Efficient Methods for Structural Topology Optimization With Random Uncertainties

Speaker:             Shengfeng Zhu

Time:                  15:30, Jan. 21th.

Location:            SIST 2-415

Host:                   Prof. Qifeng Liao

Abstract:

Structural topology optimization with random material or boundary load requires significant computational costs in solving numerous random elastic systems, particularly in 3D. Based on the multimode representation of displacement and the Monte Carlo method for sampling, a phase field model is proposed for robust topology optimization. The well-posedness and truncation error estimates of the multimode Monte Carlo method have been discussed. Numerical examples are presented.       

Bio:

Zhu Shengfeng is a professor and doctoral supervisor at the School of Mathematical Sciences, East China Normal University. He received his Bachelor of Science and Ph.D. degrees in Computational Mathematics from Zhejiang University and conducted postdoctoral research at the Swiss Federal Institute of Technology Lausanne (EPFL). His research interests include numerical solutions of partial differential equations, shape optimization, and topology optimization.  He has published over 80 papers in journals such as NM, SINUM, SISC, JCP, CMAME, and IP.