Browsing by Author "Struzziero, Giacomo"

Now showing 1 - 13 of 13
  • Thumbnail Image
    ItemOpen Access
    Assessment of the benefits of 3D printing of advanced thermosetting composites using process simulation and numerical optimisation
    (Elsevier, 2023-01-18) Struzziero, Giacomo; Barbezat, Michel; Skordos, Alexandros A.
    3D printing of continuous fibre reinforced thermosetting matrix composites is set to revolutionise composite manufacturing practice. The potential of curing additively is anticipated to bring significant improvement in terms of increasing process speed, producing geometries that are inaccessible with current processing routes and eliminating detrimental exothermic effects during the process. This study presents a comparison between the curing stage of the 3D printing and standard batch processing for carbon fibre/epoxy components of varying thickness and size. An optimisation methodology links simulation of the cure using Finite Element solver Abaqus with a Genetic Algorithm capable of dealing with multi-objective problems. Optimal cure cycles to minimise both process time and temperature overshoot in 3D printing and batch processing are identified and the optimal trade-offs compared. The results highlight that temperature overshoot reduction up to 85 % is possible and that the intrinsic additive nature of the 3D printing allows eliminating the dependence of temperature overshoot on thicknesses and producing components with thicknesses that are very difficult to manufacture conventionally. A simplified procedure for the estimation of 3D printing process duration is proposed based on the results of finite element simulation. This is used for exploration of the limits of the process with respect to part size and for a generic comparison of process applicability against batch processing. The analysis shows that 3D printing is highly advantageous for small components, is efficient for mid-size components and can – on the basis of its scalability – offer a feasible route for producing large and very large components.
  • Thumbnail Image
    ItemOpen Access
    Consolidation of continuous fibre reinforced composites in additive processes: A review
    (Elsevier, 2021-11-03) Struzziero, Giacomo; Barbezat, Michel; Skordos, Alexandros A.
    Additive manufacturing of continuous reinforced polymer is currently a focus topic in the composite manufacturing industry as it represents a viable solution to satisfy the requirements of high volume production and automation that could facilitate expanding the use of composite materials and meet sustainability goals. Nevertheless, several challenges need to be addressed to increase the quality standards to match those of parts manufactured by standard composite processing routes. Specifically, consolidation issues appear to be the determining factor which hold the technology back. The present review paper analyses current consolidation techniques utilised in additive processing of composites and identifies the most promising current and future manufacturing technologies capable of complying with stringent sustainability, quality and cost standards.
  • No Thumbnail Available
    ItemOpen Access
    Data for the paper "Stochastic multi-objective optimisation of the cure process of thick laminates"
    (Cranfield University, 2018-07-31 15:58) Tifkitsis, Konstantinos; Struzziero, Giacomo; Skordos, Alex
    Surrogate_model_validation.xlsx includes the data corresponding to the comparison between FE and surrogate model (responses surfaces, PDF of model error, stochastic simulation)-Uncertainty_quantification_results.xlsx includes the results of uncertainty quantification of convection coefficient and tool temperature.-Stochastic_optimisation_results.xlsx includes the stochastic and deterministic Pareto points of stochastic and deterministic optimisation respectively.-Sensitivity_analysis_results.xlsx includes the data corresponding to the sensitivity analysis of standard and optimal profiles.-flat_panel_15.6mm.dat : Marc input corresponding to Cure model of this study-usub.f: contains all the subroutines for material properties and boundary conditions
  • No Thumbnail Available
    ItemOpen Access
    Materials modelling and process simulation of the pultrusion of curved parts
    (Cranfield University, 2021-02-12 15:40) Struzziero, Giacomo; Maistros, George; Hartley, John; Skordos, Alex
    This dataset comprises experimental data and finite element/control volume models reported in the paper titled ‘Materials modelling and process simulation of the pultrusion of curved parts’ published in Composite Part A: Applied Science and Manufacturing (2021). There are four files: Excel workbook Material_Characterisation.xlsx contains Viscosity, Modulus, Coefficient of Thermal Expansion and Chemical Shrinkage data organised in four separate spreadsheets. File Curved_pultrusion_stage2_job.dat is the analysis deck of the stage 2 curved pultrusion thermo-mechanical model of the T cross section stiffener for finite element solver MSC.Marc.File Pre_former_stage1.dtf is the PAMRTM model setup file for stage 1 pultrusion simulation of the T cross section stiffener. File Pre_former_stage1.unv is the mesh information PAMRTM file for stage 1 pultrusion simulation of the T cross section stiffener.
