Browsing by Author "Long, A. C."

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    Non-crimp fabrics geometrical variability and its influence on composites cure
    (2014-12-31) Mesogitis, Tassos; Skordos, Alexandros A.; Long, A. C.
    A framework is developed and implemented to characterize and model in plane fibre misalignment in Non-Crimp fabrics (NCF). Image analysis based on fast Fourier Transform and correlation analysis is used to characterise in plane fibre misalignment in a carbon fibre ±45º NCF. It is found that fibre misalignment is significant showing high anisotropic spatial autocorrelation with the major direction of autocorrelation coinciding with the direction of the non-structural stitching of the fabric. The spatial autocorrelation structure of the fabric is modelled using an autoregressive two-dimensional stochastic process, the Ornstein- Uhlenbeck (OU) sheet. The resulting stochastic field is simulated using the Cholesky factorization, the spectral decomposition and the Karhunen-Loeve expansion (KLE). The three discretization techniques are compared in terms of accuracy and efficiency.
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    Stochastic heat transfer simulation of the cure of advanced composites
    (Sage, 2015-11-08) Mesogitis, Tassos; Skordos, Alexandros A.; Long, A. C.
    A stochastic cure simulation approach is developed to investigate the variability of the cure process during resin infusion related to thermal effects. Boundary condition uncertainty is quantified experimentally and appropriate stochastic processes are developed to represent the variability in tool/air temperature and surface heat transfer coefficient. The heat transfer coefficient presents a variation across different experiments of 12.3%, whilst the tool/air temperatures present a standard deviation over 1℃. The boundary condition variability is combined with an existing model of cure kinetics uncertainty and the full stochastic problem is addressed by coupling a cure model with Monte Carlo and the Probabilistic Collocation Method and applied to the case of thin carbon epoxy laminates. The overall variability in cure time reaches a coefficient of variation of about 22%, which is dominated by uncertainty in surface heat transfer and tool temperature; with ambient temperature and kinetics contributing variability in the order of 1%.
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    Stochastic simulation of the influence of cure kinetics uncertainty on composites cure
    (Elsevier, 2015-02-13) Mesogitis, Tassos; Skordos, Alexandros A.; Long, A. C.
    A stochastic cure simulation methodology is developed and implemented to investigate the influence of cure kinetics uncertainty due to different initial resin state on the process of cure. The simulation addresses heat transfer effects and allows quantification of uncertainty in temperature overshoot during the cure. 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. A cure simulation model was coupled with conventional Monte Carlo and an implementation of the Probabilistic Collocation Method. Both simulation schemes are capable of capturing variability propagation, with the collocation method presenting benefits in terms of computational cost against the Monte Carlo scheme with comparable accuracy. Simulation of the cure of a carbon fibre–epoxy panel shows that cure kinetics uncertainty can cause considerable variability in the process outcome with a coefficient of variation in temperature overshoot of about 30%.
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    Stochastic simulation of the influence of fibre path variability on the formation of residual stress and shape distortion
    (Wiley, 2015-11-20) Mesogitis, Tassos; Skordos, Alexandros A.; Long, A. C.
    A stochastic cure simulation approach is developed and implemented to investigate the influence of fibre misalignment on cure. Image analysis is used to characterize fiber misalignment in a carbon non-crimp fabric. It is found that variability in tow orientation is significant with a standard deviation of 1.2°. The autocorrelation structure is modeled using the Ornstein-Uhlenbeck sheet and the stochastic problem is addressed by coupling a finite element model of cure with a Monte Carlo scheme. Simulation of the cure of an angle shaped carbon fiber-epoxy component shows that fiber misalignment can cause considerable variability in the process outcome with a coefficient of variation in maximum residual stress up to approximately 2% (standard deviation of 1 MPa) and qualitative and quantitative variations in final distortion of the cured part with the standard deviation in twist and corner angle reaching values of 0.4° and 0.05° respectively. POLYM. COMPOS., 2015. © 2015 The Authors Polymer Composites published by Wiley Periodicals, Inc. on behalf of Society of Plastics Engineers
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    Uncertainty in the manufacturing of fibrous thermosetting composites: A review
    (Elsevier, 2014-02) Mesogitis, Tassos; Skordos, Alexandros A.; Long, A. C.
    Composites manufacturing involves many sources of uncertainty associated with material properties variation and boundary conditions variability. In this study, experimental and numerical results concerning the statistical characterization and the influence of inputs variability on the main steps of composites manufacturing including process-induced defects are presented and analysed. Each of the steps of composite manufacturing introduces variability to the subsequent processes, creating strong interdependencies between the process parameters and properties of the final part. The development and implementation of stochastic simulation tools is imperative to quantify process output variabilities and develop optimal process designs in composites manufacturing.