Elsevier

Powder Technology

Volume 327, March 2018, Pages 430-441
Powder Technology

CFD simulation of the preheater cyclone of a cement plant and the optimization of its performance using a combination of the design of experiment and multi-gene genetic programming

https://doi.org/10.1016/j.powtec.2017.12.091Get rights and content

Highlights

  • •

    A combination of CFD simulation with MGGP and DOE was performed to predict performance of a preheater cyclone.

  • •

    The parameters that affect the value of critical diameter were studied.

  • •

    Design of experiments was used to investigate the effect of three cyclone dimensions.

  • •

    Euler number and efficiency were modeled by using multi-gene genetic programing.

  • •

    Preheater cyclone performance was optimized using two-objective optimization.

Abstract

Hurriclon cyclone is a specially designed preheater cyclone with two outlet connector pipes of cleaned gas in the cement industry. In Kerman cement plant, Iran, the initial structure of this cyclone was changed. This caused a decrease in the cyclone efficiency. In this study, to optimize the changed cyclone performance, one of the twin cyclones in the first-stage of the preheater tower, which had the most significant effect on particle separation from gas was simulated and validated by computational fluid dynamics. Using the design of experiment based on the simulation results, the effects of three dimensions (vortex-finder length, cylinder height, and cone tip diameter) were investigated on cyclone performance. The turbulent gas flow inside the cyclone was modelled using the Reynolds stress model due to the swirling flow inside the cyclones. The discrete phase model was used to calculate the trajectory of particles. It was observed that because of high gas inlet velocity and particle density as well as the geometry of the preheater cyclone, particles larger than the critical diameter continue spinning in the cyclone. The Multi-Gene Genetic Programming (MGGP) was used to obtain two equations for efficiency and pressure drop in order to optimize the preheater cyclone performance. For this purpose, two-objective optimization using the Genetic Algorithm (GA) was performed. The optimization results showed that by using the optimized dimensions for the preheater cyclone, the pressure drop decreases by 2.2% and the efficiency increases by 13.4%.

Introduction

The application of cyclone separators in separating particles from gas flow began hundreds of years ago. Owing to the wide range and simplicity of the cyclone structure that leads to a low cost of investment and maintenance, they are still widely used in the chemical and petrochemical industries. The main parameters of cyclone performance are separation efficiency and pressure drop [1]. Many efforts have been made to derive an appropriate mathematical model for the study and prediction of flow behaviour as well as to find suitable cyclone geometries. However, due to the hydrodynamic complexity of cyclones, no exact mathematical model for cyclones has been offered yet. For numerical solutions, CFD is a proper tool [2], [3]. The key to the successful use of CFD for finding turbulent flow pattern depends on the selection of the right turbulence model. Selecting a suitable turbulence model has been studied by many researchers [2], [4]. The result of the Reynolds stress model (RSM) among the turbulence models has a very good agreement with the experimental data [5], [6], [7], [8] since the isotropy of the flow assumption is ignored. In addition, large-eddy simulation methodology can predict turbulent flow inside the cyclone [4], [9], [10].

The pressure drop and the cut-diameter in cyclones are important objective functions, to be optimized simultaneously.Cyclone geometry has a significant effect on its performance; various researches have been conducted to investigate the effect of geometrical parameters on cyclone performance [11], [12], [13]. Safikhani et al. [14] obtained the pressure drop and cut-diameter by CFD and then optimized the cyclone performance with the assistance of multi-objective optimization; the artificial neural network was then used to calculate the objective function. Elsayed and Lacor performed many studies in order to optimize the cyclone [15], [16], [17]. They used multi-objective optimization for the performance of the cyclone [18]. Two radial-basis function neural networks were used to model the pressure drop and the cut-diameter. Their results showed a noticeable influence of the vortex finder diameter and its length, the inlet width, and the total height on the efficiency of the cyclone. Fathizadeh et al. [19] used Leith and Licht theory to prepare some algorithms to obtain the dimensions of the Stairmand cyclone. Vortex finder length was optimized using genetic algorithm to prevent the direct escape of particles from vortex finder.

