Education

Publications

Geng, Z., Zhang, C., Jiang, Y., Pugliese, D., & Cheng, M. (2025). Integrating multi-source data for life-cycle risk assessment of bridge networks: a system digital twin framework. Journal of Infrastructure Preservation and Resilience, 6, 9. [Link]
Gong, Y., Zhang, C., Geng, Z., Chen, R., & Ren, Y. (2024). Development and evaluation of a process-oriented 3D finite element model for earth pressure balance shield tunneling. Computers and Geotechnics, 171, 106347. [Link]
Zhou, J., Deng, P., Zhang, C., Geng, Z., & Chen, R. (2024). Seismic analysis of segmental tunnels using multi-contact joint-based tunnel model. Journal of Earthquake and Tsunami. [Link]
Geng, Z., Zhang, C., Ren, Y., Zhu, M., Chen, R., & Cheng, H. (2023). A Kriging-random forest hybrid model for real-time ground property prediction during earth pressure balance shield tunneling. arXiv preprint. [Link]

03/2025: 1st Place in Student Poster Competition, 1st Symposium on Climate-Smart Infrastructure Innovations & Implementation (CSi3), Miami, United States
11/2024: Excellent Abstract Award, The 2nd Workshop on Future of Machine Learning in Geotechnics& The 5th Machine Learning in Geotechnics Dialogue, Chengdu, China
06/2024: Excellent Graduate of Hunan University, Hunan University.
11/2023: First Prize Scholarship, Hunan University.
11/2022: National Scholarship, National Ministry of Education China.
11/2021: First Prize Scholarship, Hunan University.
06/2021: Excellent Graduate of Hunan University, Hunan University.

Scheduling Software for Deep Foundation Pit Engineering
The software integrates GIS and BIM to construct the digital foundation pit engineering scene. A-star algorithm is utilized to plan the path for the excavators within the 3D foundation pit. The visualization is implemented with the aid of Unity 3D.

A Kriging-Random Forest Hybrid Model (KRF)
The KRF model synergizes prior and real-time information to predict the ground properties. Prior information incorporates the inherent spatial correlation of ground properties within a given region. Real-time information refers to the current operating parameters, reflecting real-time shield–ground interactions. These two predictions are integrated according to their uncertainties, ensuring the prediction of KRF with minimum uncertainty.

Vibration Monitoring of the Shield Machine
A vibration monitoring system including seven accelerometers is designed and implemented in the Changsha Metro Line 1 North Extension. It provides a comprehensive vibration dataset of an EPB shield machine excavating through various rock types. Based on vibration analysis, two classification charts are developed for full-face rock type detection and ground composition detection, respectively. The proposed charts yield error-free predictions for all the 1752 recorded points in the project.