Ai Shigang is a Professor and Ph.D. Supervisor at Institute of Advanced Structure Technology, Beijing Institute of Technology. He holds a Ph.D. in Engineering from South China University of Technology and completed his postdoctoral research at the State Key Laboratory for Turbulence and Complex Systems, Peking University. He has served as a visiting scholar at the School of Mechanical Engineering, Georgia Institute of Technology, and the High-Performance Computational Mechanics Laboratory, Texas A&M University. His research primarily focuses on the digital twin methodology for aerospace vehicles, deep learning-based finite element methods for aerospace structural imaging, and multi-scale numerical simulation methods for thermo-mechanical-chemical coupling in lightweight aerospace materials and structures.

As a principal investigator, he has led four projects funded by the National Natural Science Foundation of China (NSFC), one subproject of an NSFC Key Program, and one project under the Key Research and Development Program of the Ministry of Science and Technology. He has published over 70 SCI-indexed papers, with more than 2,100 citations on Google Scholar.

Digital twin methods for major defense equipment and structures;
Image-based finite element methods for advanced aerospace materials and structures;
Multiphysics coupling theories and numerical algorithms for thermal protection structures

[1] Shiyu Li, Xuanxin Tian, Qiubo Li, Shigang Ai, Advancing structural health monitoring: Deep learning-enhanced quantitative analysis of damage in composite laminates using surface strain field. Composites Science and Technology, Compos. Sci. Technol. 258, 110880 (2024). (IF:9.879).

[2] Xuanxin Tian, Heng Zhang, Zhaoliang Qu, Shigang Ai. An efficient finite element mesh generation methodology based on μCT images of multi-layer woven composites, Compos. Part A Appl. Sci. Manuf. 184, 108255 (2024). (IF:9.463).

[3] Yingying Song, Zhaoliang Qu, Haitao Liao, Shigang Ai, Material twins generation of woven polymer composites based on ResL-U-Net convolutional neural networks, Compos. Struct. 307, 116672 (2023). (IF:6.603).

[4] Guicheng Zhao, Zhonghe Jiang, Zhaoliang Qu, Huifeng Xi, Shigang Ai. Fracture characteristics and in-situ damage mechanism of PIP-C/SiC composites to various temperatures and loading velocities, Eng. Fract. Mech 286, 109300 (2023). (IF:4.898).

[5] Guicheng Zhao, Zhonghe Jiang, Huifeng Xi, Shigang Ai. Ultrahigh-temperature mechanical behavior and failure mechanisms of SiCf/SiC composites, Ceram. Int. 49(23), 39391-39399 (2023). (IF:5.532).

[6] Yihui Chen, Yanfei Chen, Dawei Wang, Shigang Ai, Generating 3D digital material twins for woven ceramic‐matrix composites from μCT images, J. Am. Ceram. Soc. 105(1), 481-497 (2022). (IF:4.186).

[7] Shigang Ai, Weili Song, Yanfei Chen. Stress field and damage evolution in C/SiC woven composites: Image-based finite element analysis and in situ X-ray computed tomography tests, J. Eur. Ceram. Soc. 41(4), 2323-2334 (2021). (IF:6.364).

[8] Yunong Zhao, Yanfei Chen, Shigang Ai and Daining Fang. A diffusion, oxidation reaction and large viscoelastic deformation coupled model with applications to SiC fiber oxidation, Int. J. Plasticity. 118, 173-189 (2019). (IF:9.4).

[9] Yunong Zhao, Yanfei Chen, Chunwang He, Shigang Ai, Daining Fang. A damage-induced short-circuit diffusion model applied to the oxidation calculation of ceramic matrix composites (CMCs), Compos. Part A Appl. Sci. Manuf. 127, 105621 (2019). (IF:9.463).