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Gengchao Yang

Doctor of Geomechanics

Sun Yat-sen University

About me

I am now working as an Assistant Professor at the Sun Yat-sen University. My research interests cover all kinds of interesting phenomena related to granular materials, in particular the flow of soil particles and their mixture with fluids. The goal of my research is to establish physics-based constitutive models to better predict the mechanical responses of granular materials and to deploy such models in an efficient numerical framework that can help the design in engineering practice.

Interests

  • Computational Geomechanics
  • Computational Fluid Dynamics
  • Geophysical Flows
  • Hazard Mitigation

Education

  • PhD in Geotechnical Engineering, 2019

    The University of Hong Kong

  • MSc in Geotechnical Engineering, 2015

    The University of Hong Kong

  • BEng in Civil Engineering, 2014

    The University of Hong Kong

Experience

 
 
 
 
 

Assistant Professer

Sun Yat-sen University

Jun 2020 – Present Shenzhen
 
 
 
 
 

Post-doc

The University of Hong Kong

Nov 2019 – Dec 2021 Hong Kong

Awards

Excellent Teacher of the 10th Teaching Competition in English

Shenzhen Overseas High-Caliber Personnel

Ringo Yu Prize for Best PhD Thesis in Geotechnical Studies

Recent Posts

My first post

A cool view of the gold coast in Hong Kong.

Projects

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Continuum simulation of granular flows using the lattice Boltzmann method

Implement physics-base constitutive models for granular flows into the lattice Boltzmann framework.

Machine learning aided computational fluid dynamics

Explore the application of machine learning techniques to optimize CFD and LBM calculations.

Fully resolved numerical simulation of particle laden flows

Numerical simulation of fluid-particle mixtures using the coupled LBM-DEM method.

Recent Publications

Frictional boundary condition for lattice Boltzmann modelling of dense granular flows

Hydrodynamic approaches that treat granular materials as a continuum via the homogenization of discrete flow properties have become …

A neural network-based PDE solving algorithm with high precision

The consumption of solving large-scale linear equations is one of the most critical issues in numerical computation. An innovative …

Efficient lattice Boltzmann simulation of free-surface granular flows with $\mu(I)$-rheology

This paper presents a lattice Boltzmann framework for accurate and efficient simulation of free-surface granular flows. The granular …

Recent Talks

基于格子Boltzmann方法的颗粒流多尺度建模与分析

This talk introduces our recent advance in efficient continuum simulation of granular flows using the lattice Boltzmann method.

Towards multiscale lattice Boltzmann modeling of granular flows

This talk starts with our previous experience on numerical simulation of granular flows using discrete methods. Then, it introduces our future plan for more efficient simulations using the lattice Boltzmann method.

Meet the Team

Graduate Students

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Feng Qiao

Master Student

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Yunjin Huang

Master Student

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Renyu Luo

Master Student