Yuanchen Zeng is a PhD researcher at the Section of Railway Engineering, Delft University of Technology. His research focuses on the vibration-based condition monitoring of railway track structures. He is under the supervision of Prof.dr. Zili Li and Dr. Alfredo Nunez.

Yuanchen Zeng got his Bachelor's degree in mechatronics engineering from Zhejiang University in 2016. Then, he completed his Master-PhD combined program at the State Key Laboratory of Traction Power, Southwest Jiaotong University in 2022. His research focused on the monitoring, prognostics, and maintenance of high-speed train wheels.

Yuanchen Zeng is/was within the instructor team of the following courses: CIE4870 (Structural design of railway track), CIE4871 (Design and maintenance of railway vehicles), MUDE Week 1.8 (Uncertainty quantification and Marko Chain Monte Carlo), MUDE Q2 Project (Health condition monitoring of railway infrastructure by track stiffness).

In the Department of Engineering Structures, Yuanchen Zeng acts as a co-organizer of ES Colloquium and a member of ES PhD Council. 

Some key publications from his previous research are listed below.

1. Y. Zeng, D. Song, W. Zhang, et al. An optimal life cycle reprofiling strategy of train wheels based on Markov decision process of wheel degradation. IEEE Transactions on Intelligent Transportation Systems. 2022, 23(8): 10354 - 10364.
2. Y. Zeng, D. Song, W. Zhang, et al. Physics-based data-driven interpretation and prediction of rolling contact fatigue damage on high-speed train wheels. Wear. 2021, 484: 203993.
3. Y. Zeng, D. Song, W. Zhang, et al. A new physics-based data-driven guideline for wear modelling and prediction of train wheels. Wear. 2020, 456: 203355.
4. Y. Zeng, D. Song, W. Zhang, et al. Risk assessment of wheel polygonization on high-speed trains based on Bayesian networks. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. 2021, 235(2): 182-192.
5. Y. Zeng, D. Song, W. Zhang, et al. Influence of different railway lines on wheel damage of high-speed trains: Data-driven modelling and prediction. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. 2022: 1748006X221122032.
6. Y. Zeng, W. Zhang, D. Song, et al. A new strategy for hunting alarm and stability evaluation for railway vehicles based on nonlinear dynamics analysis. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. 2020, 234(1): 54-64.