Effect of Impeller and Gas Stirring on Agglomeration Behavior of Polydisperse Fine Particles in Liquid

Abstract

Agglomeration, coalescence and flotation of non-metallic inclusions in steel melt are effective for obtaining "clean steel." In this study, the agglomeration and breakup behaviors of particles with a primary particle size distribution (hereinafter, polydisperse particles) in a liquid under impeller and gas stirring were compared by numerical calculations and model experiments. The particle-size-grouping (PSG) method in the numerical agglomeration model of particles was combined with a breakup term of agglomeration due to bubble bursting at the free surface. Polydisperse and monodisperse polymethylmethacrylate (PMMA) particles were used in the agglomeration experiments. The agglomeration rate of the polydisperse particles under impeller stirring was increased by an increasing energy input rate, whereas the agglomeration rate under gas stirring decreased under this condition due to the larger contribution of the breakup of agglomerated particles during bubble bursting in gas stirring. At the same energy input rate, agglomeration of polydisperse particles was larger under impeller stirring than under gas stirring. The agglomeration rate of polydisperse particles was larger than that of monodisperse particles under both impeller and gas stirring at the same energy input rate. The computational temporal changes in the total number of particles were in good agreement with the experimental results. This means that the difference in the agglomeration behaviors observed in impeller and gas stirring can be explained by the turbulent coagulation and subsequent agglomerated particle breakup in gas stirring. The computational temporal change in the number of each group approximately agreed with the experimental change in both impeller and gas stirring.

Detection and metrology of micro-nano particles through the integration of image and laser modes

“…In the experiment, the agglomeration of particles directly impacts the PSD [28][29][30]. Traditional algorithms, such as concave point detection and watershed methods, can detect the existing agglomerates, but the information is lost during the segmentation process.…”

Effect of Wettability, Number of Liquid Phases, and Agitation Procedure on Agglomeration/Breakup/Transfer of Fine Particles in Liquid

“…According to visual observations and previous papers, the sites of fine particle agglomeration, breakup, and transfer in a dual liquid phase are estimated as schematically illustrated in Figure 3. Turbulent agglomeration [9][10][11][12][13][14][15][16] occurs at sites I for hydrophobic particles and I' for hydrophilic ones. Sites I and I' were distinguished because the agglomeration rate of the hydrophobic particles was larger than that of the hydrophilic ones.…”

“…A simultaneous agglomeration model of two kinds of inclusion was developed and numerically calculated to simulate Al 2 O 3 and slag particles, [11][12][13] and an agglomeration of inclusions with wide particle size distribution was analyzed by a Particle-Size-Grouping (PSG) method. [14,15] Sumitomo et al [16] compared the agglomeration of monodisperse particles between impeller and gas stirring practices, and indicated that the agglomeration rate of the gas stirring was smaller than that of the impeller stirring due to breakup of some agglomerated particles induced by bubble bursting on the gas/liquid-free surface. Fruengieri et al [17,18] simulated the aggregation and breakup of colloidal particles under the effect of a shear field by combining a Monte Carlo algorithm and the discrete element method (DEM).…”

Turbulent Agglomeration of Polydispersed Particles in a Liquid

“…Yamaguchi et al 14) performed a water model experiment to investigate the agglomeration and breakup behaviors of particles under impeller and gas stirring and compared the results with those of the numerical model.…”

“…On the other hand, the agglomeration coefficient has been set to a constant value based on a fitting parameter 15)-16) or an approximate expression 2), 11) in previous studies. Although Nakaoka et al 11) and Yamaguchi et al 14) conducted water model experiments for agglomeration using polydispersed particles as model inclusions, they used a constant agglomeration coefficient for model calculations. Consequently, model calculations using a constant agglomeration coefficient may contain discrepancies when compared to measured values, such as number density and size distribution, among others.…”