Chen's research interests are in computational solid mechanics and multiscale materials modeling. More specifically, he investigates:
Finite Element and Meshfree Methods for nonlinear mechanics
Multiscale modeling of material defects
Computational methods for simulation of fragment-impact processes
Computational shock dynamics
Computational geomechanics
Physics constrained data-driven computing with applications to biological materials and digital twins
Physics-Informed manifold learning with deep autoencoders for nonlinear materials
Thermodynamically consistent machine-learned material models for path-dependent materials
Reduced order methods for biological systems
Reduced order method for inelastic materials and materials with defects
Multiscale and reduced order modeling of molecular systems with applications to DNA modeling
Image based multiscale computational mechanics for skeletal muscles
Accelerated Reproducing Kernel Particle Method for continuum, plates, shells, composites, large deformation, and contact problems
Mathematical analysis of Galerkin and collocation meshfree methods
Computational methods development for modeling of material manufacturing processes such as metal forming, stamping, and extrusion
Wavelet Galerkin method in multiscale homogenization of heterogeneous materials
Mesoscopic modeling of grain growth and grain boundary migration
Adaptive multiscale meshfree method for solving Schrödinger equation in quantum mechanics
Modeling of microstructural evolution and local instability (such as wrinkling formation) in polycrystalline materials
Computational damage mechanics and strain localization
Computational methods for rubber-like incompressible materials
Arbitrary Lagrangian Eulerian method for large deformation and contact problems
Mixed finite element method based on multiple-field variational principle
Probabilistic finite element method for acoustic-structure interaction
Machine-Learning Enhanced Data-Driven Computing
Physics-Informed Manifold Learning with Deep Autoencoders for Nonlinear Materials [Q. He, X. He]
Qizhi He
Xiaolong He
He, Q. and Chen, J. S., “A Physics-Constrained Data-Driven Approach Based on Locally Convex Reconstruction for Noisy Database,” Computer Methods in Applied Mechanics and Engineering, Vol. 363, 112791, 2019.
He, X., He, Q., Chen, J. S., “Deep autoencoders for Physics-Constrained Data-Driven Nonlinear Materials Modeling,”, Computer Methods in Applied Mechanics and Engineering, https://doi.org/10.1016/j.cma.2021.114034, Vol. 385, 114034, 2021.
He, Q., Laurence, D. W., Lee, C. H. and Chen, J. S., “Manifold Learning Based Data-Driven Modeling for Soft Biological Tissues,” Journal of Biomechanics, Vol 117, 110124, 2021.
Thermodynamically Consistent Machine-Learned Material Models for Path-Dependent Materials [X. He]
Xiaolong He
He, X., Chen, J. S., “Thermodynamically Consistent Machine-Learned Internal State Variable Approach for Data-Driven Modeling of Path-Dependent Materials, Computer Methods in Applied Mechanics and Engineering, https://doi.org/10.1016/j.cma.2022.115348, 2022.
Hyper Reduction of Nonlinear Inelastic Materials [S. Kaneko, H. Wei, Q. He]
Shigeki Kaneko
Haoyan Wei
Qizhi He
Kaneko, S., Wei, H., He, Q., Chen, J. S. and Yoshimura, S., “A Hyper-reduction Computational Method for Accelerated Modeling of Thermal Cycling-Induced Plastic Deformations,” Journal of the Mechanics and Physics of Solids, Vol. 151, 104385, 2021.
Multi-Scale Machine Learning Enhanced Data-Driven Musculoskeletal Digital Twins [K. Taneja, X. He, Q. He]
Karan Taneja
Xiaolong He
Qizhi He
Taneja, K., He, X., He, Q., Zhao, X., Lin, Y. A., Loh, K., Chen, J. S., “A Feature-Encoded Physics-Informed Parameter Identification Neural Network for Musculo-Skeletal Systems,” Journal of Biomechanical Engineering, https://doi.org/10.1115/1.4055238, Vol. 144(12), 121006, 2022.
