Polydispersed Granular Flows through Inclined Channels
Funded by: STW
PhD: Deepak Tunuguntla
Supervisor: Onno Bokhove / Anthony Thornton
Collaboration: Tata Steel
Polydispersed Granular Flows through Inclined Channels”, the title already stirs up a brief notion of what my work is all about. Various examples for granular flows exist both in industry and nature. In Tata Steel, iron ore processing involves inflow of iron ore, coke and sinter pellets into the blast furnace as seen in Fig 1. A pellet contains raw material in the form of a sphere of certain diameter. The ore materials(pellets) are charged through a hopper from the top of the furnace and flows downwards under gravity, see Fig 2. The hopper rotates while also moving up and down mapping out a helical path. Moreover the hopper base is fitted with rivets making it rough and varying in basal topography. The mixture of pellets entering the furnace vary in size, shape and density. Due to such variance in the properties of pellets and hopper, complex flow patterns arise which in turn can affect the production quality.
The goal of our work is to provide a mathematical solution to help predict these complex flow patterns for improved process control and reduce or eliminate the product quality variation. To begin with, we need to understand the underlying physics of granular dynamics, analyze granular flow through inclined channels(eg. Hopper) with local constrictions or obstacles. Additionally, understand the segregation phenomenon observed due to varying pellet size and density as the mixture flows down the inclined channel. It is anticipated for this complex flow that a multiscale model will be required to capture the complex physics that occurs on multiple scales. Hence, the main interest lies in developing a heterogeneous multiscale model(HMM) coupling both the macroscale continuum with microscopic discrete particle model via combined discontinuous Galerkin finite element method(DGFEM) and discrete particle method(DPM). The coupling will be done at selective regions in space and time thus reducing computational expense and allowing simulation of the complex granular flows under study. In a sister project, experiments of these flow configurations will be carried out and an exchange of laboratory data and numerical models will mutually stimulate both projects.
Fig 1: Blast furnace for iron ore processing.
Fig 2: Insight of the blast furnace at Tata Steel, the granular mixture funneled into the furnace through the hopper.