Chemical Plume Tracing by Discrete Fourier Analysis and Particle Swarm Optimization

A novel methodology for solving the chemical plume tracing problem that utilizes data from a network of stationary sensors has been developed in this study. During a toxic chemical release and dispersion incident, the imperative need of first responders is to determine the physical location of the source of chemical release in the shortest possible time. However, the chemical plume that develops from the source of release may evolve into a highly complex distribution over the entire contaminated region, making chemical plume tracing one of the most challenging problems known to date. In this study, the discrete Fourier series method was applied for re-construction of the contour map representing the concentration distribution of chemical over the contaminated region based on point measurements by sensors in a pre-installed network. Particle Swarm Optimization was then applied to the re-constructed contour map to locate the position of maximal concentration. Such a methodology was found to be highly successful in solving the chemical plume tracing problem via the sensor network approach and thus closes a long-standing gap in the literature. Furthermore, the nature of the methodology is such that a visual of the entire chemical dispersion process is made available during the solution process and this can be beneficial for warning purposes and evacuation planning. In the context of such chemical release scenarios, the algorithm developed in this study is believed to be able to play an instrumental role towards national defense for any country in the world that is subjected to such threats

Discrete element modeling for flows of granular materials

Ph.DDOCTOR OF PHILOSOPH

High-Flux Triple Bed Circulating Fluidized Bed (TBCFB) Gasifier for Exergy Recuperative IGCC/IGFC

The flow behavior of silica sand, of average particle size 128 μm, was investigated using a large-scale triple-bed combined circulating fluidized bed (TBCFB) cold model, which was composed of a 0.1 m I.D. ×16.6 m tall riser, a solids distributor, a 0.1m I.D. × 6.5 m long downer, a gas-solids separator, a 0.75 m × 0.27 m × 3.4 m bubbling fluidized bed and a 0.158 m I.D. × 5.0 m tall gas-sealing bed (GSB) with a high solids mass flux. The main focus of this study is to determine effect of riser secondary air injection on solids mass flux (Gs) and solid holdup. Gs slightly increased by secondary air injection when the riser gas velocity (Ugr) was less than 10 m/s. This was caused by the increase in the pressure difference between the GSB and the riser. Secondary air injection had little influence on the solid holdup in the riser. The mixing between silica sand and coal particles was investigated for two different coal feeding arrangements by coupling Computational Fluid Dynamics (CFD) with the Discrete Element Method (DEM). The results show a tangential arrangement provided better mixing than a normal arrangement except near the entrance

Heat Transfer from an Immersed Tube in a Bubbling Fluidized Bed

An Eulerian–Eulerian approach was used to investigate the effects of particle size and immersed tube temperature on bubbling and heat transfer behaviors in a gas fluidized bed. Large gas bubbles were observed to split into smaller bubbles that flowed around the immersed tube during the fluidization process. The formation of pockets of gas around the immersed tube led to a lower heat transfer coefficient. Heat transfer between the immersed tube and particles was facilitated by a phenomenon of particle renewal. Larger gas bubbles formed in the gas fluidized bed containing larger particles and this resulted in lower heat transfer coefficients due to the formation of more gas pockets around the immersed tube. When the temperature of the immersed tube was increased, the sensitivity of the heat transfer process toward formation of gas pockets around the immersed tube was observed to increase