Multiscale modelling for characterisation of particle transport and retention in porous media

About this project

Project description

Understanding the dynamics of particle transport and retention in porous media is critical to numerous energy and environmental engineering processes. Such flow scenarios in the real world are affected by the heterogeneity of porous media and particles, geometric complexity of the flow and multiphysics mechanisms. However, traditional mathematical models for suspension flow and fines migration apply averaged large scale mass balance and kinetic equations, which do not reflect the particle and pore size distributions and microscale conditions of mechanical equilibrium.

This project aims to develop a novel multiscale method based on stochastic population balance equation and microscale network model. Macroscale transport properties are obtained from modelling of both the pore-scale and particle-scale physics via high-resolution simulations using a mesh-free Lagrangian fluid flow solver. This solver has been in development in-house and used advanced high performance capabilities such as heterogeneous parallel algorithms. High-resolution multiphysics simulations using this solver, the development of inter-particle force models, characterisation of complex geometry and utilisation of advanced data science tools are involved to achieve this goal.

The high resolution simulations will be first validated through idealised porous media with monodisperse particles and later three dimensional scans of real porous media with known particle distribution will be used. This new multiscale method has the potential to become a powerful tool with broad applications in engineering and natural processes, such as enhanced hydrocarbon recovery, optimised subsurface fluid injection accompanied with fines migration (e.g. underground carbon dioxide and hydrogen storage) and microbial propagation in aquifers.


Year 1: Characterisation of porous media shape and validations of flow through realistic porous media – journal article.

Year 2: A two way coupled fluid – rigid body flow solver with inter-particle electrostatic force model validated against models for idealised suspension flows – journal article and datasets.

Year 3: Generate datasets of the pore and particle scale simulation for different parameter coordinates based on a principal component analysis – datasets and conference presentation.

Year 4: Use the simulation dataset from network model as input for the stochastic population balance model in macro scale – journal article and conference presentation.

Information for applicants

Essential capabilities

Basic programming skills, solid foundation in fluid mechanics.

Desireable capabilities

Stochastic methods, high performance computing.

Expected qualifications (Course/Degrees etc.)

Bachelors degree, Masters degree.

Project supervisors

Principal supervisors

UQ Supervisor

Professor Geoff Wang

School of Chemical Engineering
IITD Supervisor

Assistant professor Prapanch Nair

Department of Applied Mechanics
Additional Supervisor

Dr Zhenjiang You

School of Chemical Engineering