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Die folgende Bibliografie enthält alle in dieser Datenbank indizierten Veröffentlichungen, die mit diesem Namen als Autor, Herausgeber oder anderweitig Beitragenden verbunden sind.

  1. Chen, Peiqi / Liu, Zihao / Zhou, Xiaojie / Xu, Shuo / Wang, Junyi (2024): Research on Work Performance of Monolithic Precast Concrete Shear Walls with Post-Cast Epoxy Resin Concrete. In: Buildings, v. 14, n. 6 (19 Juni 2024).

    https://doi.org/10.3390/buildings14061675

  2. Wang, Junyi / Wu, Dazhi / Chen, Keyu / Mao, Ningning / Zhang, Zhenying: Effect of Ca content on the synthesis and properties of FA-GGBFS geopolymer: combining experiments and molecular dynamics simulation. In: Journal of Building Engineering.

    https://doi.org/10.1016/j.jobe.2024.109908

  3. Xu, Decheng / Hong, Weiqiang / Hu, Bing / Zhang, Tianxu / Chen, Dongliang / Yan, Zihao / Yao, Xiaomeng / Zhang, Xinyi / Zhao, Yunong / Sun, Taoran / Zhang, Chuanzhao / Pan, Mingqi / Ruan, Xiaoyun / Yan, Ruishen / Wang, Junyi / Guo, Xiaohui (2024): River valley-inspired, high-sensitivity, and rapid-response capacitive three-dimensional force tactile sensor based on U-shaped groove structure. In: Smart Materials and Structures, v. 33, n. 3 (2 Februar 2024).

    https://doi.org/10.1088/1361-665x/ad223c

  4. Siahkouhi, Mohammad / Wang, Junyi / Han, Xiaodong / Aela, Peyman / Ni, Yi-Qing / Jing, Guoqing (2023): Railway ballast track hanging sleeper defect detection using a smart CNT self-sensing concrete railway sleeper. In: Construction and Building Materials, v. 399 (Oktober 2023).

    https://doi.org/10.1016/j.conbuildmat.2023.132487

  5. Niu, Shilei / Wang, Zuocai / Wang, Junyi / Wang, Donghui / Sun, Xiaotong (2023): Experimental investigation on flexural performance of polyester polyurethane concrete steel bridge deck composite structure. In: Case Studies in Construction Materials, v. 18 (Juli 2023).

    https://doi.org/10.1016/j.cscm.2023.e01915

  6. Aela, Peyman / Wang, Junyi / Yousefian, Kaveh / Fu, Hao / Yin, Zhen-Yu / Jing, Guoqing (2022): Prediction of crushed numbers and sizes of ballast particles after breakage using machine learning techniques. In: Construction and Building Materials, v. 337 (Juni 2022).

    https://doi.org/10.1016/j.conbuildmat.2022.127469

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