报告人： Dr.Xiaojia Shelly Zhang

时  间： 2019年5月31日（周五）12点

地  点： 力学楼434室

主持人： 唐少强 教授

内容简介：

Topology optimization is a computational design tool for finding optimal layouts of structures and material microstructures, which can be subsequently realized by additive manufacturing (AM). However, most work in this field has been restricted to single material with linear material behavior, limited volume constraint settings, and a single load case. To address these issues, we propose an efficient multi-material topology optimization formulation considering material nonlinearity. The proposed formulation handles an arbitrary number of candidate materials with flexible material properties, features freely specified material layers, and includes a generalized volume constraint setting. To efficiently handle such arbitrary volume constraints, we derive a novel design update scheme that performs robust updates of the design variables associated with each volume constraint independently. We show that the update of design variables in each volume constraint only depends on the corresponding Lagrange multiplier. To obtain designs under many load cases, we also present a randomized approach that efficiently optimizes structures under hundreds of load cases. This approach only uses 5 or 6 stochastic sample load cases, instead of hundreds, to obtain similar optimized designs (for both continuum and truss topology optimization). Through examples using combinations of various materials, we demonstrate that the proposed topology optimization frameworks with the aforementioned update scheme and randomized algorithm lead to design tools that not only find the optimal topology but also select the proper type and local distribution, which could strengthen the connection between topology optimization and AM.

报告人简介：

Dr. Xiaojia Shelly Zhang is an Assistant Professor at the Department of Civil and Environmental Engineering and Department of Mechanical Science and Engineering in the University of Illinois at Urbana Champaign. Dr. Zhang holds a B.S. degree and a M.S. degree in Civil Engineering from University of Illinois at Urbana Champaign and a Ph.D. degree in Civil Engineering from Georgia Tech. She received the Best Ph.D. Thesis Awards from the CEE school in 2018 and from the international scientific research honor society Sigma Xi in 2019. Her research focuses on exploring topology optimization, stochastic programming, and additive manufacturing to develop resilient, smart, sustainable, and innovative engineering infrastructure and materials for applications at different scales, from as large as high-rise buildings to as small as material microstructures.

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