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Xiang Huoyue

Supervisor of Master's Candidates

Supervisor of Doctorate Candidates

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Business Address:九里校区1号教学楼

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EMPLOYMENT & EDUCATION

12/2017 – Today

Associate Professor in Department of Bridge Engineering

School of Civil Engineering, Southwest Jiaotong University


09/2013 -12/2017

Lecturer in Department of Bridge Engineering

School of Civil Engineering, Southwest Jiaotong University


09/2010 - 09/2013(PhD)

Ph.D. student in School of Civil Engineering, Southwest Jiaotong University

  

RESEARCH INTERESTS

Train and Bridge Aerodynamics, Vibration of Cable, Surrogate Model

 

 PUBLICATION (Representative Journal Articles)

  • Jiajun He, Huoyue Xiang(*), Yongle Li, Bin Han. Aerodynamic performance of traveling road vehicles on a single-level rail-cum-road bridge under crosswind and train-induced wind[J]. Engineering Applications of Computational Fluid Mechanics, 2022.

  • Huoyue Xiang(*), Xiangfu Tian, Yongle Li, Min Zeng. Dynamic interaction analysis of high-speed maglev train and guideway with a control loop failure[J]. International Journal of Structural Stability and Dynamics, 2022.

  • Jiajun He, Huoyue Xiang(*), Wenyuan Ren, Yongle Li. Numerical simulation on aerodynamic characteristics of moving car under the train-induced wind[J]. Wind and Structures, 2021, 33(1): 41-54.

  • Yulong Bao, Huoyue Xiang(*), Yongle Li, Guangyang Hou. Dynamic effects of turbulent crosswinds on a suspended monorail vehicle-curved bridges coupled system[J]. Journal of Vibration and Control, doi.org/10.1177/1077546320988197, 2021.

  • Jiajun He, Chuanjin Yu, Yongle Li, Huoyue Xiang(*). Ultra-short term wind prediction with wavelet transform, deep belief network and ensemble learning. Energy Conversion and Management, 2020, 205:112418.

  • Yulong Bao, Huoyue Xiang(*), Yongle Li. A dynamic analysis scheme for the suspended monorail vehicle-curved bridge coupling system. Advances in Structural Engineering. 2020, DOI: 10.1177/1369433219900302.

  • Han Xu, Huoyue Xiang(*), Li Yongle, Wang Yichao. Predictions of vertical train-bridge response using artificial neural network-based surrogate model, Advances in Structural Engineering,2019, 22(12), 2712-2723.

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