. The filling behavior of the simulation is in good

agreement with the experiment.

Conclusions In this paper, we carried out experimental

investigations into material properties that is required for

accurate RTM simulation. We built a robust visualization

system to improve the accuracy of permeability

measurements. Different types of fiber mats, distribution

medium and core materials, common in wind turbine

manufacturing, are thoroughly analyzed. We believed that

the methodology presented here could in term improve the

accuracy of RTM prediction and benefit the related

industry.

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Figure 1. Schematic of flow visualization system (redraw)

Figure 2. Fiber mat thickness measurement setup

Figure 3. Difference between Darcian and Sleepage

velocity

Figure 4. In plane permeability data for biaxial

(+45/-45) fabrics with surface density (808g/cm2)

Figure 5. Out of plane melt front data for biaxial

(+45/-45) fabrics with surface density (808g/cm2). The

out of plane permeability is calculated to be K33 = 2.20E-13

m2

Figure 6. Geometry of the core material

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Figure 7. In plane filling data for PVC core material

Table 1. Summary of the permeability data for different

materials

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