From Computational Research to Geotechnical Numerical Modelling

1. Research Profile

Dr Liu’s research background spans a former Associate Professor appointment at Harbin Institute of Technology and doctoral / postdoctoral research at the University of Melbourne, where he holds a current Honorary Fellow appointment following his time as a Research Fellow. Across these roles, his research has centred on computational mechanics and finite element modelling of material behaviour, deformation mechanisms and porous media response, applied primarily within biomedical engineering.

2. Biomedical Engineering Research

His PhD in Civil Engineering at the University of Melbourne (2019–2023) developed computational and finite element modelling methods to study bone fracture healing mechanisms, cartilage lubrication, motion capture systems and muscle loading. This work involved formulating mechanics-based models of load-bearing biological structures, deriving and interpreting material parameters, processing motion-capture-derived loading data, and validating model predictions against experimental data — the same discipline that underpins reliable geotechnical numerical modelling. The research was recognised with a Melbourne Research Scholarship (2019–2023) and the 2023 PhD Write-Up Award.

Bone and cartilage are, like soil, porous, heterogeneous materials whose behaviour under load is difficult to characterise from limited data. Solving that characterisation problem is the origin of the modelling discipline he now applies in geotechnical work.

3. Computational Mechanics & Finite Element Modelling

Across this research programme, he developed capability in finite element modelling, model formulation, parameter interpretation, sensitivity analysis, model validation, scientific programming and data interpretation (including processing of motion capture and muscle loading datasets), together with experience preparing peer-reviewed technical publications and supervising undergraduate and postgraduate students.

4. Transferability to Geotechnical Engineering

The core methods of this research — finite element modelling, porous media theory, material behaviour modelling, validation and sensitivity analysis — transfer directly to geotechnical and infrastructure problems involving ground-structure interaction, seepage, deformation, slope stability, embankment behaviour and tailings / dam infrastructure. In practice, this means approaching geotechnical numerical modelling with a research-trained discipline: questioning model assumptions, testing sensitivity to input parameters, and being explicit about what a model can and cannot reliably predict.

Research Method	Geotechnical Application
Finite element modelling	Settlement, deformation, excavation stability, tunnel behaviour, ground-structure interaction
Porous media theory	Seepage analysis, consolidation, pore pressure response
Material behaviour modelling (bone, cartilage)	Soil and rock constitutive behaviour under load
Motion capture & muscle loading interpretation	Interpreting field monitoring and load history data
Model validation against experimental data	Calibration of geotechnical models against site and laboratory data
Sensitivity analysis	Understanding the influence of parameter uncertainty on design outcomes
Scientific programming (MATLAB, Python)	Automation, data processing and interpretation of modelling outputs

5. Selected Publications

Citation counts and updated publication metrics are available via Google Scholar.

6. Full Publication List

Journal Articles

Listed in reverse chronological order (most recent first).

1. Li, L., Liu, X., Patel, M., & Zhang, L. Effect of hand-wrist exercises on distal radius fracture healing based on markerless motion capture system. Journal of Biomechanics, 179, 112458, 2025. https://doi.org/10.1016/j.jbiomech.2024.112458
2. Li, L., Liu, X., & Zhang, L. Real-time biofeedback monitoring rehabilitation of distal radius fracture. Journal of NeuroEngineering and Rehabilitation, 22(1), 211, 2025. https://doi.org/10.1186/s12984-025-01746-1
3. Li, L., Liu, X., & Zhang, L. Individual muscle strengths in rehabilitation outcomes of distal radius fracture. Journal of NeuroEngineering and Rehabilitation, 22(1), 140, 2025. https://doi.org/10.1186/s12984-025-01669-x
4. Liu, X., Miramini, S., Patel, M., Ebeling, P., Liao, J. J., & Zhang, L. Development of numerical model-based machine learning algorithms for different healing stages of distal radius fracture healing. Computer Methods and Programs in Biomedicine, 233, 107464, 2023. https://doi.org/10.1016/j.cmpb.2023.107464
5. Li, L., Liu, X., Patel, M., & Zhang, L. Depth camera-based model for studying the effects of muscle loading on distal radius fracture healing. Computers in Biology and Medicine, 164, 107292, 2023. https://doi.org/10.1016/j.compbiomed.2023.107292
6. Wang, S., Ma, C., Wang, W., Hou, X., Xiao, X., Zhang, Z., Liu, X., & Liao, J. J. Prediction of failure modes and minimum characteristic value of transverse reinforcement of RC beams based on interpretable machine learning. Buildings, 13(2), 469, 2023. https://doi.org/10.3390/buildings13020469
7. Zhou, L., Ma, C., Zhang, Z., Sun, S., Liu, X., & Liao, J. Electrochemical accelerating leaching behavior of plastic concrete for cut-off walls. Buildings, 13(4), 937, 2023. https://doi.org/10.3390/buildings13040937
8. Liu, X., Liao, J., Patel, M., Miramini, S., Qu, J., & Zhang, L. Effect of uncertain clinical conditions on the early healing and stability of distal radius fractures. Computer Methods and Programs in Biomedicine, 241, 107774, 2023. https://doi.org/10.1016/j.cmpb.2023.107774
9. Liao, J. J., Liu, X., Miramini, S., & Zhang, L. Influences of variability and uncertainty in vertical and horizontal surface roughness on articular cartilage lubrication. Computers in Biology and Medicine, 148, 105904, 2022. https://doi.org/10.1016/j.compbiomed.2022.105904
10. Liu, X., Miramini, S., Patel, M., Liao, J. J., Shidid, D., & Zhang, L. Influence of therapeutic grip exercises induced loading rates in distal radius fracture healing with volar locking plate fixation. Computer Methods and Programs in Biomedicine, 215, 106626, 2022. https://doi.org/10.1016/j.cmpb.2022.106626
11. Liu, X., Miramini, S., Patel, M., Liao, J. J., Shidid, D., & Zhang, L. Balance between mechanical stability and mechano-biology of fracture healing under volar locking plate. Annals of Biomedical Engineering, 49(9), 2533–2553, 2021. https://doi.org/10.1007/s10439-021-02815-x
12. Liao, J. J., Miramini, S., Liu, X., & Zhang, L. Computational study on synovial fluid flow behaviour in cartilage contact gap under osteoarthritic condition. Computers in Biology and Medicine, 123, 103915, 2020. https://doi.org/10.1016/j.compbiomed.2020.103915

Thesis

1. Liu, X. Development of patient-specific rehabilitation strategies for distal radius fracture healing. The University of Melbourne, 2023.

Conference Paper

1. Liu, X., Miramini, S., Patel, M., Liao, J. J., Shidid, D., & Zhang, L. Computational simulation of mechanical stability and mechano-biology of distal radius fracture healing under volar locking plate. ACAM10: 10th Australasian Congress on Applied Mechanics, 2021.

7. Research Links