Ph.D. in Mechanical Engineering (06/1997)
Northwestern University, Evanston, IL
M.S. in Aerospace Engineering (05/1993)
University of Florida, Gainesville, FL
M.S. in Computational Mechanics (06/1989)
Huazhong University of Science and Technology, Wuhan, China
B.S. in Mechanical Engineering (06/1982)
East China University of Science and Technology, Shanghai, China
RESEARCH, TEACHING, or OTHER INTERESTS
Computational Mechanics, Materials Science, Civil and Structural Engineering, Computational Theory and Mathematics
Computational Study of Optimal Aggregate Ratio in the Mix Design of Various Concrete Types Fazel Azarhomayun, Peyman Khodabandeh, Leila Roshanali, Mohammad Shekarchi, Shaofan Li Journal of Engineering Mechanics, 2026 The construction industry is increasingly prioritizing the enhancement of concrete materials to meet environmental goals and promote sustainability by optimizing aggregate proportion. The improvement of aggregate proportion reduces cement usage and enhances the physical, mechanical, and durability properties of concrete. This research simulated aggregate proportion to determine the optimal packing density, aiming to improve the performance of concrete. Specifically, LIGGGHTS software was used to model various aggregate proportions and identify the mixture with the highest packing density. The simulation results, which showed the variance of the experimental data, were validated against the results from the modified Andreasen and Andersen model and the experimental data. The study indicates that the optimal packing density and stress distribution between particles provides a robust framework for predicting material performance. Using these results, it is possible to identify the optimal state of aggregate composition or the optimal packing density by analyzing the gradation and specific ratios of aggregate composition, and significantly increase the accuracy of mix design and resource management. It also saves time and money. The findings from this research will help researchers facilitate the selection of optimal aggregate mixes efficiently, thereby saving both time and resources.
Dendrite Suppression by Detouring Li Transport within a Mechanically Anisotropic Solid Electrolyte Alhamdu Nuhu Bage, Joseph Vazquez Mercado, Fernando D. Cúñez, Ashok Gurung, Shaofan Li, Qingsong Howard Tu Nano Letters, 2026 Li metal solid-state batteries (LMSSBs) offer higher safety and energy density but are limited by nonuniform Li + flux leading to dendrite issues. This work investigates the correlations between dendrite growth and microstructural anisotropies of Li 6 PS 5 Cl (LPSCl) solid electrolyte (SE) separators. Modeling and experiments reveal that LPSCl separators are mechanically weakest along θ = 0° and strongest along θ = 45° of the densification direction. We propose an innovative dendrite suppression strategy that detours growth away from the mechanically weakest direction using ring-shaped anode electrodes. The critical current density (CCD) obtained relative to the SE densification direction was ∼1 mA/cm 2 at θ = 0° and increased to ∼5 mA/cm 2 at θ = 45°, indicating directional dependence of Li + transport. This work presents a novel strategy to redirect dendrite growth away from microstructurally weak regions of the separator, emphasizing the need for advanced SE processing and battery designs.
On variational Bayesian inference theory of hyperelasticity for inversely recovering nonlinear continuum deformation mappings Chao Wang, Shaofan Li Computer Methods in Applied Mechanics and Engineering, 2026 In this work, we develop a Bayesian variational’ inference theory for nonlinear hyperelastic materials, which is accomplished by using a mixed Galerkin variational Bayesian inference nonlinear finite element method (VBI-NFEM). In the proposed Bayesian statistical continuum mechanics theory, the nonlinear elastic potential energy is used as a prior in a Bayesian inference network, which can intelligently and inversely recover the detailed continuum deformation mappings with only the information on the shapes of the deformed and undeformed continuum body, without knowing the actual boundary conditions, including both traction and displacement boundary conditions, and the fine scale material constitutive relation. To solve the mixed variational problem, we developed an operator splitting or staggered algorithm that consists of a finite element (FE) step and a Bayesian learning (BL) step, analogous to the well-known Expectation-Maximization (EM) algorithm. By solving the probabilistic Galerkin variational finite element problem, we demonstrated in several examples that the proposed method can inversely predict continuum nonlinear deformation mappings without requiring knowledge of the external load conditions. This long-sought-after inverse problem solution has been a significant challenge in the forensic pattern analysis of structural failures over the past several decades, and the proposed method provides a robust machine-intelligent solution.
