Dr. Hongyang Cheng’s research focuses on advancing the understanding and modeling of soils through two primary lines of inquiry: multi-scale modeling and Bayesian uncertainty quantification. His work aims to bridge the gap between theoretical soil models and practical risk assessments, particularly in geotechnical applications like dike and embankment safety.

Multi-scale Modeling: Dr. Cheng specializes in modeling granular materials (e.g., soils, rocks) across particle, meso, and macro scales. During his PhD, he developed Discrete Element Method models to understand fiber-reinforced soils and derive constitutive laws. As a postdoc, he improved direct numerical simulations of fluid-saturated soils by integrating microstructural and particle-fluid dynamics. His contributions include also generalized multi-scale formulations that better conserve momentum and energy, with applications to soil-structure interactions and transient granular flows.

Bayesian Uncertainty Quantification: With ten years of experience in Bayesian inference, Dr. Cheng developed methods like iterative Bayesian filtering for efficient parameter inference and spearheaded “GrainLearning”. GrainLearning combines physics-based modeling with ML, utilizing clustering algorithms and neural networks to improve inference and computational efficiency. This tool has earned recognition, including industry adoption and funding to expand its surrogate modeling capabilities.

Dr. Cheng is actively involved in multidisciplinary initiatives, such as the Lorentz Center workshop he organized on “Machine Learning for Discrete Granular Media,” which aimed to integrate physics-based and machine-learning approaches in computational geomechanics. He also leads working groups to promote open science within the DEM community. The application of his research extends beyond geotechnics to other fields, including laser sintering, pharmaceutical powder processing, and industrial granular material handling.

In the Civil Engineering & Management Department, Dr. Cheng teaches undergraduate courses on Soil Mechanics (second-year) and Geotechnics for Dike Design (third-year), equipping students with foundational knowledge in soil behavior and practical techniques for soil characterization in geotechnical applications. At the MSc level, he teaches GeoRisk Management (5EC), where students integrate probability theory, stochastic modeling, and numerical methods (FEM) to assess and manage risks in geotechnical engineering, by modifying and running a dike model (Python) for risk assessment.

During his postdoctoral tenure in the Thermal and Fluid Engineering Department, Dr. Cheng coordinated and lectured in three 5EC MSc courses: Multiphase Flows, focusing on the dynamics of particle-fluid systems; Granular Matter, exploring soil elastoplasticity; and Advanced Programming in Engineering, emphasizing image analysis techniques.

191158500 - APiE

201400194 - Granular Matter

201400300 - Multiphase Flows

Click here to explore his recent NWO- and EU-funded projects on earthquakes and submarine landslides.