Yong Li, PhD, PEng

Area of Study / Keywords

Structural and Earthquake Engineering Structural Reliability & Risk Finite Element Probabilistic Structural Health Monitoring AI-assisted Structural Engineering Civil Structures (Bridges & Buildings) Energy Infrastructure (Pipelines & Wind Turbine)

About

Education:

• Ph.D., Structural Engineering, University of California, San Diego, USA
• M.A., Applied Mathematics, University of California, San Diego, USA
• M.S., Civil Engineering, Tsinghua University, Beijing, China
• B.S., Civil Engineering, Beihang University, Beijing, China

Professional Experience:

• Associate Professor (2023-), University of Alberta, Edmonton, Canada
• Assistant Professor(2017-2023), University of Alberta, Edmonton, Canada
• Postdoctoral Researcher (2015-2016), University of California, San Diego, USA
• Graduate Researcher (2009-2014), University of California, San Diego, USA

Research

Research Interest:

Dr. Li is fascinated in developing and applying (1) mechanics- and/or data-based models, and (2) probabilistic and machine learning methods to engineering risk/reliability problems in the field of structural engineering. This serves to assist decision-making in the process of probability-based design, retrofit, health monitoring, and maintenance of a wide range of structures (e.g., bridges, concrete/masonry/steel/timber buildings, pipelines, wind turbines, etc.) in the face of uncertainty. He is also interested in inverse engineering problems (e.g., structural design optimization, nonlinear system identification using field-recorded and experimental data). Specifically, his research interests include:

• Structural dynamics and earthquake engineering
• Stochastic modeling of loads and hazards
• Computational mechanics & finite element (FE) method
• Structural deterioration or damage modeling
• Structural reliability-based design and probabilistic performance evaluation (e.g., bridges, concrete/masonry/steel/timber buildings, pipelines)
• Risk analysis and management (e.g., earthquake, landslide, fire)
• Probabilistic structural health monitoring
• Nonlinear system identification (FE model updating)
• Machine learning and artificial intelligence (AI)-assisted decision making

Selected Refereed Journal Publications (google scholar):

