GAMES Webinar 2017-12期 | 陈德赛(麻省理工学院计算机科学与人工智能实验室)

【GAMES Webinar 2017-12期】




报告题目:Multiscale Methods for Fabrication Design


Modern manufacturing technologies such as 3D printing enable the design and fabrication of objects with extraordinary complexity. By arranging materials to form functional structures, a much wider range of physical properties can be achieved compared to the constituent materials. Computational design algorithms have previously been developed to automatically design objects with specified physical properties. However, many types of physical properties are still very challenging to optimize because predictive and efficient simulations are not available for problems such as high-resolution non-linear elasticity or dynamics with friction and impact. Even with problems such as linear elasticity where accurate simulation is available, the simulation resolutions is still orders of magnitudes below available printing resolutions. We propose to speed up simulation and inverse design process of fabricable objects by using multiscale methods. First, we construct a library of microstructures and their bulk material properties. Each bulk material property is stored using a small number of parameters. At runtime, fine element structures are replaced by coarse elements with precomputed material properties to speed up simulation. For validation, we performed design optimization and real-world fabrication for static and dynamic elastic objects. For 3D cubic-symmetric microstructures with linear material models, we also explored the space of achievable bulk parameters that we call the material property gamut. The gamut is represented as a level set. The level set representation allows us to use discrete and continuous sampling methods to push the structures to the limits of achievable material properties. It is also used in topology optimization algorithms to design functional objects using microstructures. Finally, the gamut also enables automatic discovery of microstructures families with extremal physical properties.






Liu, Ligang

刘利刚,中国科学技术大学教授,曾获得中国科学院“百人计划”、国家优青、杰青,从事计算机图形学研究。分别于1996年及2001年于浙江大学获得应用数学学士及博士学位。曾于微软亚洲研究院、浙江大学、哈佛大学工作或访问。曾获微软青年教授奖、陆增镛CAD&CG高科技奖一等奖、国家自然科学奖二等奖等奖项。负责创建了中科大《计算机图形学前沿》暑期课程及CCF CAD&CG专委图形学在线交流平台GAMES。

You may also like...