Hongyang Cheng

dr.

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20152024

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Personal profile

Personal profile

Dr. Hongyang Cheng is Assistant Professor of Geomechanics at the University of Twente. He obtained his PhD on "multi-scale characterization of geosynthetic-reinforced soils" at Hiroshima University in 2016. He subsequently joined the Multi-Scale Mechanics group of the University of Twente and worked on "wave propagation in granular media" and "concurrent multi-scale modeling" until 2020. For his PhD work, he received the best student paper award at the DEM7 conference and a top downloaded paper award from “Granular Matter”. Dr. Cheng has been giving invited lectures at the University of Pisa, Okayama University and the Japanese Geotechnical Society, and was the organizer and chair of the symposium “Open-Source Development” of the DEM8 conference in 2019. Dr. Cheng served as a guest editor for the special issue of Computers and Geotechnics "DEM for Geotechnics".

Research interests

Dr. Cheng has worked extensively on the multi-scale and constitutive modeling of heterogeneous soils (e.g., GRS), Bayesian parameter estimation, and 3D micro-CT image analysis. His research aims to understand the physical processes where the micro-mechanics is important and relevant length/time scales are not well defined. To this end, he develops multi-scale modeling and Bayesian inference tools to bridge geomechanical models at micro and macro scales. His most recent work involves developing a computational framework for concurrent multi-model simulations of granular matter, in all physical states. 

Dr. Cheng has developed and coupled several open-source software packages, including YADEMercuryDPMOomphLib, and LB3D, for solving geotechnics and geophysics problems, such as soil-geosynthetics interaction (FEM-DEM) and wave propagation in granular media (LBM-DEM). He has developed a Bayesian calibration software "GrainLearning" which has many users in the industry and academia. Dr. Cheng is the main developer of the coupled MercuryDPM-OomphLib code, with a vision to implement a unified multi-scale framework for modeling solid/fluid-like behavior of granular materials, incorporating state-of-the-art​ open-source codes from soil mechanics, fluid mechanics, and beyond.

Teaching

In the Thermal and Fluid Engineering Department, Dr. Cheng coordinated and gave lectures in three 5EC MSc courses. He taught the dynamics of particle-fluid systems in Multiphase Flows, soil elastoplasticity in Granular Matter, and image analysis in Advanced Programming in Engineering.

In the Civil Engineering Department, he teaches an MSc course GeoRisk Management (5EC). Students learn how to use probability theory and stochastic modeling to integrate numerical models (e.g., FEM) and observation data within a probabilistic framework for risk assessment. This multidisciplinary course covers several topics, including geomechanics, flow in porous media, finite element method, and stochastic modeling. Students practice the knowledge learned in the lectures via the final project "Dyke Risk'', by implementing a small Matlab soler for probability-based dike stability assessment.

A full list of courses I teach and contribute can be found here

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 11 - Sustainable Cities and Communities
  • SDG 13 - Climate Action

Education/Academic qualification

PhD, Multiscale characterization of geosynthetic-reinforced soil, Hiroshima University

1 Oct 201328 Sept 2016

Award Date: 28 Sept 2016

Master, Hiroshima University

1 Oct 201128 Sept 2013

Award Date: 28 Sept 2013

Keywords

  • TA Engineering (General). Civil engineering (General)
  • Geomechanics
  • Geotechnical Engineering
  • Geosynthetics
  • Computational Mechanics
  • Data Assimilation
  • Multiscale Modeling
  • Discrete Element Modeling
  • Finite Element Modeling
  • Wave Propagation in Porous Media
  • Lattice Boltzmann Method

Artificial Intelligence Expert

  • Geo Sciences
  • Machine Learning: from Traditional Methods to Deep Neural Networks

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