  • Thumbnail Image
    ItemOpen Access
    Materials modelling and process simulation of the pultrusion of curved parts
    (Elsevier, 2021-02-11) Struzziero, Giacomo; Maistros, G. M.; Hartley, J.; Skordos, Alexandros A.
    The present paper addresses the simulation of a concept for the manufacturing of aerospace quality carbon/epoxy composite curved parts using pultrusion. In this approach, the part is first partially cured in a pre-former followed by final curing in a curved post-former. An aerospace epoxy resin system has been fully characterised and the corresponding constitutive material models, incorporating dependence on both temperature and degree of cure, developed. A 3D Finite Element model of the process, to manufacture a T-stiffener, involving impregnation, curing and forming of the curvature was developed and implemented. The simulation results show that a degree of cure of around 62% -close to the gelation point of the resin system considered - at the exit of the pre-former stage is appropriate for the success of the subsequent stage. In the post-former the cure is completed reaching a final degree of cure of about 87%. The stresses generated in post-forming reach a maximum of 54 MPa in compression in the transverse direction and of 200 MPa in tension in the fibre direction showing that the process is feasible without inducing defects linked to micro buckling or rupture.
  • No Thumbnail Available
    ItemOpen Access
    Measurement of thermal conductivity of epoxy resins during cure
    (Cranfield University, 2018-07-12 08:45) Skordos, Alex; Struzziero, Giacomo; Remy, Berenice
    Thermal_conductivity_glycerine: Experimental and FE data of the thermal conductivity test run on glycerine at 100 degC and 4 degC. Includes also the sensitivity analysis of the measurement on thermocouple misplacement. - -RTM6_cure_kinetics_results: Includes the isothermal and dynamic data for the RTM6 cure kinetics characterisation and the corresponding model. It also includes the sensitivity analysis on period and amplitude influence for RTM6 - - 890RTM_cure_kinetics_results: Includes the isothermal and dynamic data for the 890RTM cure kinetics characterisation and the corresponding model. It also includes the sensitivity analysis on period and amplitude influence for 890RTM - - XU3508_cure_kinetics_results: Includes the isothermal and dynamic data for the XU3508 cure kinetics characterisation and the corresponding model. - -Di Benedetto_XU3508: Includes the dataused to build the Di Benedetto equation for the XU3508 resin system and the corresponding model - - Cp_density_conductivity_data: Includes the Cp data and model, the density and the thermal conductivity data for the three resin systems under investigation: RTM6, 890RTM and XU3508 - -Thermal_conductivity_model: Includes the data from the thermal conductivity tests for the three resin system and the fitting of the experimental data with the analytical model.
  • Thumbnail Image
    ItemOpen Access
    Measurement of thermal conductivity of epoxy resins during cure
    (Wiley, 2018-08-28) Struzziero, Giacomo; Remy, B.; Skordos, Alexandros A.
    This work reports the development of a methodology for the measurement of thermal conductivity of thermosetting polymers during their cure. The study addresses the reliability and robustness of the method through FEA modeling and testing using a noncuring material with known thermal conductivity. The thermal conductivity and its evolution during the cure has been measured for three widely used aerospace epoxy resins, namely, RTM6, 890RTM, and the XU3508/XB3473 system as function of cure temperature. A constitutive model expressing the dependence of thermal conductivity on the degree of cure and temperature has been established. The device developed here can measure thermal conductivity of epoxy resin with accuracy up to 3%.
