Application to Composite Materials

Using the model from Section 5.3.2, one promising application of such a cure simulation is in regard to the prediction of composite surface finish. Surface finish is a very

challenging topic in the composites world. Thermoplastics, which exhibit a large thermal dependence, commonly show waviness on a moulded part due to the uneven contraction of the polymer around the embedded fibres. Thermosets are usually easier to work with to produce a smooth, class-A surface, though the cure shrinkage and thermal shrinkage need to be managed – typically with polymer fillers. The goal during production is to produce a composite part that has a near-mirror finish which can either be painted or coated to achieve an aesthetically pleasing final surface. Though one challenge is to

manage the composite part during an automotive paint-bake cycle where the

aforementioned springback is a concern, predicting the surface quality of a composite part is an initial need.

To demonstrate this simulation ability, an exploratory simulation was created to investigate two impacts on surface finish: fibre separation and the thickness of the

polymer layer above the fibres nearest the free surface. The model setup and deformation pattern is shown in Figure 5.17, below. It is anticipated that the surface curvature will be reduced as fibre separation is reduced or the polymer layer above the outer fibres is increased.

Figure 5.17 – Fibre surface finish model showing a) model setup with surface points for determining curvature and b) the post-simulation deformation behaviour and

residual stresses.

To determine the predicted curvature, points are placed on the free surface between the upper midpoints of each fibre as in Figure 5.17a). The displacement of each point will be recorded at the end of each simulation to determine the predicted surface curvature. The two important values that are calculated are the surface roughness and the radius of curvature. Though there are many values which can be used to characterize the

employed. The arithmetic average of surface roughness, denoted Ra, is calculated as defined: as the average of all the points on the surface, taking the lowest point as the reference point. The surface curvature is calculated from:

𝜅_𝑟 = |(1 + 𝑦′2)

3 2⁄

𝑦′′ | (5.1)

where 𝑦′ _{and 𝑦}′′ _{are the first and second derivatives of the Cartesian function defining}

the curve [123]. Here it is assumed that points on the surface of the simulated composite form a continuous curve which is at least twice differentiable.

While the data produced from the simulation is useful, it is not immediately apparent if the simulations are providing a realistic measure of the surface of a fibrous composite. To coincide with the predictions, several test composites were specifically fabricated to generate some experimental data. The first such sample was composed of unidirectional glass fibres in an epoxy matrix such that there would be fibres near to the upper free surface. This was mounted in a differently coloured epoxy so that polishing would not impose damage to this surface which could now be viewed end-on using a transmitted light setup to see this composite surface as in Figure 5.18a).

At the maximum optical magnification the samples were imaged such that the interface between the composite epoxy and the mounting epoxy was readily apparent. The surface curvature is quite visible and was manually extracted from the image using constructed curves as in Figure 5.18b) for several locations. Both the simulation data and the experimental data are collected in Figure 5.19.

Figure 5.18 – High optical magnification of glass / epoxy fibre surface viewed perpendicular to the fibre direction: a) native b) with lines of curvature.

Figure 5.19 – Comparison of predicted and measured surface roughness as related to the surface curvature

The two simulation studies resulted in overlapping trends between the fibre spacing and the polymer layer above the surface fibres. As was predicted, a greater fibre spacing or a decreasing polymer layer tend to sharply increase the roughness and decrease the surface curvature. A fine curvature is undesirable as it implies that light hitting the surface will scatter and the fine features around surface fibres in a composite will be visible. This, for instance, causes the appearance of grooves in the surface after the paint application, and is not attractive to consumers.

The experimental data presented in Figure 5.19 is quite scattered. While the correct magnitude of roughness is attained from the optical measurements, the image resolution prevented the curvature from being accurately assessed. Therefore, two alternate methods were explored to determine their feasibility to generating accurate surface profiles of composite materials. A snapshot of each test method is presented; for the 3D laser scanning in Figure 5.20 and for the high resolution 3D optical scanning in Figure 5.21.

Laser scanning a surface requires that the surface reflect enough of the light for the detector to measure the time-of-flight accurately, and hence map the surface by rastoring the laser. The neat polymer caused too much light scatter to be measured without first gold-coating to increase the reflectivity. Figure 5.20a shows the result for a section of composite with three glass fibres embedded just below the surface. While the roughness can again be determined from this method accurately, the curvature measurement is very sensitive to a clean surface, which was impeded by the gold-coating operation.

Figure 5.20 – 3D laser scanned profile map of glass / epoxy fibre surface

The optical scanning did not require gold-coating to be effective, but is here sensitive to proper surface calibration. Since the optical scanning requires a flat reference area to perform the lens distortion correction algorithms, and no flat surface was available on the tested sample, the result is a wavy image as in Figure 5.21a). From this present data, it was not possible to generate accurate roughness or curvature measurements to check against the simulated values.

Figure 5.21 – 3D optical profile map of glass / epoxy fibre surface These techniques show much promise as experimental methods to vet the cure

simulation, but require a dedicated study through which careful and systematic analysis can be conducted. It is concluded that it is possible with the present technology to measure the surface characteristics of a polymer composite if given enough time to determine the proper measurement setup parameters. It is also concluded that the composite model as presented is capable of predicting such phenomena as the surface roughness of a composite part. Future work could examine how a mould-wall might impact the surface quality and what steps are needed to produce a consistent class-A surface given the polymer and composite properties.

6

Applying Interfacial Failure

The crux of the research is hereby reached: adding interfacial strength into a composite material model to facilitate an accurate failure prediction. Two supporting experimental studies are used to demonstrate the application of the failure criterion on different

material systems and to provide a measure of the accuracy of the criterion. The criterion is discussed in detail with comments toward its application, strengths, and outstanding areas for further research.