Dongyun Liu

About me

I am a Postdoctoral Researcher in the Structural Engineering Research Group at LTU. My research focuses on the dynamic behavior of railway infrastructure, including railway noise barriers and railway bridges, with particular emphasis on structural performance assessment and service-life prediction using long-term monitoring data and data-driven approaches under real operating conditions.

I received my Ph.D. in Structural Engineering from LTU in May 2026. My doctoral research focused on characterizing train-induced aerodynamic loads and investigating the dynamic behavior of railway noise barriers through a combination of field measurements, numerical simulations, and data-driven analyses. Prior to joining LTU in December 2021, I obtained a Bachelor's degree in Engineering from China University of Petroleum (Qingdao), China, in 2017, followed by a Master's degree in Architectural and Civil Engineering from Southeast University, Nanjing, China, in 2020. My master's research focused on the durability assessment of concrete subjected to early-age freeze–thaw damage.

I am passionate about tackling challenging engineering problems and exploring new research areas. Outside of academia, I enjoy watching football matches and playing basketball, which help me maintain a healthy balance between my professional and personal life.

Research interests

• Performance assessment of existing railway infrastructure
• Long-term monitoring and structural health monitoring
• Structural dynamics and vibration analysis
• Train-induced aerodynamics and railway noise barriers
• Data-driven analysis and machine learning in structural engineering
• Durability of concrete materials and structures

My objectives are to

• Advance data-driven approaches for structural performance assessment, condition evaluation, and service-life prediction under real operating and environmental conditions.
• Enhance the understanding of the dynamic behavior and long-term reliability of railway infrastructure through monitoring, numerical modeling, and machine learning.

Professional expertise

• Long-term monitoring and field measurements
• Structural dynamics analysis
• Finite element modeling (Abaqus)
• CFD simulation (ANSYS Fluent)
• Data analytics and machine learning
• Service-life prediction and fatigue assessment
• Concrete durability assessment

On-going projects

Long-term dynamic behavior of railway noise barrier

Climate-resilient railway bridges: From long-term monitoring to adaptive management