Abstract:
This study focuses on the development of a stochastic simulation methodology to
study the effects of cure kinetics uncertainty, in plane fibre misalignment and
boundary conditions uncertainty on the cure process of composite materials.
Differential Scanning Calorimetry was used to characterise cure kinetics variability of
a commercial epoxy resin used in aerospace applications. It was found that cure
kinetics uncertainty is associated with variations in the initial degree of cure,
activation energy and reaction order. Image analysis was employed to characterise
in plane fibre misalignment in a carbon fibre ±45º non-crimp fabric. The experimental
results showed that variability in tow orientation was significant with a standard
deviation of about 1.2º. A set of experiments using an infusion set-up was carried
out to quantify boundary conditions uncertainty related to tool temperature, ambient
temperature and surface heat transfer coefficient using thermocouples (tool/ambient
temperature) and heat flux sensors (surface heat transfer coefficient). It was
concluded that boundary conditions uncertainty can show considerable short term
and long term variability. Conventional Monte Carlo and Probabilistic Collocation
Method were integrated with a thermo-mechanical cure simulation model in order to
investigate the effect of cure kinetics, fibre misalignment and boundary conditions
variability on process outcome. The cure model was developed and implemented
using a finite element model incorporating appropriate material sub-models of cure
kinetics, specific heat capacity, thermal conductivity, moduli, thermal expansion and
cure shrinkage. The effect of cure kinetics uncertainty on the temperature overshoot
of a thick carbon fibre epoxy flat panel was investigated using the two stochastic
simulation schemes. The stochastic simulation results showed that variability in cure
kinetics can introduce a significant scatter in temperature overshoot, presenting a
coefficient of variation of about 30%. Furthermore, it was shown that the collocation
method can offer an efficient solution with significantly lower computational cost
compared to Monte Carlo at comparable accuracy. Stochastic simulation of the cure
of an angle shaped carbon fibre-epoxy component within the Monte Carlo scheme
showed that fibre misalignment can cause considerable variability in the process
outcome. The coefficient of variation of maximum residual stress can reach up to
approximately 2% (standard deviation of 1 MPa) whilst qualitative and quantitative
variations in final distortion of the cured part occur with the standard deviation in twist
and corner angle reaching values of 0.4 º and 0.05º respectively. Simulation of the
cure of a thin carbon fibre-epoxy panel within the Monte Carlo scheme indicated that
surface heat transfer and tool temperature variability dominate variability in cure time,
resulting in a coefficient of variation of about 22%. In addition to Monte Carlo, the
effect of surface heat transfer coefficient and tool temperature variations on cure
time was addressed using the collocation method. It was found that probabilistic
collocation is capable of capturing variability propagation with good accuracy while
offering tremendous benefits in terms of computational costs.