He, X., Taneja, K., Chen, J. S., Lee, C. H., Hodgson, J. Malis, V. Sinha, U., Sinha, S., “Multiscale Modeling of Passive Material Influences on Deformation and Force Output of Skeletal Muscles, Journal for Numerical Methods in Biomedical Engineering,” DOI: 10.1002/cnm.3571, Vol. 38 (4), e3571, 2022.
Zhang, Y., Chen, J. S., He, Q., He, X., Basava, R. R., Hodgson, J., Sinha, U., Sinha, S., “Microstructural Analysis of Skeletal Muscle Force Generation During Ageing,” International Journal for Numerical Methods in Biomedical Engineering, DOI: 10.1002/cnm.3295, Vol. 36, Issue 1, e3295, 2020.
Neural Network Enhanced RKPM for for Modeling Localization and Microstructural Evolution [J. Baek, K. Susuki]
Jonghyuk Baek
Kristen Susuki
Baek, J., Chen, J. S., Susuki, K., “Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations,” International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022.
Baek, J., Chen, J. S., Tupek, M., Beckwith, F., & Fang, H. E., “A Duality based Coupling of Cosserat Crystal Plasticity and Phase Field Theories for Modeling Grain Refinement,” International Journal for Numerical Methods in Engineering, https://doi.org/10.1002/nme.6884, Vol. 123 (4), pp. 953-991, 2022
Digital Models for Disasters Prediction and Mitigation
A Semi‑Lagrangian RKPM with Particle‑Based Shock Algorithm for Explosive Welding and Jet Formation Simulation [J. Baek]
Jonghyuk Baek
Baek, J., Chen J. S., Zhou, G., Arnett K. P., Hillman, M., Hegemier, G., Hardesty, S., “Modeling of Explosive Welding Using a Semi-Lagrangian Meshfree Method with a Node-based Shock Algorithm,” Computational Mechanics, Vol., 67, pp. 1059–1097, 2021.
Pasetto, M., Baek, J., Chen, J. S., Wei, H., Sherburn, J. A., Roth, M. J., “A Lagrangian/semi-Lagrangian Coupling Approach for Accelerated Meshfree Modelling of Extreme Deformation Problems,” Computer Methods in Applied Mechanics and Engineering, https://doi.org/10.1016/j.cma.2021.113827, Vol. 381, 113827, 2021.
A Variational Multiscale Immersed Meshfree (VMIM) Method and Shock Algorithms for Modeling of Fluid Structure Interactive Systems Involving Shock Waves [T. Huang, F. Beckwith]
Tsung-Hui Huang
Frank Beckwith
Huang, T. H., Chen, J. S., Tupek, M. R., Beckwith, F. N., Fang, H. El., “A Variational Multiscale Immersed Meshfree Method for Fluid Structure Interactive Systems involving Shock Waves,” Computer Methods in Applied Mechanics and Engineering, https://doi.org/10.1016/j.cma.2021.114396, Vol. 389, 114396, 2022.
Huang, T. H., Chen, J. S., Tupek, M., Beckwith, F. N., Koester, J. J., “A Variational Multiscale Immersed Meshfree Method for Heterogeneous Materials,” Computational Mechanics, Vol. 67(4), pp. 1059-1097, 2021.
Huang, T. H., Chen, J. S., Wei, H., Roth, M. J., Sherburn J. A., Bishop, J. E., Tupek, M. R., Fang, E. H. “A MUSCL-SCNI Approach for Meshfree Modeling of Shock Waves in Fluids,” Journal of Computational Particle Mechanics, Vol. 7, pp. 329–350, 2020.
A Deformation‑Dependent Coupled Lagrangian/Semi‑Lagrangian Meshfree Hydromechanical Formulation for Landslide Modeling [J. Baek, R. Schlinkman, H. Wei]
Jonghyuk Baek
Ryan Schlinkman
Haoyan Wei
Baek, J., Schlinkman, R. T., Beckwith, F. N., Chen, J. S., “A Deformation-Dependent Coupled Lagrangian/semi-Lagrangian Meshfree Hydromechanical Formulation for Landslide Modeling,” Advanced Modeling and Simulation in Engineering Sciences, https://doi.org/10.1186/s40323-022-00233-9, 2:20, 2022.