Owing to environmental concerns-and as the cement industry is one of the major producers of greenhouse gases-strict regulations have been enforced in this industry. In recent years, different researches on the various techniques that improve the cement production process and reduce resultant pollution [20] have been carried out. Mikulcic et al. [21] showed the application of CFD in the implementation of the calcination reaction, which is carried out in calciner in order to reduce carbon dioxide emissions in the cement industry. Mikulcic et al. [22] numerically studied gas-solid flows in a cement cyclone using the Eulerian-Lagrangian approach. The heat exchange phenomenon in the cyclone, arising from the heat exchange between the gas-solid phase and the endothermic calcination reaction, was investigated. Cristea and Conti [23] studied the heat exchange between the gas and the solid phase in a cement plant preheater. They concluded that the most of the heat distribution occurs within the duct, and the temperatures of the gas and particles in the cyclones remain approximately constant and equal. Ferrite and Ari [9] optimized the preheater cyclone by means of the Taguchi method. They optimized the cyclone performance by changing the four parameters of diameter, vortex-finder length, velocity inlet, and the concentration of particles. By modernizing the design of cyclone preheaters, significant energy saving can be achieved. The role of the first-stage cyclones is significantly important as specifying the separation efficiency. Wasilewski and Duda [24] for optimizing the first-stage cyclones proposed guidelines depending on the objective function. In another study [25] they optimized the geometry of cyclone. Mariani et al. [26] optimized the length and angle of vortex finder to increase the separation efficiency and decrease the exit gas temperature.

Section snippets

Background

In traditional cement manufacturing technology, the preheater system is positioned before the rotary kiln in order to increase the heat transfer between the raw materials and hot gases. Raw materials in the preheater are gradually dried, heated, and calcined by moving against the flow of the hot gases coming from the rotary kiln. In Fig. 1, a rotary kiln with a suspension preheater similar to that one from Kerman cement plant is shown. Preheaters are built in several stages in order to increase

The governing equations

For an incompressible and steady-state fluid flow, the continuity equation for the mean flow is as follows [29]:∂ui∂xi=0

The time-averaged Navier–Stokes equation is as follows [29]:∂∂xjρuiuj=−∂p∂xi+∂∂xjμ∂ui∂xj+∂uj∂xi−23δij∂uk∂xk+∂∂xj-ρuj′uk′¯

The last term is defined as the Reynolds stress tensor, which reflects the effects of turbulent fluctuations in the fluid flow. The RSM used in this study is required for solving equations for each of the Reynolds stresses. In the Reynolds stress model, the

Cyclone geometry

The cyclone was a scroll type in which the radius of the cylindrical part (R) was 1.26 m and the radius of the scroll part (Rs) was 1.722 m, which was located at a distance of δr = 0.64 m from the cylinder centre. Cyclone dimensions are provided in Table 1; it consists of cyclone diameter (D), inlet height (a) and width (b), vortex-finder diameter (De) and length (S), the height of outlet pipe (l) (it was selected greater than usual, in order to be sure of accessing fully developed flow in the

Multi-gene genetic programming

Genetic algorithm is a search technique in computer science used to find approximate solutions for optimization. Genetic algorithms apply the principle of Darwin's theory. (According to Darwin's theory, the generations that have better characteristics than other generations will have a better chance of survival and reproduction; their superior characteristics are also transmitted to the next generation). Genetic algorithm with random initial population generation checks the problem space

The mesh independency and the validation of the model

The computational results of the three different meshes for the preheater cyclone pressure drop and efficiency are provided in Table 2, Table 3 respectively. Since the pressure drop and cyclone efficiency difference between both the sequential meshes were minimum (< 5%), the CFD results are independent of the mesh size. To reduce computational times, the mesh number of 2,208,864 was used in this study. The last row in Table 2, Table 3 represent experimental pressure drop and efficiency of the

Conclusions

The first-stage cyclones' efficiency in the preheater system of a cement plant is very important. In this study, one of the twin cyclones in the first-stage of the preheater in the Kerman cement plant was investigated using a combination of CFD, the design of the experiment, and multi-gene genetic programming. Since its structure had been changed, a decrease in its efficiency had taken place. In the same pressure drop and volumetric flow rate, the Stairmand cyclone efficiency was 2.5% greater

Nomenclature

    a

    inlet height (m)

    b

    inlet width (m)

    B

    the cone-tip diameter (m)

    D

    cyclone diameter (m)

    De

    vortex-finder diameter (m)

    Dij

    stress diffusion

    Ef

    efficiency

    Eu

    Euler number

    h

    cylindrical part height[m]

    hs

    part of the scroll height (m)

    H

    the cyclone total height (m)

    Hc

    conical height (m)

    L

    the height of outlet pipe (m)

    P

    pressure (Pa)

    Pij

    shear production

    r

    radius of cyclone (m)

    S

    vortex-finder length (m)

    U

    inlet velocity (m/s)

    ui

    time averaged fluid velocity i (m/s)

    u′i

    fluctuating velocity to direction i (m/s)

    u′¯

    sub grid scale velocity

Acknowledgements

The authors acknowledge the Kerman cement plant, Iran in allowing them to use their experimental data.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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