1. Huang, C., Li, Y., Gu, Q., and Liu., J., "Machine Learning–Based Hysteretic Lateral Force-Displacement Models of Reinforced Concrete Columns," Journal of Structural Engineering 148 (3), 04021291, 2022
2. Bartaula, D., Adeeb, S., and Li, Y., "Stochastic Filter-based Fatigue Crack Growth Prediction for Pipelines considering Unknown Model Parameters and Measurement Uncertainty," Journal of Pipeline Science and Engineering, 2021
3. Liu, J., Huang, L., Wu, Z., Tomlinson, D., Cruz-Noguez, C., Alexander J., Adeeb, S., and Li, Y., "Development of Enhanced Fiber Beam Element with Multi-axial Material Constitutive Models for Reinforced/prestressed Concrete Beams," Engineering Structures 248, 113289, 2021
4. Li, Y., Castiglione, J., Astroza, R., and Chen, Y., "Real-time Thermal Dynamic Analysis of a House using RC Models and Joint State-parameter Estimation," Building and Environment 188, 107184, 2021.
5. Zeng, B., Li, Y., and Noguez, CC., "Modeling and Parameter Importance Investigation for Simulating In-plane and Out-of-plane Behaviors of Un-reinforced Masonry Walls," Engineering Structures 248, 113233, 2021
6. Zheng, Q., Abdelmoety, AK, Li, Y., Kainat, M., Yoosef-Ghodsi, N., and Adeeb, A., "Reliability Analysis of Intact and Defected Pipes for Internal Pressure Related Limit States Specified in CSA Z622:19," International Journal of Pressure Vessels and Piping 192, 104411, 2021.
7. Abdelmoety, AK., Zheng, Q., Li, Y., Kainat, M., Yoosef-Ghodsi, N., Adeeb, S., "Probability of Failure Associated with Design and Safety Factors for Intact and Corroded Pipes under Internal Pressure," Journal of Pipeline Systems Engineering and Practice 12 (3), 04021010, 2021
8. Abdollahi, A., Moghaddam, M., Monfared, S.A., Rashki, M., and Li, Y., "Subset Simulation Method including Fitness-based Seed Selection for Reliability Analysis," Engineering with Computers 37 (4), 2689-2705, 2021.
9. Abdollahi, A., Moghaddam, M,, Monfared, S.A., Rashki, M., and Li, Y., "A Refined Subset Simulation for the Reliability Analysis using the Subset Control Variate," Structural Safety, 87, 102002, 2020.
10. Astroza, R., Barrientos, N., Li, Y., Flores, E., and Z Liu, "Bayesian Updating of Complex Nonlinear FE Models with High-dimensional Parameter Space using Heterogeneous Measurements and a Batch-recursive Approach," Engineering Structures 201, 109724, 2019.
11. Su, L., Wan, H.P., Abtahi, S., Li, Y., and Ling, X.Z., "Dynamic Response of Soil–pile–structure System subjected to Lateral Spreading: Shaking Table Test and Parallel Finite Element Simulation," Canadian Geotechnical Journal 57 (4), 497-517, 2020.
12. Li, Y.., Conte, J.P., and Gill, P., "Probabilistic Performance Based Optimum Seismic Design Framework: Illustration and Validation," Computer Modeling in Engineering & Sciences 120 (3), 517-543, 2019.
13. Wang, Z., Chen, Y. and Li, Y., "Development of RC Model for Thermal Dynamic Analysis of Buildings through Model Structure Simplification," Energy and Buildings 195, 51-67, 2019.
14. Ghazizadeh, S., Cruz-Noguez, C.A., and Li, Y., "Numerical Study of Hybrid GFRP-steel Reinforced Concrete Shear Walls and SFRC Walls," Engineering Structures 180, 700-712, 2019
15. Gu, Q., Wang, L., Li, Y., Deng, X., and Lin, C., "Multi-scale Response Sensitivity Analysis based on Direct Differentiation Method for Concrete Structures," Composites Part B: Engineering 157, 295-304, 2019
16. Su, L., Wan, H.P., Li, Y., Ling, X.Z., "Soil-pile-quay Wall system with Liquefaction-induced Lateral Spreading: Experimental investigation, Numerical simulation, and Global Sensitivity Analysis," Journal of Geotechnical and Geoenvironmental Engineering, 2018.
17. Li, Y., and Conte, J.P., "Probabilistic Performance Evaluation of Seismic Isolation System for California High-speed Rail Prototype Bridge," Journal of Structural Engineering, 2018.
18. Li, Y., and Conte, J.P., "Probabilistic Performance-based Optimum Seismic Design of Seismic Isolation for California High-speed Rail Prototype Bridge," Earthquake Engineering and Structural Dynamics, 47(2), 2017.
19. Astroza, R., Ebrahimian, H., Li, Y., and Conte, J.P., "Bayesian Nonlinear Structural FE Model Updating for Damage Identification of Civil Structures Subjected to Unknown Inputs," Mechanical Systems and Signal Processing, 93, 2017.
20. Li, Y, Huang, S., Lin, C., Gu, Q., and Qiu, Z., "Response Sensitivity Analysis for Plastic Plane Problems based on Direct Differentiation Method," Computers and Structures, 182, 2017.
21. Li, Y., Astroza, R., Conte, J.P., and Soto, P., "Nonlinear Finite Element Model Updating and Reconstruction of the Response of an Instrumented Isolated Bridge Subjected to the 2010 Maule Earthquake," Earthquake Engineering and Structural Dynamics, 46(15), 2017.
22. Gu, Q., Liu, Y., Li, Y., and Lin, C., "Finite Element Response Sensitivity Analysis of Three-dimensional Soil-Foundation-Structure Interaction(SFSI) Systems," Earthquake Engineering and Engineering Vibration, in press, 2017.
23. Li, Y., and Conte, J.P., "Effects of Seismic Isolation on the Seismic Response of a California High-Speed Rail Prototype Bridge with Soil-Structure and Track-Structure Interaction," Earthquake Engineering and Structural Dynamics, 46(15), 2016.
24. Li, Y., Conte, J.P., and Barbato, M., "Influence of the Time-Varying Frequency Content in Earthquake Ground Motions on Seismic Response of Linear Elastic Systems," Earthquake Engineering and Structural Dynamics, 45(8), 2016.

Teaching

Undergraduate Courses

CIVE 295 Civil Engineering Analysis II (Winter 2021 - present)

CIVE 372 Structural Analysis I (Fall 2017 - present)

Graduate Courses

CIVE 660 Advanced Structural Analysis (Winter 2017 - present)

CIVE 661 Dynamics of Structures (Winter 2020)

CIVE 779 Structural Reliability (Winter 2018 - present)

Candidates with strong interest in mechanics- and data-based structural modeling, probabilistic modeling and analysis, are strongly encouraged to apply for openings in the SM&RA research group.