Peridynamics modeling of ice fragmentation under blast loads Ying Song, Shaofan Li, Furen Ming Defence Technology, 2026 This study presents a Non-Ordinary State-Based Peridynamics (NOSB-PD) and Smoothed Particle Hydrodynamics (SPH) coupling framework for simulating the dynamics of ice fragmentation under explosive blasting loads. Addressing critical limitations in conventional numerical methods for modeling fragmentation dynamics and fluid-structure interaction, the proposed PD-SPH model has some unique features: (1) A novel ice constitutive model is adapted for ice's viscoelastoplastic behavior under explosive loading; (2) Experimentally determined temperature factors were incorporated into the plastic consistency law of the yield function, and a failure criterion accounting for temperature-dependent critical strain was adopted; (3) A newly identified optimal stand-off distance is implemented, which can maximize ice-breaking efficiency, and (4) Dimensionless parameters are adopted for cross-scale analysis. By doing so, the proposed PD-SPH model demonstrates exceptional numerical accuracy in capturing shock wave propagation and ice fracture patterns. These advances provide a robust, physics-based predictive modeling tool that can simulate explosive-induced icebreaking at an engineering scale for the design and implementation of various engineering projects in cold regions.
Atomic-scale identification of defects in alite Qi Zheng, Chengyao Liang, Jinyang Jiang, Haiyan Mao, Karen C. Bustillo, Chengyu Song, Jeffrey A. Reimer, Paulo J.M. Monteiro, Haimei Zheng, Shaofan Li Cement and Concrete Research, 2024
ONR MURI project on soil blast modeling and simulation Richard Regueiro, Ronald Pak, John McCartney, Stein Sture, Beichuan Yan, Zheng Duan, Jenna Svoboda, WoongJu Mun, Oleg Vasilyev, Nurlybek Kasimov, Eric Brown-Dymkoski, Curt Hansen, Shaofan Li, Bo Ren, Khalid Alshibli, Andrew Druckrey, Hongbing Lu, Huiyang Luo, Rebecca Brannon, Carlos Bonifasi-Lista, Asghar Yarahmadi, Emad Ghodrati, James Colovos Conference Proceedings of the Society for Experimental Mechanics Series, 2014
Molecular dynamics simulations of ions diffusion in carbon nanotubes embedded in cell membrane CMES Computer Modeling in Engineering and Sciences, 2014
Particle method modeling of nonlocal multiresolution continua Lecture Notes in Computational Science and Engineering, 2014
Preface Yongdan Li, Bin Zhu, Peter D. Lund, Angelo Basile Handbook of Micromechanics and Nanomechanics, 2013
X-FEM for three-dimensional dynamic crack growth Kan Ni, Patrick Hu, Xiaochen Fan, Shaofan Li Collection of Technical Papers AIAA ASME ASCE AHS ASC Structures Structural Dynamics and Materials Conference, 2011
Dynzamic shear band and crack propagation under high strain rate loading European Congress on Computational Methods in Applied Sciences and Engineering Eccomas 2000, 2000
Effective models for prediction of springback in flanging American Society of Mechanical Engineers Manufacturing Engineering Division MED, 2000
Invariant-conserving finite difference algorithms for the nonlinear Klein-Gordon equation American Society of Mechanical Engineers Pressure Vessels and Piping Division Publication PVP, 1992
RECENT SCHOLAR PUBLICATIONS
How Do Ice Shelves Calve? Peridynamic Modeling of Ice Shelf Fracture Driven by Wave Erosion, Basal Melting, and Buoyancy Flexure Y Song, X Hu, J Xu, K Zhu, Y Zhang, W Lu, S Li arXiv preprint arXiv:2605.04365 , 2026 2026
Computational Study of Optimal Aggregate Ratio in the Mix Design of Various Concrete Types F Azarhomayun, P Khodabandeh, L Roshanali, M Shekarchi, S Li Journal of Engineering Mechanics 152 (3), 04026001 , 2026 2026
On variational Bayesian inference theory of hyperelasticity for inversely recovering nonlinear continuum deformation mappings C Wang, S Li Computer Methods in Applied Mechanics and Engineering 448, 118448 , 2026 2026 Citations: 2
