Eldin Wee Chuan Lim

Agglomeration of magnetic nanoparticles

The formation of agglomerates by salt-induced double layer compression of magnetic nanoparticles in the absence and presence of an external magnetic field was investigated experimentally as well as computationally in this study. The structures of the agglomerates were analyzed through scanning electron microscopy and proved to be highly porous and composed of large spaces among the branches of a convoluted network. In the absence of an external magnetic field, the branches of such a network were observed to be oriented in no particular direction. In contrast, when the agglomeration process was allowed to occur in the presence of an external magnetic field, these branches appeared to be oriented predominantly in one direction. A modified Discrete Element Method was applied to simulate the agglomeration process of magnetic nanoparticles both in the absence and presence of an external magnetic field. The simulations show that agglomeration occurred by the formation of random clusters of nanoparticles which then joined to form a network. In the presence of anisotropic magnetic forces, these clusters were rotated to align along the direction of the magnetic field and the final network formed consisted largely of elongated branches of magnetic nanoparticles.

Pattern formation in vibrated beds of dry and wet granular materials

The Discrete Element Method was coupled with a capillary liquid bridge force model for computational studies of pattern formation in vibrated granular beds containing dry or wet granular materials. Depending on the vibration conditions applied, hexagonal, stripes, or cellular pattern was observed in the dry vibrated granular bed. In each of these cases, the same hexagonal, stripes, or cellular pattern was also observed in the spatial distribution of the magnitudes of particle-particle collision forces prior to the formation of the corresponding actual pattern in physical distributions of the particles. This seemed to suggest that the pattern formation phenomenon of vibrated granular bed systems might be the result of a two-dimensional Newtons cradle effect. In the presence of a small amount of wetness, these patterns were no longer formed in the vibrated granular beds under the same corresponding set of vibration conditions. Despite the relatively much weaker capillary forces arising from the simulated l...

Human evacuation modeling by the discrete element method

The Discrete Element Method (DEM) was applied for human evacuation modeling in this study. The computational domain consisted of a room without any obstacles and a single exit and the evacuation of 100 subjects from the room was simulated. The typical phenomenon of jamming that is typical of such systems was reproduced computationally with such an approach. The evacuation process was observed to consist of the formation of a human cluster around the exit of the room followed by departure of subjects one at a time that created a significant bottleneck for the entire process.

ELECTROSTATIC EFFECTS IN PNEUMATIC TRANSPORT OF GRANULAR MATERIALS

The methodology of coupling the Discrete Element Method (DEM) with Computational Fluid Dynamics (CFD) was applied for computational studies of pneumatic transport of granular materials through vertical and horizontal pipes in the presence of electrostatic effects. The simulations showed that a thin layer of particles formed and remained adhered to the pipe walls during the pneumatic conveying process due to the effects of strong electrostatic forces of attraction towards the pipe walls. Particle concentrations were generally higher near the pipe walls than at the pipe centre resulting in the ring flow pattern observed in previous experimental studies. The close correspondence between particle velocity vectors and fluid drag force vectors was indicative of the importance of fluid drag forces in influencing particle behaviors. In contrast, the much weaker particle-particle electrostatic repulsion forces had negligible effects on particle behaviors within the system under all operating conditions considered....

Process Tomographic Measurements of Granular Flow in a Pneumatic Conveying System

The application of process tomography (PT) technologies, i.e. Electrostatic Tomography (EST) and Electrical Capacitance Tomography (ECT) to investigate complex industrial processes has obtained wide popularity in recent years. This study focuses on the characterization of non-uniformly distributed electrostatic effects across the cross-section of a pneumatic transportpipe. A digital electrometer was used to measure the electrostatics current and an ECT was used to observe the particle distribution in a vertical pipe. Due to non-uniform particle-wall collisions, the electrostatics generated was observed to be non-uniformly distributed across the pipe cross-section, especially at pipe bends and in a vertical pipe. Large electrostatic effects were associated with high particle concentration in the pipe. There was a good correspondence between the electrostatic effects measured and particle concentration distributions obtained using ECT. Based on ECT measurements at the vertical pipe section, it was observed that particles tended to concentrate at sections where generation of electrostatic charges was high. Thus, it is clear that electrostatic effects should be the key factor giving rise to non-uniform particle concentration distribution in pneumatic transport lines.

Fourier Analysis and Swarm Intelligence for Stochastic Optimization of Discrete Functions

A new methodology for solving discrete optimization problems by the continuous approach has been developed in this study. A discrete Fourier series method was derived and used for re-formulation of discrete objective functions as continuous functions. Particle Swarm Optimization (PSO) was then applied to locate the global optimal solutions of the continuous functions derived. The continuous functions generated by the proposed discrete Fourier series method correlated almost exactly with their original model functions. The PSO algorithm was observed to be highly successful in achieving global optimization of all such objective functions considered in this study. The results obtained indicated that the discrete Fourier series method coupled to the PSO algorithm is indeed a promising methodology for solving discrete optimization problems via the continuous approach.