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Volume 51 Issue 4
Nov.  2021
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Article Navigation >  Advances in Mechanics  > 2021  >  51(4): 865-900
Zhang J M, Yang W D, Li Y. Application of artificial intelligence in composite materials. Advances in Mechanics, 2021, 51(4): 865-900 doi: 10.6052/1000-0992-21-019
Citation: Zhang J M, Yang W D, Li Y. Application of artificial intelligence in composite materials. Advances in Mechanics, 2021, 51(4): 865-900 doi: 10.6052/1000-0992-21-019
shu

Application of artificial intelligence in composite materials

doi: 10.6052/1000-0992-21-019

  • School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai 200092, China

More Information
  • Corresponding author: 20501@tongji.edu.cn
  • Received Date: 2021-04-15
  • Accepted Date: 2021-07-20
    • Available Online: 2021-07-26
  • Publish Date: 2021-11-26
    Abstract
  • Composite materials have become the major materials of light-weight structure due to their light weight, high strength, high modulus, and strong designability. However, as the component, structure and requirements of capability become increasingly complex, traditional research methods based on experiment, theoretical modeling and numerical simulation meet lots of new problems in the properties prediction, design optimization, manufacturing and processing of composite materials. Insufficient experimental observation, lacking theoretical model, constrained numerical simulation and difficult conclusion validation have seriously restricted the development of advanced composite materials in the future-oriented engineering. Instead of the mathematical models used by mechanics, data-driven models are used in the Artificial Intelligence. It directly establishes the complex relationship between variables from high-dimensional and high-throughput data, then captures the laws that are difficult to be discovered by traditional mechanical method, shows natural advantages in simulation, prediction, optimization in complex systems. It has become the development trend in the field of composite materials to find new solutions to the problems faced by traditional methods through Artificial Intelligence. In this paper, the status of properties prediction, design optimization, manufacturing and health monitoring is introduced. The future development direction of this field is discussed.

     

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