Browsing by Author "Long, Andrew"

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    Optimisation of Sheet Forming for Textile Composites using variable Peripheral Pressure.
    (2006-03-01T00:00:00Z) Long, Andrew; Skordos, Alexandros A.; Harrison, Phil; Clifford, Mike; Sutcliffe, Michael P. F.
    This paper addresses optimisation of the sheet forming process for textile composites. A woven carbon/epoxy prepreg helicopter pilot helmet is used to demonstrate both experimental and numerical studies. A novel stamp-forming experimental procedure is developed, where a segmented blank-holder is used to control draw-in, facilitating process control and optimisation. A truss based finite element model, incorporating non-linear fabric shear properties and the occurrence of wrinkling due to tow buckling, is used to simulate forming. The simple basis of the model results in low computational times that allow its use within an optimization procedure. A genetic algorithm is used to solve the optimisation problem, minimizing the wrinkling in the formed component by selecting a suitable peripheral holding force distribution. Optimised designs resulting from the inversion procedure have significantly lower wrinkling than uniform peripheral force profiles.
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    Stochastic simulation of the cure of advanced composites
    (Cranfield University, 2015-02) Mesogitis, Tassos; Skordos, Alexandros A.; Long, Andrew
    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.