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.

The photopolymerization of multifunctional acrylates leads to the formation of a complex and insoluble network due to cross-linking. This characteristic is a useful property for stereolithography applications, where solid parts of the desired shape are cured using a pre-determined energy exposure profile. Traditionally, the required energy exposure is determined using a critical energy--depth of penetration, or Ec--Dp, model. The parameters Ec and Dp, are usually fit to experimental data at a specific resin composition and cure intensity. As a result, since the Ec--Dp model does not explicitly incorporate cure kinetics, it cannot be used for a different set of process conditions without first obtaining experimental data at the new conditions. Thus, the Ec--Dp model does not provide any insight when a new process needs to be developed, and the best processing conditions are unknown. The kinetic model for multifunctional acrylate photopolymerization presented here is based on a set of ordinary differential equations (ODE), which can be used to predict part height versus exposure condition across varying resin compositions. Kinetic parameter information used in the model is obtained by fitting the model to double bond conversion data from Fourier Transform Infrared Spectroscopy (FTIR) measurements. An additional parameter, the critical conversion value, is necessary for determining the formation of a solid part of the desired height. The initial rate of initiation, Ri, combines all the factors that impact part height, and therefore, it is an important quantity that is required in order to find the critical conversion value. The critical conversion value is estimated using the Ri and Tgel value from microrheology measurements. Information about network connectivity, which can be used to get properties such as molecular weight, cannot be derived from models using traditional mass-action kinetics for the cross-linking system. Therefore, in addition to modeling the reaction using the ODE based model, the results from a statistical model based on Kinetic Monte Carlo (KMC) principles are also shown here. The KMC model is applicable in situations where the impact of chain length on the kinetics or molecular weight evolution is of interest. For the present project, the detailed information from network connectivity was not required to make part height predictions, and the conversion information from the ODE model was sufficient. The final results show that the kinetic ODE model presented here, based on the critical conversion value, captures the impact of process parameters such as initiator concentration, light intensity, and exposure time, on the final part height of the object. In addition, for the case of blanket cure samples, the part height predictions from the ODE model make comparable predictions to the Ec--Dp model. Thus, the ODE model presented here is a versatile tool that can be used to determine optimum operating conditions during process development.

The curing characteristics of photopolymer resin determine the relationship between the vat polymerization (VP) process parameters and the layer thickness, geometric accuracy, and surface quality of the 3D printed specimen. Dispersing filler material into the photopolymer resin changes its curing characteristics because the filler scatters and absorbs light, which modifies the curing reaction. However, the ability to cure photopolymer resin with high filler volume fraction is important to 3D print material specimens for specific engineering applications, e.g. structural polymer composite materials, electrical and thermal conductive materials, and ceramic materials for biological and high-temperature environments. We methodically measure the curing characteristics of diacrylate/epoxy photopolymer resin with dispersed glass microspheres. The experiments show that the curing depth, degree-of-cure, and surface roughness depend on both the light exposure dose and the filler fraction. We determine that the degree-of-cure increases with increasing filler fraction for constant exposure dose, and approaches 90% with increasing exposure dose, independent of the filler fraction. The geometric accuracy of the 3D printed specimens decreases with increasing exposure dose and with increasing filler volume fraction due to so-called profile broadening. Finally, we show that the average surface roughness of the 3D printed specimens decreases with increasing exposure dose and filler fraction. This work has implications for VP of photopolymer resins with high filler fraction. / Master of Science / Photopolymer resin is a gel-like liquid material that hardens (cures) into solid after absorbing light energy, and such a material is often used in the field of additive manufacturing (3D printing) to create complex geometry. Certain types of filler materials, such as metal powder or carbon fiber, can be added into the photopolymer resin to tailor the material properties, and thus, affects the curing behavior of photopolymer resin mixed with these filler materials. We conducted an experiment to understand how adding glass microspheres to a consumer grade photopolymer resin affects the process of creating 3D objects. This is important in the context of 3D printing engineered composite materials that derive their function from the organization and orientation of filler material in a matrix. To do this, we created many samples in the shape of a "VT" logo using the composite resin we made and measured their thickness (curing depth), degree-of-cure, surface roughness, and geometric accuracy, as a function of the amount of light energy being exposed to the resin (exposure dose) and the amount of the glass filler being added into the resin (filler fraction). We observed that when we increased the amount of light exposure, it resulted specimens that are thicker and more in degree of cure. Adding the glass filler to the liquid had mixed effects on the hardening process, because glass can scatter light and change how light travels within the resin. As a result, the printed objects became less accurate in shape and have smoother surface with increasing exposure dose and filler fraction, because more light is scattered off the designed curing profile and unintentionally cured the surrounding resin.

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