Y. Yan
Please Note
8 records found
1
A convex pattern surface is proposed and optimized to mitigate the sliding wear of bulk handling equipment caused by interaction with bulk solids. This work investigates the effectiveness of the convex pattern surface on wear reduction during interactions with non-spherical particles. Multiple representative particles, obtained through a sampling method, are reconstructed using a photogrammetry technique. Two contact parameters between particles are calibrated through shear box and drawdown tests to ensure flow behavior similar to the real material. The numerical results indicate that the convex pattern surface can effectively reduce wear compared to a plain sample when involving both spherical and non-spherical particles. For a plain sample, the wear volume remains independent of particle shapes and increases linearly with numerical revolutions. For the convex pattern surface, the wear volume demonstrates a quadratic relationship with the test revolutions as the deformation of convex elements weakens the effectiveness of the sample on wear reduction. The particle flow behavior analysis reveals that the convex pattern surface experiences the lowest wear volume when in contact with non-spherical particles. This can be attributed to the non-spherical particles sliding shorter distances and rotating with higher angular velocities on the convex pattern surface.
A convex pattern surface has been proposed and optimized to reduce sliding wear of bulk handling equipment by adjusting the flow behaviour of bulk material. This study aims at modelling the surface deformation of the convex pattern sample to investigate how effectively the sample reduces sliding wear. Archard wear model and a deformable geometry technique are combined to capture the sample deformation. A short-time laboratory wear experiment is performed as a benchmark to validate the numerical model. The simulation resutls indicate that there is a linear relation between the wear volume of a plain sample and the simulated revolutions, while the convex pattern sample has a quadratic trend. The wear distribution displays that the convex pattern accounts for the majority of wear of the sample. The contact behaviour demonstrates that the convex pattern facilitates the rolling of particles, resulting in the reduction of sliding distance. The numerical results indicate that the deformed convex pattern sample leads to lower overall sliding wear than a plain sample, although its effectiveness weakens as wear evolves.
A previous study revealed that a convex pattern surface can reduce sliding wear of a transfer chute. A convex pattern surface is a flat surface outfitted with a pattern of convexes defined by five parameters. A three-level definitive screening design (DSD) method combined with discrete element method (DEM) is used to investigate the influence of the five parameters and two operational conditions on the sliding wear. Two flow regimes are distinguished, namely continuous and discontinuous flow regimes, and both flow regimes can significantly reduce the sliding wear. The particle velocity and angular velocity profiles verify the guiding and rolling effect of the convex pattern on the motion of particles. A regression model fitted based on the DSD indicates that three main factors and one interaction have significant influence on the sliding wear.
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. ...
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.