Modeling of the Size Distribution Resulting from Dissolution of Spherical Solid Particles in Turbulent Flow

• Published in: Journal of dispersion science and technology Vol. 33; no. 4; pp. 521 - 526
• Main Authors: Ekmekyapar, Ahmet, Künkül, Asım, Yüceer, Mehmet, Kelbaliyev, Gudret
• Format: Journal Article
• Language: English
• Published: Philadelphia, PA Taylor & Francis Group 01.04.2012; Taylor & Francis; Taylor & Francis Ltd
• Subjects: Atoms & subatomic particles; Chemistry; Colloidal state and disperse state; Dissolution; Dissolution of solids; Exact sciences and technology; General and physical chemistry; Genetic algorithms; mass transfer; Mathematical models; modeling; Particle size; particle size distribution; Physical and chemical studies. Granulometry. Electrokinetic phenomena; spherical particles; Studies; Turbulent flow; Motion; Stirred vessel; Particle size; Experimental data; Turbulent flow; Dissolution of solids; spherical particles; Industrial application; Equation; Solid particle; Time; Dissolution; Modeling; Solid; Mass transfer; Liquid; Particle size distribution; Flow regime; Genetic algorithm; Distribution function; Spherical particle; Diffusion; Mathematical model; Boundary layer
• ISSN: 0193-2691; 1532-2351
• DOI: 10.1080/01932691.2011.574929

The process of dissolution of solid particles in turbulent flow regime is of importance in many industrial applications. A new size distribution takes place due to dissolving during the motion of a solid-liquid suspended system in a stirred vessel. An analytical relationship was derived to represent the concentration profile in diffusion boundary layer between solid and liquid. An expression was obtained between mass transfer flow from spherical particle area and particle size changing with time during dissolution of solids. A mathematical model was developed for calculating particle size distribution varying with time during dissolution of spherical solid particles. The Focker-Planck equation was used to construct the distribution function varying with particle size. Model parameters were estimated by the Genetic Algorithm, the validity of the model was confirmed with experimental data.