Advanced structural material design based on simulation and data-driven method

LI Xiang; YAN Ziming; LIU Zhanli; ZHUANG Zhuo

doi:10.6052/1000-0992-20-012

Volume 51 Issue 1

Mar. 2021

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LI Xiang, YAN Ziming, LIU Zhanli, ZHUANG Zhuo. Advanced structural material design based on simulation and data-driven method[J]. Advances in Mechanics, 2021, 51(1): 82-105. doi: 10.6052/1000-0992-20-012

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LI Xiang, YAN Ziming, LIU Zhanli, ZHUANG Zhuo. Advanced structural material design based on simulation and data-driven method[J]. Advances in Mechanics, 2021, 51(1): 82-105. doi: 10.6052/1000-0992-20-012

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Advanced structural material design based on simulation and data-driven method

doi: 10.6052/1000-0992-20-012

LI Xiang^1,2,
YAN Ziming¹,
LIU Zhanli^{1,*
,
,},
ZHUANG Zhuo¹

¹ Applied Mechanics Lab., Dept. of Engineering Mechanics, School of Aerospace, Tsinghua University, Beijing 100084, China
² School of Information Science and Technology, Hainan Normal University, Haikou 570206, China

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Corresponding author: LIU Zhanli
Received Date: 2020-05-29
Publish Date: 2021-03-25

Abstract

Abstract

Advanced structural materials have received extensive attention in the field of materials and structural design in recent years. These materials generally achieve excellent performances via structural design at multiple length-scales. In the early material design, some researchers created reasonable mathematical and mechanical models from the natural topologies; some researchers established bionic mechanical models based on the structural and functional characteristics of biological systems. Nevertheless, it isn't easy to obtain the optimal designs only based on ingenious design. To traverse the design space to search for the optimal design by trial and error is also not practical. For these reasons, the topology optimization method has been successfully applied to the design of advanced structural materials such as phononic crystals, cellular materials, etc. However, the existing topology optimization methods still have challenges in achieving accurate reverse designs. Data-driven methods can establish complex relationships of multi-dimensional variables, and they can reveal mechanical mechanisms and laws that are difficult to be discovered by traditional methods. Hence, this paper systematically reviews the development of advanced structural material design methods. Various mainstream design methods are compared and illustrated. The status of intelligent design of advanced structural materials based on data-driven methods is introduced. The prospect of this research area is discussed.
- structural materials,
- metamaterials,
- material design,
- data-driven,
- machine learning

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References(185)

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