activity
20182022
most citedAn efficient and easy-to-extend Matlab code of the Moving Morphable Component (MMC) method for three-dimensional topology optimization

120 citations · 160 across the 5 of their papers we have counts for

collaborators

6 papers

math.OC2022

Data-driven Topology Optimization (DDTO) for Three-dimensional Continuum Structures

Yunhang Guo, Zongliang Du, Lubin Wang +6

Developing appropriate analytic-function-based constitutive models for new materials with nonlinear mechanical behavior is demanding. For such kinds of materials, it is more challe…

math.OC2022

A sequential linear programming (SLP) approach for uncertainty analysis-based data-driven computational mechanics

Mengcheng Huang, Chang Liu, Zongliang Du +2

In this article, an efficient sequential linear programming algorithm (SLP) for uncertainty analysis-based data-driven computational mechanics (UA-DDCM) is presented. By assuming t…

math.OC202231 cited

Topology optimization on complex surfaces based on the moving morphable component (MMC) method and computational conformal mapping (CCM)

Wendong Huo, Chang Liu, Zongliang Du +3

In the present paper, an integrated paradigm for topology optimization on complex surfaces with arbitrary genus is proposed. The approach is constructed based on the two-dimensiona…

math.OC2022120 cited

An efficient and easy-to-extend Matlab code of the Moving Morphable Component (MMC) method for three-dimensional topology optimization

Zongliang Du, Tianchen Cui, Chang Liu +3

Explicit topology optimization methods have received ever-increasing interest in recent years. In particular, a 188-line Matlab code of the two-dimensional (2D) Moving Morphable Co…

cs.LG20219 cited

A mechanistic-based data-driven approach to accelerate structural topology optimization through finite element convolutional neural network (FE-CNN)

Tianle Yue, Hang Yang, Zongliang Du +4

In this paper, a mechanistic data-driven approach is proposed to accelerate structural topology optimization, employing an in-house developed finite element convolutional neural ne…

cond-mat.mtrl-sci2018

The Role of Grain Boundaries under Long-Time Radiation

Yichao Zhu, Jing Luo, Xu Guo +2

Materials containing a high proportion of grain boundaries offer significant potential for the development of radiation-resistent structural materials. However, a proper understand…