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Structural optimization for 3D and 4D printing
3D printing is an umbrella term for a set of technologies that manufacture highly intricate and complex designs not feasible with traditional die-casting or injection molding methods. 4D printing builds on these technologies to create designs capable of changing their shape and functionalities via external stimulus. But despite their popularization in recent years, several limitations prevent greater integration of 3D and 4D printing into existing production lines. In this talk we report on some mathematical problems and results based on a structural topology optimization framework. Namely, for 3D printing we attempt to identify designs that are self-supporting and for 4D printing we attempt to discover the structure of a shape morphing design that would yield specific configurations after applying an external stimulus. This is joint work with Harald Garcke (Regensburg), Robert Nurnberg (Trento) and Andrea Signori (Milan).
Dr. Kei Fong LAM Recevied his Ph.D. from University of Warwick, U.K., in 2014, and after a 3-year postdoc at University of Regensburg, Germany, followed by a 3-year Research Assistant Professorship at Chinese University of Hong Kong, Dr. Kei Fong LAM joined Hong Kong Baptist University in 2020 as an Assistant Professor.
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