Computer virtual experiment on fluidized beds using a coarse-grained discrete particle method—EMMS-DPM

2016 ◽  
Vol 155 ◽  
pp. 314-337 ◽  
Author(s):  
Liqiang Lu ◽  
Ji Xu ◽  
Wei Ge ◽  
Guoxian Gao ◽  
Yong Jiang ◽  
...  
Keyword(s):  
Fluidized Beds ◽  
Particle Method ◽  
Coarse Grained ◽  
Virtual Experiment ◽  
Discrete Particle ◽  
Discrete Particle Method

Simulation of Particle-Wall Collisions in a Viscous Fluid Using a Resolved Discrete Particle Method

2010 ◽  
Author(s):  
Zhi-Gang Feng ◽  
Efstathis E. Michaelides ◽  
Shaolin Mao
Keyword(s):  
Viscous Fluid ◽  
Numerical Method ◽  
Solid Wall ◽  
Particle Method ◽  
Solid Particles ◽  
Force Density ◽  
Model Parameters ◽  
Discrete Particle ◽  
Soft Sphere ◽  
Discrete Particle Method

The process of particle-wall collisions is very important in understanding and determining the fluid-particle behavior, especially near walls. Detailed information on particle-wall collisions can provide insight on the formulation of appropriate boundary conditions of the particulate phases in two-fluid models. We have developed a three-dimensional Resolved Discrete Particle Method (RDPM) that is capable of meaningfully handling particle-wall collisions in a viscous fluid. This numerical method makes use of a Finite-Difference method in combination with the Immersed Boundary (IB) method for treating the particulate phase. A regular Eulerian grid is used to solve the modified momentum equations in the entire flow region. In the region that is occupied by the solid particles, a second particle-based Lagrangian grid is used, and a force density function is introduced to represent the momentum interactions between particle and fluid. We have used this numerical method to study both the central and oblique impact of a spherical particle with a wall in a viscous fluid. The particles are allowed to move in the fluid until they collide with the solid wall. The collision force on the particle is modeled by a soft-sphere collision scheme with a linear spring-dashpot system. The hydrodynamic force on the particle is solved directly from the RDPM. By following the trajectories of a particle, we investigate the effect of the collision model parameters to the dynamics of a particle close to the wall. We report in this paper the rebound velocity of the particle, the coefficient of restitution, and the particle slip velocity at the wall when a variety of different soft-sphere collision parameters are used.

A Numerical Approach to Predict Sulphur Dioxide Emissions During Switchgrass Combustion

2013 ◽  
Vol 34 (1) ◽  
pp. 121-137
Author(s):  
Bernhard Peters ◽  
Joanna Smuła-Ostaszewska
Keyword(s):  
Experimental Data ◽  
Sulphur Dioxide ◽  
Kinetic Data ◽  
Combustion Process ◽  
Particle Method ◽  
Least Square ◽  
Exponential Factor ◽  
Discrete Particle ◽  
Sulphur Dioxide Emissions ◽  
Discrete Particle Method

Abstract The demand for a net reduction of carbon dioxide and restrictions on energy efficiency make thermal conversion of biomass a very attractive alternative for energy production. However, sulphur dioxide emissions are of major environmental concern and may lead to an increased corrosion rate of boilers in the absence of sulfatation reactions. Therefore, the objective of the present study is to evaluate the kinetics of formation of sulphur dioxide during switchgrass combustion. Experimental data that records the combustion process and the emission formation versus time, carried out by the National Renewable Energy Institute in Colorado (US), was used to evaluate the kinetic data. The combustion of switchgrass is described sufficiently accurate by the Discrete Particle Method (DPM). It predicts all major processes such as heating-up, pyrolysis, combustion of switchgrass by solving the differential conservation equations for mass and energy. The formation reactions of sulphur dioxide are approximated by an Arrhenius-like expression including a pre-exponential factor and an activation energy. Thus, the results predicted by the Discrete Particle Method were compared to measurements and the kinetic parameters were subsequently corrected by the least square method until the deviation between measurements and predictions was minimised. The determined kinetic data yielded good agreement between experimental data and predictions.

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