Methodologies for the optimization of fibre-reinforced composite structures with manufacturing uncertainties
Hamilton, Ryan Jason
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Fibre Reinforced Plastics (FRPs) have been used in many practical structural applications due to their excellent strength and weight characteristics as well as the ability for their properties to be tailored to the requirements of a given application. Thus, designing with FRPs can be extremely challenging, particularly when the number of design variables contained in the design space is large. For example, to determine the ply orientations and the material properties optimally is typically difficult without a considered approach. Optimization of composite structures with respect to the ply angles is necessary to realize the full potential of fibre-reinforced materials. Evaluating the fitness of each candidate in the design space, and selecting the most efficient can be very time consuming and costly. Structures composed of composite materials often contain components which may be modelled as rectangular plates or cylindrical shells, for example. Modelling of components such as plates can be useful as it is a means of simplifying elements of structures, and this can save time and thus cost. Variations in manufacturing processes and user environment may affect the quality and performance of a product. It is usually beneficial to account for such variances or tolerances in the design process, and in fact, sometimes it may be crucial, particularly when the effect is of consequence. The work conducted within this project focused on methodologies for optimally designing fibre-reinforced laminated composite structures with the effects of manufacturing tolerances included. For this study it is assumed that the probability of any tolerance value occurring within the tolerance band, compared with any other, is equal, and thus the techniques are aimed at designing for the worst-case scenario. This thesis thus discusses four new procedures for the optimization of composite structures with the effects of manufacturing uncertainties included.