Composite materials, particularly carbon fibre-reinforced polymers (CFRPs), have garnered significant
attention in the aerospace industry due to their lightweight and high-strength properties. Autoclaving,
a well-known method for producing high-quality CFRPs suitable for aerospace applications, faces
challenges such as high energy consumption making it less suitable for high-volume production. Resin
Transfer Moulding (RTM) has emerged as a viable alternative, offering advantages over autoclaving,
including lower temperature latency during curing stage. This potentially can reduce the likelihood of
temperature overshooting within thick CFRP laminates and result in a more uniform temperature
through part thickness, consequently lowering residual stress.
This PhD thesis investigates and optimises the through-thickness temperature of thick CFRP laminates
during curing stages by studying the effect of a wide range of manufacturing parameters for RTM
processing. This was carried out by developing a thermal and cure simulation tool using
MATLAB_Simulink and connecting the model to the response surface method (RSM).
Initially, cure kinetics of epoxy resin were studied through thermal analysis. As a result of the analysis,
a deceleration reaction was detected and described by the Sestak-Berggren Kinetic model. The total
heat of reaction, activation energy, pre-exponential factor, and n and m constants were measured by
following the Kissinger-Akahira-Sunose (KAS) and Malek’s methods to verify that the selected model
can comply with the epoxy resin. The comparison of the reaction rate obtained from the cure kinetic
equation with the thermal analysis showed close agreement.
The CFRPs were manufactured using vacuum bagging mainly due to the simplicity of embedding
thermocouples inside the mould and between the carbon fibre plies. Laminates with 10, 20, and 30
mm in thickness were manufactured while their temperature and degree of cure at the top, middle,
and bottom of the lay-up were recorded.
Void content, density, fibre weight fraction, in-plane and through-plane thermal conductivity (TC) ,
and heat capacity of the manufactured samples were measured through different methods and
showed uniformity between all samples.
The RSM was used to identify the impact of different variables such as the thickness of the part,
heating cycle, one-sided and two-side heating conditions, thermal conductivity of the mould and the
composites, and ambient temperature on the temperature distribution inside the CFRP laminates.
Eight parameters (response variables) were defined in the RSM to give a clear picture of the
temperature and degree of cure within the parts. Maximum temperature (T_max), maximum
temperature difference through the thickness (ΔT_max), and location of the maximum temperature (“C”) are among response variables that were studied for their dependence of other controllable
variables. The factor “C” is helpful in detecting curing patterns through the part thickness, which is
linked to a reduction in the level of induced stress during the curing process. Inside-to-outside curing
pattern should happen before resin gelation points (preferably from the start of the curing) to be
effective in reduction of residual stress.
The RSM with central composite design (CCD) was used to create more than two thousand test runs
required to detect the interaction between the manufacturing variables (controllable variables) and
response variables. This was carried out by developing a simulation tool that could predict the
temperature and state of the cure through the CFRP laminates under desired heating condition. A 1D
thermal model based on the finite differential method (FDM) was developed in MATLAB_Simulink,
and the experimental results verified its performance.
The influential variables and their effect on the eight response variables were investigated for
different scenarios. The mould with low thermal conductivity resulted in a smaller ΔT_max and T_max,
specifically for thick laminates. For composites with lower thicknesses, the low thermally conductive
mould showed little benefit and have result in longer curing time.
The results from varying ambient temperatures demonstrated that selecting an appropriate ambient
temperature can significantly reduce the temperature difference through the thickness of the part
(ΔT_max), as well as minimize the temperature overshoot (T_max) and variations in the degree of
cure. Notably, ambient temperature was found to be the most influential factor in determining the
location of T_max, effectively shifting the curing behaviour to inside-to-outside pattern. This shift
suggests that with a well-controlled ambient heating program, one-sided heating can achieve similar
thermal and curing uniformity as two-sided heating. However, unlike two-sided systems, one-sided
heating requires less complex tooling and setup. This can lead to significant reductions in
manufacturing cost, tooling complexity, and energy consumption, particularly in large-scale or thick
composite parts.
The optimal ambient temperature and heating schedule were developed using Response Surface
Methodology (RSM), enabling precise control over curing conditions and ensuring high-quality results
with a more cost-effective setup.
Overall, the combination of the RSM and Simulink built a comprehensive model that was able to
predict the temperature and degree of cure in composite laminates. The model was also used to
optimize the process by suggesting the correct values for the manufacturing parameters to provide
the response variables close to the target defined by the user. This was confirmed by setting the CFRP curing conditions according to the model-defined parameters and comparing the temperature values measured at the top, middle and bottom of the samples with the simulation. The model showed a
promising performance in designing manufacturing conditions and a potential to be used on more
complicated geometries. The developed model can be adjusted for a wide range of reinforced
composites and different resin systems, although it remains subject to further testing and validation.
| Date of Award | 19 Feb 2026 |
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| Original language | English |
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| Awarding Institution | - University Of Strathclyde
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| Sponsors | University of Strathclyde |
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| Supervisor | Liu Yang (Supervisor) & James Thomason (Supervisor) |
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