Using bionic surface on the material equipment interface of bulk handling equipment is a promising solution for abrasive wear reduction. A bionic surface is a flat surface outfitted with a pattern of convexes that disrupt the natural sliding flow of bulk material. Previous numerical work has shown a significant wear reduction of bionic surfaces compared to a smooth surface and revealed the effect degrees of geometric parameters and the interactions between them. The aim of this paper is to design samples with an optimal convex pattern for steel plates of 100 mm by 100 mm to verify the simulation results in a test rig for industrial scale experiments in Newcastle, Australia. In order to find an optimal convex pattern, a stepwise optimization, one-factor-at-a-time, is performed by optimizing four parameters of convex patterns. The geometric convex patterns were evaluated with the aid of Discrete Element Method (DEM). The simulated material was iron ore with d50 of 4.6 mm sliding down a smooth chute transitioning into bionic surfaces of different geometric configurations. Hertz-Mindlin (no slip) model with the Archard wear model were implemented to calculate the sliding wear volume. Considering the direct relation between the dimensions of convexes and the sizes of particles, the ratios of a0, b0, c0 and d0 to d50 were used for analysis simulation results. The results show that a chute surface with circular convexes with a radius of 6 mm (a0:d50=1.3), spaced 25 mm apart in both horizontal and vertical directions (c0:d50=5.4), is optimal in reducing wear. This sample configuration and smooth surface will be tested to verify the predictability of the simulation approach.@en

Using bionic surface on the material equipment interface of bulk handling equipment is a promising solution for wear reduction. A bionic surface is a flat surface outfitted with a pattern of convexes that disrupt the natural sliding flow of bulk material. Previous numerical work has shown a significant reduction of wear of bionic surfaces compared to a smooth surface. The aim of this paper is to study the influence of bionic configurations on wear reduction. Four geometric parameters were introduced to define the shape and size of these convex patterns. The geometric convex patterns were evaluated with the aid of Discrete Element Method (DEM). The simulated material was iron ore with d50 of 10 mm sliding down a smooth chute transitioning into bionic surface of different geometric configurations. Hertz-Mindlin (no slip) model and Archard wear model were implemented to calculate the sliding wear volume. The experimental plan was based on a full factorial design, which varied the parameters of a0, a0:b0, c0 and d0. Simulation results show that different patterns of convexes have different influence on wear volumes and velocities of particles. The factors a0 and d0 of each pattern have significant influence on sliding wear, while there are insignificant interactions between geometric parameters. It is found that the existence of convex patterns makes the particles closest to the chute’s surface have the tendency to slow down, causing the remainder of the particles to slide and roll over these bottom particles instead of sliding directly over the surface.@en

The infeed ofThe material in a blast furnace isThe composed of a mixtureThe of three different materials: sinter, iron ore pellets and coke. They are each very different in shape, size and mechanical properties and likely this promotes segregation, an unwanted effect. However up till now it is not clear to what extent the Particle Size Distribution (PSD) of each of the three components affects the homogeneity. This work aims to assess the influence of particle size distributions of the individual components on the homogeneity of the infeed material by Discrete Element Model (DEM) Simulations. It can be concluded that modelling the PSD of the individual components is not required to model the tendency to segregate of the mixture of iron ore pellets, sinter and coke. Representing each of the materials by its mean particle size d50 reduces the number of particles and simulation time drastically without compromising the simulation results of the used material models.@en