A unified framework of bond-associated peridynamic material correspondence models: Formulation and evaluation X Hu, H Chen, S Li Computer Methods in Applied Mechanics and Engineering 447, 118340 , 2025 2025 Citations: 6
Peridynamics modeling of ice fragmentation under blast loads Y Song, S Li, F Ming Defence Technology , 2025 2025
3D Printing of Conventional and Geopolymer Concretes: Advancements, Challenges, Future Directions, and Cost Analysis AK Pour, E Noroozinejad Farsangi, TY Yang, S Li, A Hajirasouli, ... Journal of Structural Design and Construction Practice 30 (4), 03125003 , 2025 2025 Citations: 6
Artificial Intelligence-Aided Design (AIAD) for Structures and Engineering: A State-of-the-Art Review and Future Perspectives: Y. Ao et al. Y Ao, S Li, H Duan Archives of Computational Methods in Engineering 32 (7), 4197-4224 , 2025 2025 Citations: 21
Semianalytical Solution to the Impact Effects of Continuous Highway Bridges under Random Moving Loads L Ma, CS Cai, L Nie, S Li Journal of Bridge Engineering 30 (9), 04025058 , 2025 2025
A stress-intensity-factor-driven phase field modeling of mixed mode fracture X Hu, S Li Computer Methods in Applied Mechanics and Engineering 443, 118058 , 2025 2025 Citations: 7
Hybrid‐data‐driven bridge weigh‐in‐motion technology using a two‐level sequential artificial neural network W Yan, H Ren, X Luo, S Li Computer‐Aided Civil and Infrastructure Engineering 40 (20), 2992-3012 , 2025 2025 Citations: 3
A stochastic multiscale asymptotic homogenization approach to 3D printed biodegradable resin TPMS bio-inspired structures TD Hoang, TH Ngo, KQ Tran, S Li, H Nguyen-Xuan Thin-Walled Structures 212, 113100 , 2025 2025 Citations: 16
Peridynamics simulations of the damage of reinforced concrete structures under radial blasting C Shi, S Zhang, X Zhang, S Li International Journal of Damage Mechanics 34 (7), 1165-1181 , 2025 2025 Citations: 3
Electron energy loss spectroscopy of nanoscale local structures in calcium silicate hydrate C Liang, Q Zheng, R Maboudian, PJM Monteiro, S Li Cement and Concrete Research 192, 107840 , 2025 2025 Citations: 5
Updated lagrangian particle hydrodynamics (ULPH) simulations of underwater bubble motions in three-dimensional space X Kan, J Yan, S Li, J Wang, Y Wang, Y Chen Engineering with Computers 41 (3), 1455-1475 , 2025 2025 Citations: 4
Artificial Intelligence-Aided Design for Unmanned Underwater Vehicles: A Multiple Activation Function Network-Based Hull Resistance Prediction Y Ao, H Duan, S Li IEEE Journal of Oceanic Engineering , 2025 2025 Citations: 2
Experimental study on the structural performance of glass-fiber-reinforced concrete slabs reinforced with glass-fiber-reinforced polymer (GFRP) bars: A sustainable alternative … F Xie, W Tian, S Li, P Diez, S Zlotnik, AG Gonzalez Polymers 17 (8), 1068 , 2025 2025 Citations: 14
An updated Lagrangian particle hydrodynamics (ULPH) implementation of heat conduction model for weakly-compressive fluid J Xiong, Z Wang, S Li, X Lai, L Liu, X Liu Computational Particle Mechanics 12 (2), 1249-1261 , 2025 2025 Citations: 4
A real-time multimodal transformer neural network-powered wildfire forecasting system Q Chen, S Li arXiv preprint arXiv:2503.05971 , 2025 2025 Citations: 2
The peridynamic material correspondence models: a state-of-the-art review on stabilization schemes D Liu, H Chen, X Hu, S Li Journal of Peridynamics and Nonlocal Modeling 7 (1), 5 , 2025 2025 Citations: 7
A variational Bayesian inference theory of elasticity and its mixed probabilistic finite element method for inverse deformation solutions in any dimension C Wang, S Li IEEE Transactions on Pattern Analysis and Machine Intelligence , 2025 2025 Citations: 4
MOST CITED SCHOLAR PUBLICATIONS