Wei, H, Chen, J. S., Beckwith, H., Baek, J., “A Naturally Stabilized Semi-Lagrangian Meshfree Formulation for Multiphase Porous Media with Application to Landslide Modeling,” Journal of Engineering Mechanics, Vol.146 (4), 04020012, 2020.
Soft Target Impact Modeling by Smooth Kernel Contact Algorithms [R. Schlinkman, J. Baek]
Ryan Schlinkman
Jonghyuk Baek
Pasetto, M., Baek, J., Chen, J.-S., Wei, H., Sherburn, J., & Roth, M., “A Lagrangian/semi-Lagrangian coupling approach for accelerated meshfree modelling of extreme deformation problems,” Computer Methods in Applied Mechanics and Engineering, 381, 113827, 2021.
Baek, J., Schlinkman, R. T., Beckwith, F. N., Chen, J.-S., “A Deformation-Dependent Coupled Lagrangian/semi-Lagrangian Meshfree Hydromechanical Formulation for Landslide Modeling,” Advanced Modeling and Simulation in Engineering Sciences, https://doi.org/10.1186/s40323-022-00233-9, 2:20, 2022.
Wang, H.-P., Wu, C.-T., & Chen, J.-S., “A reproducing kernel smooth contact formulation for metal forming simulations,” Computational Mechanics, 54(1), 151-169, 2014.
Support Vector Machine Guided Reproducing Kernel Particle Method for Image-Based Modeling of Microstructures [Y. Wang, J. Baek]
Yanran Wang
Jonghyuk Baek
Wang, Y., Baek, J., Tang, Y., Du, J., Hillman, M., & Chen, J. S. (2023). Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures. Computational Mechanics, 1-36.
Multi-Physics Computational Models for Coupled-Systems
Imaged-based RKPM for Chemo-Mechanical Modeling of Energy Storage Materials [K. Susuki]
Kristen Susuki
Physics-Informed Data-Driven Constitutive Modeling of Thermo-Hydro-Mechanical Behaviors of Bentonite under High Temperature [J. Baek, X. He]
Jonghyuk Baek
Xiaolong He
He, X., Chen, J. S., “Thermodynamically Consistent Machine-Learned Internal State Variable Approach for Data-Driven Modeling of Path-Dependent Materials, Computer Methods in Applied Mechanics and Engineering, https://doi.org/10.1016/j.cma.2022.115348, 2022.
Baek, J., Schlinkman, R. T., Beckwith, F. N., Chen, J. S., “A Deformation-Dependent Coupled Lagrangian/semi-Lagrangian Meshfree Hydromechanical Formulation for Landslide Modeling,” Advanced Modeling and Simulation in Engineering Sciences, https://doi.org/10.1186/s40323-022-00233-9, 2:20, 2022.
Wei, H, Chen, J. S., Beckwith, H., Baek, J., “A Naturally Stabilized Semi-Lagrangian Meshfree Formulation for Multiphase Porous Media with Application to Landslide Modeling,” Journal of Engineering Mechanics, Vol.146 (4), 04020012, 2020.
Isogeometric Analysis and Shape Optimization
Interpolation-based integration for immersed boundary methods [J.E. Fromm]
Jennifer Fromm
Fromm, J.E., Wunsch, N., Xiang, R., Zhao, H., Maute, K., Evans, J.A., and Kamensky, D., Interpolation-based immersed finite element and isogeometric analysis. Computer Methods in Applied Mechanics and Engineering, , 405:115890, 2023.
Automated isogeometric analysis and design optimization for complex shell structures [H. Zhao]
Han Zhao
Zhao, H., Liu, X., Fletcher, A. H., Xiang, R., Hwang, J. T., and Kamensky, D., An open-source framework for coupling non-matching isogeometric shells with application to aerospace structures. Computers & Mathematics with Applications, 111:109–123, 2022.
Zhao, H., Kamensky, D., Hwang, J. T., and Chen, J. S., Automated shape and thickness optimization for non-matching isogeometric shells using free-form deformation. arXiv preprint arXiv:2308.03781, 2023.