Topology Optimization Considering Constructability of Truss Structures and Manufacturability of Composite Components
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Topology optimization is a mathematical process that systematically searches for the 'best possible' solution to a specific engineering design problem. In discrete domains (such as truss or frame structures), topology optimization is used to determine optimal layout of structural members, while in continuum domains it is used to determine optimal material distribution. Due to its free-form and systematic nature, topology optimization has become a powerful computational tool in engineering design that is capable of discovering solutions that are both innovative and high performance. Despite its potential capabilities, topology optimization has a tendency to produce structural solutions that are 'suboptimal' when considering constructability and manufacturability of solutions. This dissertation aims to address this fundamental challenge by proposing new topology optimization design methods and algorithms that consider constructability and manufacturability in the design of structures. When optimizing structural layout in discrete design domains, topology optimization has a tendency to design structures that are topologically complex, which drives construction costs significantly higher, potentially overtaking cost savings from reduced material usage and enhanced system performance. This dissertation examines opportunities to incorporate constructability metrics directly into the topology optimization of structures, such that the designer gains control and may explore potential constructability-performance tradeoffs. In particular, several new algorithms are proposed that incorporate cost metrics associated with section selection, including maximum member sizes, section repeatability, and connection complexity. In continuum design domains, topology optimization is traditionally employed with an underlying assumption that structures have a continuous distribution and connectivity of material phases. Many engineering components and materials, however, gain strength and functionality through strategic placement of reinforcing objects. Often these objects are selected 'off-the-shelf' and thus come in fixed size and shapes, and are not permitted to overlap due to physical geometry or functionality requirements. This dissertation investigates the use of Discrete Object Projection (DOP) for optimizing the distribution of reinforcing objects within a structure and extends the DOP approach to simultaneously optimize the component topology. The approach is then tailored to the properties of a novel 3D printer developed at NASA capable of printing polymer selectively reinforced with carbon nanotube yarn.