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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. Zhao, Li-ming / Zhang, Wen-Ming / Wang, Zhi-wei / Ge, Yao-Jun / Jiang, Nan (2024): Nonlinear unsteady aerodynamic forces prediction and aeroelastic analysis of wind-induced bridge response at multiple wind speeds: A deep learning-based reduced-order model. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 254 (November 2024).

    https://doi.org/10.1016/j.jweia.2024.105905

  2. Zhang, Zhe-hong / Zhang, Wen-Ming / Wang, Zhi-wei (2024): An analytical method for thermal behavior analysis of long-span suspension bridges: Based on elastic catenary cable and gradient optimization. In: Engineering Structures, v. 321 (Dezember 2024).

    https://doi.org/10.1016/j.engstruct.2024.119013

  3. Zhang, Wen-Ming / Zhang, Zhe-hong / Wang, Zhi-wei / Chen, Bin (2024): Temperature analysis and prediction for road-rail steel truss cable-stayed bridges based on the structural health monitoring. In: Engineering Structures, v. 315 (September 2024).

    https://doi.org/10.1016/j.engstruct.2024.118476

  4. Wang, Zhi-wei / Lu, Xiao-fan / Zhang, Wen-Ming / Fragkoulis, Vasileios C. / Zhang, Yu-Feng / Beer, Michael (2024): Deep learning-based prediction of wind-induced lateral displacement response of suspension bridge decks for structural health monitoring. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 247 (April 2024).

    https://doi.org/10.1016/j.jweia.2024.105679

  5. Wang, Zhi-wei / Lu, Xiao-fan / Zhang, Wen-Ming / Fragkoulis, Vasileios C. / Beer, Michael / Zhang, Yu-Feng (2023): Deep learning-based reconstruction of missing long-term girder-end displacement data for suspension bridge health monitoring. In: Computers & Structures, v. 284 (August 2023).

    https://doi.org/10.1016/j.compstruc.2023.107070

  6. Wang, Zhi-wei / Li, An-dong / Zhang, Wen-Ming / Zhang, Yu-Feng (2022): Long-term missing wind data recovery using free access databases and deep learning for bridge health monitoring. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 230 (November 2022).

    https://doi.org/10.1016/j.jweia.2022.105201

  7. Wang, Zhi-wei / Zhang, Wen-Ming / Zhang, Yu-Feng / Liu, Zhao (2022): Temperature Prediction of Flat Steel Box Girders of Long-Span Bridges Utilizing In Situ Environmental Parameters and Machine Learning. In: Journal of Bridge Engineering (ASCE), v. 27, n. 3 (März 2022).

    https://doi.org/10.1061/(asce)be.1943-5592.0001840

  8. Wang, Zhi-wei / Zhang, Wen-Ming / Zhang, Yu-Feng / Liu, Zhao (2021): Circular-linear-linear probabilistic model based on vine copulas: An application to the joint distribution of wind direction, wind speed, and air temperature. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 215 (August 2021).

    https://doi.org/10.1016/j.jweia.2021.104704

  9. Zhang, Wen-Ming / Lu, Xiao-fan / Wang, Zhi-wei / Liu, Zhao (2021): Effect of the main cable bending stiffness on flexural and torsional vibrations of suspension bridges: Analytical approach. In: Engineering Structures, v. 240 (August 2021).

    https://doi.org/10.1016/j.engstruct.2021.112393

  10. Zhang, Wen-Ming / Yang, Chao-yu / Wang, Zhi-wei / Liu, Zhao (2019): An analytical algorithm for reasonable central tower stiffness in the three-tower suspension bridge with unequal-length main spans. In: Engineering Structures, v. 199 (November 2019).

    https://doi.org/10.1016/j.engstruct.2019.109595

  11. Zhang, Wen-Ming / Wang, Zhi-wei / Liu, Zhao (2020): Joint Distribution of Wind Speed, Wind Direction, and Air Temperature Actions on Long-Span Bridges Derived via Trivariate Metaelliptical and Plackett Copulas. In: Journal of Bridge Engineering (ASCE), v. 25, n. 9 (September 2020).

    https://doi.org/10.1061/(asce)be.1943-5592.0001608

  12. Wang, Zhi-wei / Zhang, Wen-Ming / Tian, Gen-min / Liu, Zhao (2020): Joint values determination of wind and temperature actions on long-span bridges: Copula-based analysis using long-term meteorological data. In: Engineering Structures, v. 219 (September 2020).

    https://doi.org/10.1016/j.engstruct.2020.110866

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