Dr Huilin Xing

Principal Research Fellow

School of Earth and Environmental Sciences
Faculty of Science
+61 7 334 64093


Huilin Xing (H. L. Xing)’s current research interest is on Multiscale Multiphysical Modelling (M3) and practical applications in such as Earthquake Prediction & Virtual Near Wellbore by using supercomputers.

He received his PhD in computational mechanics and engineering in 1995 at Harbin Institute of Technology, China and then worked at the Institute of Physical and Chemical Research (RIKEN) in Japan before his coming to UQ in 2002, as a team member of the Japanese national priority science project, Earth Simulator, which combined computational earth systems science and super-parallel computer development. He has been working on advanced computational model and software development for simulating large scale non-linear multi-physical (Thermo-Hydro-Mechanical-Chemical) coupled geo-science and –engineering issues across different scales spanning from pore to lab and field scales, this includes crustal dynamics, interacting fault systems, earthquakes and tsunami as well as engineered reservoir system for such as geothermal electricity, unconventional gas/oil, CO2 geosequestration and deep underground engineering issues. His research at UQ has been supported by ARC, ACcESS major national research facility, NCRIS for AuScope and industrial partners such as Geodynamics Ltd and Coffey, and reported by UQ news (5 times) and major news media (e.g. ABC, SBS, 9 news, skynews, The Australian, NZ Herald, Couriermail). He has published 2 books, 3 book chapters and over 100 referred publications. Currently, he is working with his 6 PhD students and 2 visiting postdoctors and also serves as the Australian Representative in ACES International Science Board (ACES – APEC Cooperation for Earthquake Simulation, http://www.aces.org.au).

Research Impacts

PANDAS Software:

A novel finite element and/or Lattice Boltzmann method (FEM/LBM) based software has been developed and successfully applied for simulating the highly coupled geomechanical-fluid flow-thermal-chemical reaction systems involving heterogeneously fractured geomaterials to address the key scientific and technological challenges in the relevant geo-science and –engineering issues across different scales spanning from the pore to the lab and filed scale. Currently, it includes six key components: Pandas/Pre, ESyS_Crustal, Pandas/Thermo, Pandas/Fluid, Pandas/LBM and Pandas/Post:

· Pandas/Pre is developed to (1) visualise the microseismicity events and further evaluate the fracture location and evolution, volume of fractured domain and the relevant reservoir property (i.e. permeability); (2) link with other commercial software such as GoCAD, Geomodeller for complicated 3D reservoir model construction; (3) generate 2D/3D mesh by using microseismicity and complicated geological setting data for the following FEM/LBM analysis at different scales;

· Pandas/ESyS_Crustal is a FEM based module developed for the interacting fault system simulation. It employs the adaptive static/dynamic algorithm to simulate the dynamics and evolution of interacting fault systems and processes. All these are needed to better describe rupture/microseismicity/earthquake related phenomena with applications in earthquake forecasting, reservoir engineering, hazard quantification, exploration, and environmental problems;

· Pandas/Thermo is a finite element method based module for the thermal analysis of the fractured porous media and the metals; the temperature distribution is calculated from the heat transfer induced by the thermal boundary conditions without/with the coupled fluid flow effects in the fractured porous media and the geomechanical energy conversion for the individual/coupled thermal analysis

· Pandas/Fluid is a finite element method based module for simulating the Darcy and/or non-Darcy geo-fluids flow in the fractured porous media by solving the conservation equations of macroscopic properties numerically. Here the multiphase geo-fluids flow velocity and pressure are calculated from energy equilibrium equations without/with the coupling effects of the thermal and solid rock deformation for the individual/coupled fluid flow analysis ;

· Pandas/LBM is a LBM based module newly developed for explicitly simulating the 2D/3D complicated pore scale processes in complicated fractured porous media (fluid, thermal and even chemical reactions). Due to its particulate nature and local dynamics, LBM has several advantages over other conventional computational fluid dynamics (CFD) methods, especially in dealing with complex boundaries such as multiphase geo-fluids flow in complicated fractures/porous media incorporating microscopic interactions ;

· Pandas/Post is used to visualise the simulation results through the integration of the above modules with GUI (graphical user interface).

All the above modules have been verified and applied independently/together to simulate individual/ coupled phenomena for the relevant research and practical engineering applications. PANDAS has been gradually used in the related research community as the base research code for such as earthquake dynamics and tsunami for natural hazard forecasting and warning, as well as collaboration with industrial partners in different ways, such as from Geodynamics Ltd, Coffey Geotechnics, QGC/BP, Department of Main Road QLD, China National Petroleum Corporation (CNPC), SinoCoal, National Active Fault Centre of China, Chinese Earthquake Administration, Geology Survey of China, JAPEX of Japan etc.


  • MSc, Harbin IT
  • BSc, Harbin IT
  • Diploma, Harbin IT
  • PhD, Harbin IT


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  • Doctor Philosophy

  • Doctor Philosophy

  • Doctor Philosophy

View all Supervision



Book Chapter

  • Xing, Huilin, Yu, Wenhui and Zhang, Ji (2009). 3D mesh generation in geocomputing. In Huilin Xing (Ed.), Advances in geocomputing (pp. 27-64) Berlin & Heidelberg: Springer-Verlag. doi:10.1007/978-3-540-85879-9_2

  • Liu, Yan, Shi, E.O., Sevre, D, Xing, Huilin and Yuen, D.A. (2009). Probabilistic Forecast of Tsunami Hazards along Chinese Coast. In Huilin Xing (Ed.), Advances in Geocomputing (pp. 279-317) Berlin & Heidelberg: Springer-Verlag GmbH. doi:10.1007/978-3-540-85879-9_8

Journal Article

Conference Publication

Other Outputs

PhD and MPhil Supervision

Current Supervision

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

    Other advisors:

  • Doctor Philosophy — Principal Advisor

Completed Supervision