Abstract
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.
| Date of Award | 20 Jun 2023 |
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| Original language | English |
| Awarding Institution |
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| Supervisor | James Kratz (Supervisor) |