Computational geomechanics
Discrete element method and finite element method
In situ characterization and utilization of extraterrestrial regolith
Biomass feedstock preprocessing and handling
Liquefaction hazard assessment and mapping
B.S., Civil Engineering, Shanghai Jiaotong University, China, 2006
M.S., Theoretical and Applied Mechanics (Geomechanics), Northwestern University, 2009
Ph.D., Theoretical and Applied Mechanics (Geomechanics), Northwestern University, 2011
Introduction to Geotechnical Engineering
Inelastic Materials Modeling
Computational Mechanics of Granular and Porous Materials
Creative Inquiry
Associate Member of the American Society of Civil Engineers
Member of the Engineering Mechanics Institute
Member of the Geo-Institute
Member of the Soil Properties and Modeling Committee, ASCE
Vice-Chair of the Computational Geotechnics Committee, ASCE
Chen, F., Xia, Y., Klinger, J. L., & Chen, Q. (2022). A set of hysteretic nonlinear contact models for DEM: Theory, formulation, and application for lignocellulosic biomass. Powder Technology, 117100. https://doi.org/10.1016/j.powtec.2021.117100
Lai, Z., Chen, Q., & Huang, L. (2022). Machine learning-enabled discrete element method: contact detection and resolution of irregular-shaped particles. International Journal for Numerical and Analytical Methods in Geomechanics, 46(1), 113-140. https://doi.org/10.1002/nag.3293
Guo, Y., Chen, Q., Xia, Y., Klinger, J., & Thompson, V. (2021). A nonlinear elasto-plastic bond model for the discrete element modeling of woody biomass particles. Powder Technology, 385, 557-571. https://doi.org/10.1016/j.powtec.2021.03.008
Zhan, W., & Chen, Q. (2021). Accelerogram-based method for quick assessment of liquefaction occurrence. Journal of Geotechnical and Geoenvironmental Engineering, 147(8), 04021060. https://doi.org/10.1061/(ASCE)GT.1943-5606.0002577
Lai, Z., & Chen, Q. (2019). Reconstructing granular particles from X-ray computed tomography using the TWS machine learning tool and the level set method. Acta Geotechnica, 14(1), 1-18. https://doi:10.1007/s11440-018-0759-x
Y. Guo, Q. Chen, Y. Xia, T. Westover, S. Eksioglu, and M. Roni, “Discrete element modeling of switchgrass particles under compression and rotational shear”, Biomass and Bioenergy, in press (2020).
Z, Lai, Q., Chen, and L. Huang, “Fourier series-based discrete element method for computational mechanics of irregular-shaped particles”, Computer Methods in Applied Mechanics and Engineering, 362, 112873, (2020).
Z. Lai and Q. Chen, “Reconstructing granular particles from X-ray computed tomography using the TWS machine learning tool and the level set method”, Acta Geotechnica, 14(1):1-18, doi:10.1007/s11440-018-0759-x, (2019).
C. Wang and Q. Chen, “A hybrid geotechnical and geologic data-based framework for multiscale regional liquefaction hazard mapping”, Gétechnique, 68(7): 614-625, DOI: 10.1680/jgeot.17.P.074, (2018).
C. Wang, Q. Chen, M. Shen and C.H. Juang, “On the spatial variability of CPT-based geotechnical parameters for liquefaction potential evaluation”, Soil Dynamics and Earthquake Engineering, 95, 153-166, doi:10.1016/j.soildyn.2017.02.001, (2017).
Computational geomechanics is an interdisciplinary topic that is at the interface of geotechnical engineering, applied mechanics, computational science and material science. Prospective M.S. and Ph.D. students who are interested in this area are always encouraged to apply to join my group.