Reproducing kernel particle methods for structural dynamics WK Liu, S Jun, S Li, J Adee, T Belytschko International Journal for Numerical Methods in Engineering 38 (10), 1655-1679 , 1995 1995 Citations: 4620
Meshfree and particle methods and their applications S Li, WK Liu Appl. Mech. Rev. 55 (1), 1-34 , 2002 2002 Citations: 1350
Meshfree particle methods S Li, WK Liu Springer Berlin Heidelberg , 2004 2004 Citations: 984
Swelling of graphene oxide membranes in aqueous solution: characterization of interlayer spacing and insight into water transport mechanisms S Zheng, Q Tu, JJ Urban, S Li, B Mi ACS nano 11 (6), 6440-6450 , 2017 2017 Citations: 815
Moving Reproducing Least Square Kernel Method.(i) Methodology and convergence WK Liu, S Li, T Belytschko Computer Methods in Applied Mechanics and Engineering 143, 113-154 , 1997 1997 Citations: 801
Eighty years of the finite element method: birth, evolution, and future WK Liu, S Li, HS Park Archives of Computational Methods in Engineering 29 (6), 4431-4453 , 2022 2022 Citations: 455
Understanding the Aqueous Stability and Filtration Capability of MoS 2 Membranes Z Wang, Q Tu, S Zheng, JJ Urban, S Li, B Mi Nano letters 17 (12), 7289-7298 , 2017 2017 Citations: 419
Introduction to micromechanics and nanomechanics S Li, G Wang World Scientific , 2008 2008 Citations: 419
A critical review on structural health monitoring: Definitions, methods, and perspectives VR Gharehbaghi, E Noroozinejad Farsangi, M Noori, TY Yang, S Li, ... Archives of computational methods in engineering 29 (4), 2209-2235 , 2022 2022 Citations: 386
Finite difference calculus invariant structure of a class of algorithms for the nonlinear Klein-Gordon equation S Li, L Vu-Quoc SIAM Journal on Numerical Analysis, 1839-1875 , 1995 1995 Citations: 308
A State-of-the-Art Review on Machine Learning-Based Multiscale Modeling, Simulation, Homogenization and Design of Materials: D. Bishara et al. D Bishara, Y Xie, WK Liu, S Li Archives of computational methods in engineering 30 (1), 191-222 , 2023 2023 Citations: 262
Reproducing kernel hierarchical partition of unity, part I—formulation and theory S Li, WK Liu International Journal for Numerical Methods in Engineering 45 (3), 251-288 , 1999 1999 Citations: 240
Mesh-free Galerkin simulations of dynamic shear band propagation and failure mode transition S Li, WK Liu, AJ Rosakis, T Belytschko, W Hao International Journal of solids and structures 39 (5), 1213-1240 , 2002 2002 Citations: 219
Reproducing kernel element method. Part I: Theoretical formulation WK Liu, W Han, H Lu, S Li, J Cao Computer Methods in Applied Mechanics and Engineering 193 (12-14), 933-951 , 2004 2004 Citations: 214
Numerical simulations of large deformation of thin shell structures using meshfree methods S Li, W Hao, WK Liu Computational Mechanics 25 (2), 102-116 , 2000 2000 Citations: 213
Selected machine learning approaches for predicting the interfacial bond strength between FRPs and concrete M Su, Q Zhong, H Peng, S Li Construction and Building Materials 270, 121456 , 2021 2021 Citations: 201
Moving least-square reproducing kernel method Part II: Fourier analysis S Li, WK Liu Computer Methods in Applied Mechanics and Engineering 139 (1-4), 159-193 , 1996 1996 Citations: 178
Dynamic crack propagation in piezoelectric materials—Part I. Electrode solution S Li, PA Mataga Journal of the Mechanics and Physics of Solids 44 (11), 1799-1830 , 1996 1996 Citations: 178
On criteria for dynamic adiabatic shear band propagation SN Medyanik, WK Liu, S Li Journal of the Mechanics and Physics of Solids 55 (7), 1439-1461 , 2007 2007 Citations: 176
A Peridynamics-SPH modeling and simulation of blast fragmentation of soil under buried explosive loads H Fan, S Li Computer methods in applied mechanics and engineering 318, 349-381 , 2017 2017 Citations: 162