Before presenting the Sheet Moulding Compound (SMC) process, which is the primarily focus of this work, a literature survey is carried out to deal with fibre reinforced polymer composites in general. Then the first part of this work is presented and is primarily focused on experimental visualisation of the flow during mould closure of SMC. Circular plates are manufactured with industry scale equipment at close to production conditions. Special attention is given to the advancing flow front, for which the full complexity is captured by means of continuous high resolution close-up monitoring. From the experimental visualisation of the flow front, three phases are defined, namely squish, flow, and boiling. During the initial phase, squish, outer layers do not remain outer layers, the actual flow is very complex and air is likely to be entrapped. The governing process parameters during this phase are mould temperature, mould closing speed and amount of preheating in the mould. During the second phase, flow, the flow is stable and seemingly viscous. During the last phase, boiling, bubbles are observed in the low pressure region at the flow front, favouring the void content both internally and on the surface. Based on a chemical analysis including mass spectrometry and thermogravimetry, the gas is probably styrene. In the second part it is investigated if an inverse modelling approach by proportional regularisation can be applied to mimic the pressure distribution during compression moulding of SMC. The process is simulated with Computational Fluid Dynamics and the mastered parameter, the viscosity of the SMC, is allowed to vary as a function of time. A grid refinement study of two ways to model the process and for three fictitious pressure scenarios yields that the suggested approach work very well and that the numerical errors can be minimised as desired. Finally a validation process is carried out showing that to get quantitative agreements of the whole pressure field more advanced viscosity models must be used. In order to verify the inverse modelling system have to important errors are studied. Firstly the error between calculated and experimental pressure, secondly the discretisation error due to solving the problem for many small volumes. Both have to be minimized and the later is studied with Richardson's extrapolation. The conclusions are that the initial guess is very important for predictions in the beginning of the simulation.
Luleå: Luleå tekniska universitet, 2005. , 41 p.