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Design detail control strategies for structural topology optimization
Xin Yan
Postdoc, Tsinghua University
Dr. Xin Yan is an architect with a comprehensive background in mechanics and computer sciences. Currently, he is a post-doctoral researcher at Future Lab at Tsinghua University. He received his Ph.D. in Architecture and Urban Design and Master of Architectural and Civil Engineering from the University of Chinese Academy of Sciences (UCAS) in 2022 and 2016 respectively. He graduated from Theoretical and Applied Mechanics at the University of Science and Technology of China (USTC) in 2013. In 2019, he also carried out his research work on Structural Topology Optimization at the Centre for Innovative Structure and Material (CISM) at RMIT University, Australia.
Besides academic publications, Dr. Yan has participated in several exhibitions, such as IASS Barcelona, Shenzhen Urban Biennale, Beijing Design Week, and Digital FUTURES in Shanghai. Dr. Yan also received the Grand Prix Design Paris (GPDP) - Gold Award, MUSE Design Award, and IAI Architectural Design Adward in 2021, First Prize in the 3rd Chinese Structural Optimization and Additive Manufacturing Competition in 2019, and the 5th International 3D Printing and Design Competition in 2020. His research interests include digital humanities and smart cities, structural form optimization and design, Intelligent fabrication, complex architectural geometric and construction optimization, and architectural tectonic history.
Abstract
With the ability to generate forms with high efficiency and elegant geometry, topology optimization has been increasingly used in architectural and structural designs. However, the conventional topology optimization techniques aim at achieving the structurally most efficient solution without any potential for architects or designers to control the design details. This presentation introduces several strategies based on Bi-directional Evolutionary Structural Optimization (BESO) method to artificially pre-design the topologically optimized structures. These strategies have been successfully applied in the computational morphogenesis of various structures for solving practical design problems. The results demonstrate that the developed methodology can provide the designer with structurally efficient and topologically different solutions according to their proposed designs. This work establishes a general approach to integrating objective topology optimization methods with subjective human design preferences, which has great potential for practical applications in the architecture and engineering industry.
Host
Wei Wu
Wei Wu is a designer and computational artist with a Master's degree in Design Studies from Harvard University Graduate School of Design. She operates at the intersection of design and emerging technologies, producing work that encompasses robotic installations, interactive media art, and extended reality design.
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