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Chaolin Song
Chaolin Song
Verified email at tongji.edu.cn
Title
Cited by
Cited by
Year
Optimization of cable pre-tension forces in long-span cable-stayed bridges considering the counterweight
C Song, R Xiao, B Sun
Engineering Structures 172, 919-928, 2018
562018
Adaptive reliability analysis for multi-fidelity models using a collective learning strategy
C Zhang, C Song, A Shafieezadeh
Structural Safety 94, 102141, 2022
332022
Value of information analysis in non-stationary stochastic decision environments: A reliability-assisted POMDP approach
C Song, C Zhang, A Shafieezadeh, R Xiao
Reliability Engineering & System Safety 217, 108034, 2022
312022
BUAK-AIS: Efficient Bayesian updating with active learning Kriging-based adaptive importance sampling
C Song, Z Wang, A Shafieezadeh, R Xiao
Computer Methods in Applied Mechanics and Engineering 391, 114578, 2022
252022
High-dimensional reliability analysis with error-guided active-learning probabilistic support vector machine: Application to wind-reliability analysis of transmission towers
C Song, A Shafieezadeh, R Xiao
Journal of Structural Engineering 148 (5), 04022036, 2022
212022
Improved method for shape finding of long-span suspension bridges
C Song, R Xiao, B Sun
International Journal of Steel Structures 20, 247-258, 2020
172020
Design and experimental study of a replaceable steel-UHPC composite bridge deck
R Xiao, C Song, B Sun, R Guo, H Chen
Structures 40, 1107-1120, 2022
162022
Cable force optimization of cable-stayed bridges: A surrogate model-assisted differential evolution method combined with B-Spline interpolation curves
C Song, R Xiao, B Sun, Z Wang, C Zhang
Engineering Structures 283, 115856, 2023
102023
An efficient structural reliability analysis method with active learning Kriging-assisted robust adaptive importance sampling
C Song, R Xiao, B Sun, C Zhang, Z Wang
Structures 52, 711-722, 2023
82023
Evolving reliability assessment of systems using active learning-based surrogate modelling
Y Zhu, Y Zhao, C Song, Z Wang
Physica D: Nonlinear Phenomena 457, 133957, 2024
62024
Active-learning Kriging-assisted robust design optimization of tuned mass dampers: Vibration mitigation of a steel-arch footbridge
C Song, R Xiao, Z Jiang, B Sun
Engineering Structures 303, 117502, 2024
52024
A new interpretation on structural reliability updating with adaptive batch sampling-based subset simulation
Z Wang, Y Zhao, C Song, X Wang, Y Li
Structural and Multidisciplinary Optimization 67 (1), 7, 2024
42024
Study on flexural and shear performance of ultra‐high performance concrete prefabricated pi‐beams
B Sun, R Luo, R Xiao, J Huang, C Song, J Wang, W Wang
Structural Concrete 24 (6), 7116–7134, 2023
22023
Reliability-assisted determination of partial factors for the design of main cables considering secondary stress effect
R Xiao, C Song, B Sun, W Dai, J Liu
Structures 48, 1479-1490, 2023
22023
GELF: A global error-based learning function for globally optimal adaptive reliability analysis
C Zhang, C Song, A Shafieezadeh
Structural Safety 109, 102464, 2024
12024
Simulation-free reliability analysis with importance sampling-based adaptive training physics-informed neural networks: Method and application to chloride penetration
C Song, R Xiao, C Zhang, X Zhao, B Sun
Reliability Engineering & System Safety 246, 110083, 2024
12024
Shear behavior of prestressed UHPC rectangular beams: experimental investigation and limit equilibrium state-based prediction method
B Sun, R Luo, C Quan, C Song, R Xiao
Archives of Civil and Mechanical Engineering 24 (1), 31, 2023
12023
Special Issue on Recent Challenges and Innovations in Long-Span Bridges
B Sun, R Xiao, C Song
Applied Sciences 13 (17), 9694, 2023
12023
An analytical method for out-of-plane stability assessment of network arch bridges
Z Jiang, R Xiao, C Song, B Sun, S Tong, Y Ma
Thin-Walled Structures 204, 112289, 2024
2024
Analytical Robust Design Optimization for Hybrid Design Variables: An Active-learning Methodology Based on Polynomial Chaos Kriging
C Song, A Shafieezadeh, R Xiao, B Sun
Reliability Engineering & System Safety, 110286, 2024
2024
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