  • No Thumbnail Available
    ItemOpen Access
    Multi-objective optimisation of Resin Infusion
    (Cranfield University, 2019-01-14 16:52) Struzziero, Giacomo; Skordos, Alex
    Exhaustive_analysis.xlsx: -‘Exhaustive’ sheet: All the data gathered during the exhaustive search are reported. Column 1 to 8 report respectively the temperature of first and second dwell, duration of first dwell and ramp, convection coefficient, gatelocati on, filling time and maximum degree of cure. -‘Gate-T1’ sheet: Reports the data to plot the 3D landscape -‘T1-T2’ sheet: Reports the data to plot the 3D landscape Optimisation results.xlsx -‘Results’ sheet: Reports the 13 generations the GA requires to converge to a final optimal Pareto front. Column 1 to 9 report respectively the generation number, temperature of first and second dwell, duration of first dwell and ramp, gate location, convection coefficient, filling time and maximum degree of cure. -‘Details of individuals’ sheet: Reports the detailed analysis f the different strategies of solutions belonging to different region of the Pareto. Regions_analysis.xlsx -‘Horizontal_flow_front_data’ sheet: Reports the compact data for the Temperature, viscosity and degree of cure evolution for an horizontal region solution -‘Viscosity_horizontal_region’ sheet: Reports the viscosity evolution for different nodes in the model for an horizontal region solution -‘Degree cure_horizontal_region’ sheet: Reports the degree of cure envelope for an horizontal solution ‘Temperature_horizontal region’ sheet: Reports the temperature evolution for different nodes in the model for an horizontal region solution -‘Model_verification’ sheet: reports the analytical viscosity model implementation ‘Vertical_flow front_data’ sheet: Reports the compact data for the Temperature, viscosity and degree of cure evolution for a vertical region solution -‘Degree_cure_vertical_region’ sheet: Reports the degree of cure envelope for a vertical solution region -‘Temperature_vertical_region’ sheet: Reports the temperature evolution for different nodes in the model for a vertical region solution -‘Viscosity_vertical_region’ sheet: Reports the viscosity evolution for different nodes in the model for a vertical region solution -‘Standard_flow_front_data’ sheet: Reports the compact data for the Temperature, viscosity and degree of cure evolution for the standard solution -‘Deg_cure_standard’ sheet: Reports the degree of cure envelope for the standard solution ‘-Temperature_data_standard’ sheet: Reports the temperature evolution for different nodes in the model for the standard solution -‘Viscosity_standard’ sheet: Reports the viscosity evolution for different nodes in the model for the standard solution -‘Plots’ sheet: plots summary
  • Thumbnail Image
    ItemOpen Access
    Multi-objective optimisation of the cure of thick components
    (Elsevier, 2016-11-14) Struzziero, Giacomo; Skordos, Alexandros A.
    This paper addresses the multi-objective optimisation of the cure stage of composites manufacture. The optimisation aims to minimise the cure process duration and maximum temperature overshoot within the curing part by selecting an appropriate thermal profile. The methodology developed combines a finite element solution of the heat transfer problem with a Genetic Algorithm. The optimisation algorithm approximates successfully and consistently the Pareto optimal front of the multi-objective problem in a variety of characteristic geometries of varying thickness. The results highlight the efficiency opportunities available in comparison with standard industrial cure profiles. In the case of ultra-thick components improvements of up to 70% in terms of overshoot and 14 h in terms of process time, compared to conventional cure profiles for ultra-thick components, can be achieved. In the case of thick components reduction up to 50% can be achieved in both temperature overshoot and process duration.
  • No Thumbnail Available
    ItemOpen Access
    Multi-objective optimisation of the cure of thick components
    (Cranfield University, 2016-11-18 08:21) Struzziero, Giacomo; Skordos, Alex
    The file-set contains the following files: - Flatpanel_24mm.dat: A Marc input file used as template for the optimisation methodology - Usub.f: Contains the subroutines implemented to modify the input file at each optimisation iteration - Exhaustive_search.xlsx: Contains the data of the comparison between the GA and exhaustive search final Pareto fronts. Columns contain temperature of first and second dwell, duration of first dwell, ramp rate, process time and overshoot temperature for the exhaustive case whilst in column H and I the process time and overshoot temperature of the GA Pareto are reported. - Flat_panel_results.xlsx: The spreadsheet contains: optimisation of flat panel 24 and 60 mm case, optimisation of flat panel 60 mm with 30 and 100 W/m^2 K convection coefficient and optimisation of flat panel 24 mm with 30 and 100 W/m^2 K convection coefficient. In each sheet columns contain the generation number, the optimisation parameters, process time and temperature overshoot. - L_shape_results.xlsx: The spreadsheet contains optimisation of the L-shape for the 24 and 60 mm case. In each sheet columns contain the generation number, the optimisation parameters, process time and temperature overshoot. - T_joint_results.xlsx: The spreadsheet contains optimisation of the T-joint for the 24 and 60 mm case. In each sheet columns contain the generation number, the optimisation parameters, process time and temperature overshoot. - L_shape_24mm_corner_point.xlsx: Contains the detailed analysis of a corner point optimisation solution for the L-shape 24 mm. Columns contain time, temperature, degree of cure and reaction rate values at different increments for different nodes through thickness. - L_shape_24mm_standard_point.xlsx: Contains the detailed analysis of the standard point solution for the L-shape 24 mm. Columns contain time, temperature, degree of cure and reaction rate values at different increments for different nodes through thickness. - L_shape_24mm_horizontal_point.xlsx: Contains the detailed analysis of a corner point optimisation solution for the L-shape 24 mm. Columns contain time, temperature, degree of cure and reaction rate values at different increments for different nodes through thickness.
