Computational design in digital and bio fabrication

Publication Type:
Thesis
Issue Date:
2024
Full metadata record
Computational design holds promising applications in digital fabrication and biofabrication, offering innovative solutions to complex challenges in manufacturing and tissue engineering. In this thesis, we explore the application of computational design principles in these domains and present novel approaches to address two specific problems. In the realm of biofabrication, we introduce a physically-based simulation framework for the elastic-plastic fusion of 3D bioprinted spheroids. Spheroids are microtissues containing cells organized in a spherical shape that are used in biofabrication to create human tissue. Specifically, we employ bioprinting spheroids to fabricate heart tissues in our lab. However, achieving tissue with the desired geometrical shape requires understanding how they fuse after printing. Therefore, we have developed a physically-based simulation framework based on elastic-plastic solid and fluid continuum mechanics models using the smoothed particle hydrodynamics (SPH) method. This accurately captures the fusion process of spheroids and facilitates reverse engineering to achieve tissue with the desired shape. Our method can save significant time and costs compared to trial-and-error methods. Through extensive sensitivity and morphological analyses, we validate our simulations against in-vitro experiments, demonstrating their capability to predict and control tissue geometries. Shifting our focus to digital fabrication, we introduce the concept of "Ruling Patches," a method that approximates triangular meshes with developable patches driven by surface line features. Developable shapes find practical application in manufacturing, where surfaces of three-dimensional shapes can be efficiently constructed from flat patches. We demonstrate the effectiveness of our method in achieving aesthetic and manufacturable patch layouts, showcasing its superiority over existing techniques. Our work advances the understanding of complex phenomena in digital and biofabrication and opens new avenues for research and development in these fields. By providing efficient computational tools and frameworks, our contributions empower researchers and practitioners to tackle emerging challenges and drive innovation in manufacturing and tissue engineering.
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