Get started
Author

Shaoheng Guan

Observed name: GUAN, SHAOHENG
Observed institutions: University of Liverpool, Wuhan University, Swansea University, Graz University of Technology, Jingchu University of Technology, State Key Laboratory of Water Resources and Hydropower Engineering Science
ORCID: 0000-0001-7867-9517
Observed ORCID: 0000-0001-7867-9517
OpenAlex ID: A5091203766
Deep active learning for constitutive modelling of granular materials: From representative volume elements to implicit finite element modelling
2023 · Tongming Qu, Shaoheng Guan, et al. · International Journal of Plasticity · 105
Data-driven multiscale modelling of granular materials via knowledge transfer and sharing
2023 · Tongming Qu, Jidong Zhao, et al. · International Journal of Plasticity · 73
A neural network-based material cell for elastoplasticity and its performance in FE analyses of boundary value problems
2023 · Shaoheng Guan, Xue Zhang, et al. · International Journal of Plasticity · 28
PE-MPINN: A parameters-enhanced multiphysics-informed neural network for data assimilation of seepage-consolidation coupling problems in spatially variable soils
2026 · Mingyue Sun, Gang Ma, et al. · Advanced Engineering Informatics · 8
Differentiable constitutive modelling of granular media: From surrogate material model in explicit FEM-DEM to automatic elastoplastic calibration
2026 · Mengqi Wang, Tongming Qu, et al. · International Journal of Plasticity · 4
Machine-Learning-Based Multiscale Methods for 3D Modelling of Granular Materials by Incorporating History-Dependent State Variables
2025 · Mengqi Wang, Min Wang, et al. · KONA Powder and Particle Journal · 1
Physics-Consistency Condition for Infinite Neural Networks and Experimental Characterization
2023 · Sascha Ranftl, Shaoheng Guan · International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt)
PDF
Machine Learning-Based Constitutive Modelling for Granular Materials
2023 · GUAN, SHAOHENG · Cronfa (Swansea University)
Works count: 9
Citation count: 219
H-index: 4
I10-index: 3
Year
Topic
Type