  • Thumbnail Image
    ItemOpen Access
    Numerical optimisation of thermoset composites manufacturing processes: A review
    (Elsevier, 2019-06-25) Struzziero, Giacomo; Teuwen, Julie J. E.; Skordos, Alexandros A.
    The impetus for higher performance, robustness and efficiency in the aerospace, automotive and energy industries has been reflected in more stringent requirements which the composite manufacturing industry needs to comply with. The process design challenges associated with this are significant and can be only partially met by integration of simulation in the design loop. The implementation of numerical optimisation tools is therefore necessary. The development of methodologies linking predictive simulation tools with numerical optimisation techniques is pivotal to identify and therefore develop optimal design conditions that allow full exploitation of the efficiency opportunities in composite manufacturing. Numerical and experimental results concerning the optimisation techniques and methodologies implemented in literature to address the optimisation of thermoset composite manufacturing processes are presented and analysed in this study.
  • Thumbnail Image
    ItemOpen Access
    Optimisation of the VARTM process
    (Cranfield University, 2014-08) Struzziero, Giacomo; Skordos, Alexandros A.
    This study focuses on the development of a multi-objective optimisation methodology for the vacuum assisted resin transfer moulding composite processing route. Simulations of the cure and filling stages of the process have been implemented and the corresponding heat transfer and flow through porous media problems solved by means of finite element analysis. The simulations involved material sub-models to describe thermal properties, cure kinetics and viscosity evolution. A Genetic algorithm which constitutes the foundation for the development of the optimisation has been adapted, implemented and tested in terms of its effectiveness using four benchmark problems. Two methodologies suitable for multi-objective optimisation of the cure and filling stages have been specified and successfully implemented. In the case of the curing stage the optimisation aims at finding a cure profile minimising both process time and temperature overshoot within the part. In the case of the filling stage the thermal profile during filling, gate locations and initial resin temperature are optimised to minimise filling time and final degree of cure at the end of the filling stage. Investigations of the design landscape for both curing and filling stage have indicated the complex nature of the problems under investigation justifying the choice for using a Genetic algorithm. Application of the two methodologies showed that they are highly efficient in identifying appropriate process designs and significant improvements compared to standard conditions are feasible. In the cure process an overshoot temperature reduction up to 75% in the case of thick component can be achieved whilst for a thin part a 60% reduction in process time can be accomplished. In the filling process a 42% filling time reduction and 14% reduction of degree of cure at the end of the filling can be achieved using the optimisation methodology. Stability analysis of the set of solutions for the curing stage has shown that different degrees of robustness are present among the individuals in the Pareto front. The optimisation methodology has also been integrated with an existing cost model that allowed consideration of process cost in the optimisation of the cure stage. The optimisation resulted in process designs that involve 500 € reduction in process cost. An inverse scheme has been developed based on the optimisation methodology aiming at combining simulation and monitoring of the filling stage for the identification of on-line permeability during an infusion. The methodology was tested using artificial data and it was demonstrated that the methodology is able to handle levels of noise from the measurements up to 5 s per sensor without affecting the quality of the outcome.
  • Thumbnail Image
    ItemOpen Access
    Stochastic multi-objective optimisation of the cure process of thick laminates
    (Elsevier, 2018-06-11) Tifkitsis, Konstantinos; Mesogitis, Tassos S.; Struzziero, Giacomo; Skordos, Alexandros A.
    A stochastic multi-objective cure optimisation methodology is developed in this work and applied to the case of thick epoxy/carbon fibre laminates. The methodology takes into account the uncertainty in process parameters and boundary conditions and minimises the mean values and standard deviations of cure time and temperature overshoot. Kriging is utilised to construct a surrogate model of the cure substituting Finite Element (FE) simulation for computational efficiency reasons. The surrogate model is coupled with Monte Carlo and integrated into a stochastic multi-objective optimisation framework based on Genetic Algorithms. The results show a significant reduction of about 40% in temperature overshoot and cure time compared to standard cure profiles. This reduction is accompanied by a reduction in variability by about 20% for both objectives. This highlights the opportunity of replacing conventional cure schedules with optimised profiles achieving significant improvement in both process efficiency and robustness.