AMSI Winter School 2019 - Computational Modeling of Heterogeneous Media - 1-12 July 2019 - Queensland University of Technology

AMSI Winter School 2019

Queensland University of Technology

1-12 July

About Winter School


The aim of AMSI Winter School 2019 is to develop the next generation of mathematical scientists to work in the exciting field of modelling heterogeneous media. Our impressive line-up of international and national speakers will build knowledge in this field, and introduce students to a range of topical applications.

Hosted by the Queensland University of Technology this winter, the School is designed for postgraduate students and early-career researchers in the mathematical sciences and cognate disciplines. Students and early-career researchers working specifically in this area of study are of course encouraged to attend: however, the school is a great opportunity for those working in other areas of the mathematical sciences to strengthen their mathematics toolkit.

Computational Modelling of Heterogeneous Media

The study of multiphase flow in heterogeneous media finds application across a number of important industrial and biological processes, including drying of foods for preservation, converting biomass into biofuels, using fractional dynamic models for MRI to probe tissue microstructure, studying viscoelastic non-Newtonian fluids, and understanding the role of heterogeneity for treating diseases of the heart. A significant challenge to modelling these processes is to understand how the strongly coupled heat and mass transfer phenomena evolve and interact in the complicated porous microstructure. To elucidate the complex physics, exposure to a broad cross-section of sophisticated numerical methods is essential and we will explore some of these methods in the Winter School. The School will feature modules on multiscale modelling; computational homogenization; fractional calculus; finite volume, finite element, spectral and meshless methods; Stokes flow; parameter estimation; and Krylov subspace methods.