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La bibliographie suivante contient toutes les publications répertoriées dans la base de données qui sont reliées à ce nom en tant qu'auteur, éditeur ou collaborateur.

  1. Wang, Senna / Cheng, Xiaowei / Li, Yi / Yang, Xiaohua / Zhang, Haoyou / Guo, Ruijie / Song, Xiaoyan / Liang, Zihan (2025): Assessing progressive collapse regions of reinforced concrete frame structures using Graph Convolutional Networks. Dans: Engineering Structures, v. 322 (janvier 2025).

    https://doi.org/10.1016/j.engstruct.2024.119076

  2. Guo, Xuekang / Li, Yi / McCrum, Daniel P. / Hu, Yutao / Bai, Zhun / Zhang, Haoyou / Li, Zhenyu / Wang, Xueji (2024): A reinforced concrete shear wall building structure subjected to internal TNT explosions: Test results and numerical validation. Dans: International Journal of Impact Engineering, v. 190 (août 2024).

    https://doi.org/10.1016/j.ijimpeng.2024.104950

  3. Song, Xiaoyan / Cheng, Xiaowei / Li, Yi / Guo, Ruijie / Zhang, Haoyou / Liang, Zihan / Wang, Senna (2024): A numerical model database for rapid seismic damage assessment of typical regular reinforced concrete frame structures in urban building clusters. Dans: Journal of Building Engineering, v. 90 (août 2024).

    https://doi.org/10.1016/j.jobe.2024.109392

  4. Cheng, Xiaowei / Zhang, Haoyou (2021): Numerical Modelling of Reinforced Concrete Slender Walls Subjected to Coupled Axial Tension–Flexure. Dans: International Journal of Concrete Structures and Materials, v. 15, n. 1 (7 janvier 2021).

    https://doi.org/10.1186/s40069-021-00471-y

  5. Wang, Senna / Cheng, Xiaowei / Li, Yi / Song, Xiaoyan / Guo, Ruijie / Zhang, Haoyou / Liang, Zihan (2023): Rapid visual simulation of the progressive collapse of regular reinforced concrete frame structures based on machine learning and physics engine. Dans: Engineering Structures, v. 286 (juillet 2023).

    https://doi.org/10.1016/j.engstruct.2023.116129

  6. Zhang, Haoyou / Cheng, Xiaowei / Li, Yi / He, Dianjin / Du, Xiuli (2023): Rapid seismic damage state assessment of RC frames using machine learning methods. Dans: Journal of Building Engineering, v. 65 (avril 2023).

    https://doi.org/10.1016/j.jobe.2022.105797

  7. Yang, Yingchun / Yang, Zhiliang / Cheng, Zhuxin / Zhang, Haoyou (2022): Effects of wet grinding combined with chemical activation on the activity of iron tailings powder. Dans: Case Studies in Construction Materials, v. 17 (décembre 2022).

    https://doi.org/10.1016/j.cscm.2022.e01385

  8. Cheng, Zhuxin / Yang, Yingchun / Zhang, Haoyou (2022): Interpretable ensemble machine-learning models for strength activity index prediction of iron ore tailings. Dans: Case Studies in Construction Materials, v. 17 (décembre 2022).

    https://doi.org/10.1016/j.cscm.2022.e01239

  9. Zhang, Haoyou / Cheng, Xiaowei / Li, Yi / Du, Xiuli (2022): Prediction of failure modes, strength, and deformation capacity of RC shear walls through machine learning. Dans: Journal of Building Engineering, v. 50 (juin 2022).

    https://doi.org/10.1016/j.jobe.2022.104145

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