Modeling of Liquid-Liquid Extraction Column: A Review (original) (raw)
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Modeling of Liquid - Liquid Extraction Column
2004
There is hardly any chemical process, which does not involve separation of liquid mixtures or recovery of valuable components from reaction products. Liquidliquid extraction processes have been increasingly used with advantage in these operations. The development of sound methods of equipment design has been the present trend. In recent times the approach to data interpretation has undergone a shift towards better modeling of the transport processes yielding new methods of scaleup and design. Liquid extraction modeling demonstrates the performance of the extraction equipment, which includes concentration profile, hold up of dispersed phase along column height, fluid dynamics etc. In the present study, the modeling of a liquid extraction column has been carried out which describes the concentration profile of solute in dispersed phase and continuous phase. In this thesis, an one-dimensional, steady state mathematical model has been developed for the simulation of a Karr reciprocating...
Detailed Mathematical Modelling of Liquid-Liquid Extraction Columns
Computer Aided Chemical Engineering, 2011
A comprehensive bivariate population balance model for the dynamic and steady state simulation of extraction columns is developed. The model is programmed using visual digital FORTRAN and then integrated into the whole LLECMOD program [23]. As a case study, the simulation tool LLECMOD is used to simulate the steady state performance of pulsed packed and sieve plate columns. Two chemical test systems recommended by the EFCE are used in the simulation. Model predictions are successfully validated against steady state and dynamic experimental data, where good agreements are achieved.
Computer Aided Simulation of Liquid-liquid Extraction Columns
Liquid-liquid extraction columns have a small footprint, a high number of theoretical stages and allow high throughput. However, the deviation of the flow field from the ideal plug flow makes the simulation and design of these columns a challenging task. In order to help in this tedious design procedure (scale-up experiments) two simulation tools are presented. The first one is the PPBLAB software, which is based on a one-dimensional CFD (Computational Fluid Dynamics) model. Deviations from the ideal plug flow are accounted by the axial dispersion and by population balance modeling, which accounts for the droplet-droplet interactions and forward mixing of the dispersed phase. The second tool is based on a three dimensional modelling of the flow field using 3D CFD simulation, which is able to describe the local flow field without any geometrical dependent correlations more than the drag coefficient correlation. As a case study, a Kühni mini-plant column is simulated using the one dimensional and the three dimensional tools for comparison. The design procedure of each tool is shown, where the benefits (computational time, local information) of each tool are highlighted.
Chemical Engineering & Technology, 2007
A large number of theories are reported in the literature for the calculation of individual mass transfer coefficients and each has a well defined application range, which depends on the nature of the continuous and the dispersed phases. Each theory is also based on a different transfer mode, e.g., the dispersed phase depends essentially on the drop behavior, which is directly related to the drop size. However, an accurate determination of the overall mass transfer coefficient depends upon the choice of the combination of theories to be used for the calculation of the individual mass transfer coefficients, i.e., for the continuous and dispersed phases. In the present work, different combinations for the calculation of the overall mass transfer coefficient have been tested for the commonly recommended Acetone/Toluene/Water system, which is characterized by relatively large drop sizes.
LLECMOD: A Bivariate Population Balance Simulation Tool for Liquid- Liquid Extraction Columns
The Open Chemical Engineering Journal, 2008
The population balance equation finds many applications in modelling poly-dispersed systems arising in many engineering applications such as aerosols dynamics, crystallization, precipitation, granulation, liquid-liquid, gas-liquid, combustion processes and microbial systems. The population balance lays down a modern approach for modelling the complex discrete behaviour of such systems. Due to the industrial importance of liquid-liquid extraction columns for the separation of many chemicals that are not amenable for separation by distillation, a Windows based program called LLECMOD is developed. Due to the multivariate nature of the population of droplets in liquid -liquid extraction columns (with respect to size and solute concentration), a spatially distributed population balance equation is developed. The basis of LLECMOD depends on modern numerical algorithms that couples the computational fluid dynamics and population balances. To avoid the solution of the momentum balance equations (for the continuous and discrete phases), experimental correlations are used for the estimation of the turbulent energy dissipation and the slip velocities of the moving droplets along with interaction frequencies of breakage and coalescence. The design of LLECMOD is flexible in such a way that allows the user to define droplet terminal velocity, energy dissipation, axial dispersion, breakage and coalescence frequencies and the other internal geometrical details of the column. The user input dialog makes the LLECMOD a user-friendly program that enables the user to select the simulation parameters and functions easily. The program is reinforced by a parameter estimation package for the droplet coalescence models. The scale-up and simulation of agitated extraction columns based on the populations balanced model leads to the main application of the simulation tool. d ) is then obsolete . Accordingly, the promising modelling of these phenomena, based on the population balances, offers not only the dispersed phase hold-up (volume concentration) but also any integral property associated with the resulting particle (droplet) distribution such as the mean droplet size and the specific inter-