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This thesis explores the use of numerical methods to simulate composite manufacturing processes. These simulation methods are more effective at conducting manufacturing trials for evaluating the material and processing parameters for a given process. This helps to reduce the risk of manufacturing processes, whilst also reducing the cost and time of manufacturing. This work will focus on dry fabric vacuum forming and resin infusion processes, with the use of two separate case studies. The first case study is of a vacuum preforming process of a dry non-crimp fabric and the second is the resin infusion of a large-scale dry preform. Both case studies set up manufacturing process simulations using commercial off the shelf software (PAM-RTM and PAM-Form by ESI) and compare the results of the simulations against the results of manufacturing trials. The vacuum preforming process compares the shear angles found within the part, the predicted part edge and the size, location and type of defects induced through the manufacturing process. The large-scale resin infusion process compares the resin flow front after a set time, as well as information from resin arrival, flow rate and flow pressure sensors. This work helps to build confidence from industry in the simulation tools available by quantifying the error associated with these tools. The simulations set up within this thesis are then used to perform a sensitivity study, which aims to determine which material parameters are driving the outputs of the manufacturing process. For the vacuum preforming process, the shear angles and defects are used as the main outputs of the process, and for the resin infusion process, the filling time is investigated as the main process output. The results of this work will help to make decisions and prioritise material and processing parameters in future work.

Any composite manufacturing method requires an application of a carefully designed consolidation process to ensure the suppression of voids in the laminate, establish bonding in laminate layers and prevent dimensional or fibre-path defects. The optimisation of consolidation processes relies on the characterisation of the composite precursors’ deformability. There are multiple mechanisms occurring in consolidation and various experimental programmes have been suggested in the literature to describe these mechanisms and deduce relevant material properties. The selection of a testing methodology often relies on an initial hypothesis or prior knowledge regarding the deformation modes. This may be a source of significant errors. This research poses questions on the testing rationales, on subjectivity in material testing and on how data-rich programmes should be designed. The proposed solution to the consolidation characterisation problem is a real-time adaptive testing strategy that enables a “conversation with the material” – flexible autonomous steering of a testing programme reacting on the obtained output. Such system is implemented within this research and is called adaptive consolidation sensor framework. The system’s algorithm is set to analyse composite precursor’s feedback to compression in real time and to track characteristic signatures relevant to existing consolidation models. Based on that feedback the framework formulates a load programme for the test in a reactive manner. The developed testing system focuses on the identification of the underlying physical mechanisms rather than material properties identification in a rightly or wrongly assumed resin flow mode. To validate the proposed testing approach, a series of characterisation experiments for different material systems was performed. The obtained results highlight a way forward in terms of rethinking experiments for materials used in manufacturing and beyond.

Conventional fibre polymer composite materials consist of a single matrix system for a whole part and are selected on the dominant requirements of the part. A multi-matrix composite would provide an expanded design space for a composite part. However, there are few processes available to realise such a composite and these rely on modified forms of resin transfer moulding. These processes require active venting using an expensive vacuum system and the quality is reliant on bag quality. This research is devoted to developing a foundational principle for a processing strategy that uses the localised introduction of resin combined with an out-of-bag consolidation process containing a preheating stage that can form a multi-matrix composite. The resin flow in local deposition and consolidation processes is determined by a complex interplay between the resin and preform. Hence the chosen resin and fabric were characterised extensively. A range of viscosity-tailored consolidation schemes was implemented using a setup to estimate the in-line viscosity using the rheo-kinetics of the fast-curing resin system. By initiating the consolidation pressure at a higher resin viscosity, the voids were found to be suppressed. A simplified model to capture the dominant mechanisms during consolidation was developed. The dominant flow transitioned from a 2D yarn-scale to macro-scale flow on increasing the activation viscosity. The increased resin pressure associated with high resin viscosity during consolidation was found to be a dominating factor in reducing the voids. The model was then used to develop a simple analytical design tool for tailoring the consolidation parameters to minimise the void content. A feasibility study was conducted on combining different matrices to improve the mechanical performance of composites in an open hole tension test. The use of high stiffness carbon nanotube modified resin to locally manipulate the region around the hole increased the strength of the

Any composite manufacturing method requires an application of a carefully designed consolidation process to ensure the suppression of voids in the laminate, establish bonding in laminate layers and prevent dimensional or fibre-path defects. The optimisation of consolidation processes relies on the characterisation of the composite precursors’ deformability. There are multiple mechanisms occurring in consolidation and various experimental programmes have been suggested in the literature to describe these mechanisms and deduce relevant material properties. The selection of a testing methodology often relies on an initial hypothesis or prior knowledge regarding the deformation modes. This may be a source of significant errors. This research poses questions on the testing rationales, on subjectivity in material testing and on how data-rich programmes should be designed. The proposed solution to the consolidation characterisation problem is a real-time adaptive testing strategy that enables a “conversation with the material” – flexible autonomous steering of a testing programme reacting on the obtained output. Such system is implemented within this research and is called adaptive consolidation sensor framework. The system’s algorithm is set to analyse composite precursor’s feedback to compression in real time and to track characteristic signatures relevant to existing consolidation models. Based on that feedback the framework formulates a load programme for the test in a reactive manner. The developed testing system focuses on the identification of the underlying physical mechanisms rather than material properties identification in a rightly or wrongly assumed resin flow mode. To validate the proposed testing approach, a series of characterisation experiments for different material systems was performed. The obtained results highlight a way forward in terms of rethinking experiments for materials used in manufacturing and beyond.

Conventional fibre polymer composite materials consist of a single matrix system for a whole part and are selected on the dominant requirements of the part. A multi-matrix composite would provide an expanded design space for a composite part. However, there are few processes available to realise such a composite and these rely on modified forms of resin transfer moulding. These processes require active venting using an expensive vacuum system and the quality is reliant on bag quality. This research is devoted to developing a foundational principle for a processing strategy that uses the localised introduction of resin combined with an out-of-bag consolidation process containing a preheating stage that can form a multi-matrix composite. The resin flow in local deposition and consolidation processes is determined by a complex interplay between the resin and preform. Hence the chosen resin and fabric were characterised extensively. A range of viscosity-tailored consolidation schemes was implemented using a setup to estimate the in-line viscosity using the rheo-kinetics of the fast-curing resin system. By initiating the consolidation pressure at a higher resin viscosity, the voids were found to be suppressed. A simplified model to capture the dominant mechanisms during consolidation was developed. The dominant flow transitioned from a 2D yarn-scale to macro-scale flow on increasing the activation viscosity. The increased resin pressure associated with high resin viscosity during consolidation was found to be a dominating factor in reducing the voids. The model was then used to develop a simple analytical design tool for tailoring the consolidation parameters to minimise the void content. A feasibility study was conducted on combining different matrices to improve the mechanical performance of composites in an open hole tension test. The use of high stiffness carbon nanotube modified resin to locally manipulate the region around the hole increased the strength of the