Browsing by Author "Mesogitis, Tassos"
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Item Open Access Developing cure kinetics models for interleaf particle toughened epoxies(Society for the Advancement of Material and Process Engineering (SAMPE), 2016-12-31) Kratz, James; Mesogitis, Tassos; Skordos, Alexandros A.; Hamerton, Ian; Partridge, Ivana K.In this study, we investigated the cure kinetics behaviour of the commercial Hexply® M21 thermoplastic interleaf epoxy resin system. Dynamic, isothermal, and cure interrupted modulated differential scanning calorimetry (mDSC) tests were used to measure the heat flow of the system, and semi-empirical models were fitted to the data. The cure kinetics model describes the cure rate satisfactorily, under both dynamic heating and isothermal conditions. The glass transition temperature was described using the DiBenedetto equation and showed that heating rate can influence formation of the network; therefore cure schedule must be controlled carefully during processing.Item Open Access 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.Item Open Access 'Optimisation of an in-process lineal dielectric sensor for liquid moulding of carbon fibre composites'(Cranfield University, 2020-11-04 09:22) Mesogitis, Tassos; Asareh, Mehdi; Skordos, Alex; Maistros, George; Lira, ChristianData: -RTM experiment - 4 bar clamping pressure.xlsx Excel spreadsheet containing the impedance/admittance signals and corresponding covered length for the the PI-LD lineal sensor alongside the visual flow front measurements using video for the 4 bar clamping pressure RTM trial -RTM experiment - 7 bar clamping pressure.xlsx Excel spreadsheet containing the impedance/admittance signals and corresponding covered length for the PI-LD and NyPU lineal sensor, the impedance signals for the PI-LD cure sensor, and the temperature evolution used for the kinetics/specific heat capacity evolution for the 6 bar clamping pressure RTM trial -Air sensor tests.xlsx Excel spreadsheet containing the impedance and admittance spectra of 3 PU sensors in air Models: -FLEXPDE sensor in air.dat FLEXPDE script for 2D FE complex electric field model of sensor in air -FLEXPDE sensor in resin.dat FLEXPDE script for 2D FE complex electric field model of sensor in resin Images: - Flow front mm_process time min.zip Compressed set of images used to identify the flow front position in the 4 bar clamping pressure RTM trial. Files are named to indicate the flow front position and process time. For example, file 150-1.70 is the image corresponding to a flow position of 150 mm at 1.70 min.Item Open Access Stochastic simulation of the cure of advanced composites(Cranfield University, 2015-02) Mesogitis, Tassos; Skordos, Alexandros A.; Long, AndrewThis 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.Item Open Access 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%.Item Open Access 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 EngineersItem Open Access 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.