alexa Experimental Studies on Hydrodynamics Characteristics of Co-current Three Phase Fluidization Using Different Sizes of Glass Beads and its Prediction by Fuzzy Logic
ISSN: 2157-7048
Journal of Chemical Engineering & Process Technology

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Experimental Studies on Hydrodynamics Characteristics of Co-current Three Phase Fluidization Using Different Sizes of Glass Beads and its Prediction by Fuzzy Logic

Anish T. Achankunju1, Sivalingam A2 and Kannadasan T3
1M.Tech Student, Department of Chemical Engineering, Coimbatore Institute of Technology, Coimbatore, Tamil Nadu, India
2Associate professor, Department of Chemical Engineering, Coimbatore Institute of Technology, Coimbatore, Tamil Nadu, India
3Head of the Department, Department of Chemical Engineering, Coimbatore Institute of Technology, Coimbatore, Tamil Nadu, India
Corresponding Author : Kannadasan T
Head of the Department, Department of Chemical Engineering
Coimbatore Institute of Technology, Coimbatore
641014, Tamil Nadu, India
Tel: +919600734363
E-mail: [email protected]
Received May 02, 2013; Accepted June 24, 2013; Published June 28, 2013
Citation: Achankunju AT, Sivalingam A, Kannadasan T (2013) Experimental Studies on Hydrodynamics Characteristics of Co-current Three Phase Fluidization Using Different Sizes of Glass Beads and its Prediction by Fuzzy Logic. J Chem Eng Process Technol 4:163 doi:10.4172/2157-7048.1000163
Copyright: © 2013 Achankunju AT, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Abstract

The experiment was carried out with different sizes of Glass beads. That is Glass beads of diameter 0.2 cm, 0.4 cm, 0.6 cm. Water was used as a continuous phase and air was used as a dispersed phase. These three different sized Glass beads were used as solids for co-current studies. The three sections of the experimental setup viz. gas liquid disengagement section, test section and gas liquid distributed section. The experiment was conducted with Glass beads with varying liquid velocities and keeping constant gas velocity 0.16985138 cm/sec, 0.212314225 cm/sec, 0.304317056 cm/sec, 0.346779901 cm/sec. The graphs were plotted and their effects on individual phase holdups for various particle sizes were studied. Pressure drop of fluids in the fluidized bed was measured by using mercury manometer and by using ethyl acetate manometer. The phase holdups like solid, liquid, gas were determined, liquid holdup and solid holdup decreases with increase in liquid velocity whereas gas holdup increases with increases in liquid velocity. With the experimental data, simulation studies were carried out using Fuzzy Logic.

Keywords
Gas velocity; Glass beads; Phase holdup; Mercury manometer; Liquid velocity
Introduction
Fluidization is the operation by which solid particles are transformed into a fluid like state through suspension in a gas or liquid. A fluidized bed is formed when a quantity of a solid particulate substance (usually present in a holding vessel) is placed under appropriate conditions to cause the solid/fluid mixture to behave as a fluid [1]. This is usually achieved by the introduction of pressurized fluid through the particulate medium. This results in the medium then having many properties and characteristics of normal fluids; such as the ability to free-flow under gravity, or to be pumped using fluid type technologies. The resulting phenomenon is called fluidization. A fluidized bed demonstrates all the characteristics of a fluid. The static pressure at any height is approximately equal to the weight of bed solids per unit cross section above that level. The solids from the bed may be drained like a liquid through an orifice at the bottom or on the side. An object denser than the bulk of the bed will sink, while one lighter than the bed will float.
Materials and Methods
Experimental setup
The Perspex fluidized bed column used was of 5.4 cm I.D, 6 cm O.D and 160 cm height as shown in Figure 1. The liquid and gas flow rate were measured. The gas and liquid streams were merged and passed through a quick closing valve, a 0.3 cm thick perforated grid before entering the bed. The calming section and the grid ensured that the liquid and the gas were well mixed and evenly distributed into the particles. A tee joint at the top of the column allowed gas to escape and liquid to be recirculated to the reservoir. Pressure tapping were provided at the top and bottom of the test section.
Experimental procedure
The experiment is performed with water at 35°C and gas through the bed of glass beads with diameter 0.2 cm, 0.4 cm, 0.6 cm. The flow rates of both gas and liquid are regulated by the control valves. The liquid flow rate, manometer readings and the bed heights are observed. The gas velocity is kept constant and the liquid velocity is varied. After steady state is attained for each liquid velocity the fluidized bed height and manometer readings are noted. The same procedure is repeated for four different gas velocities. The effect on phase holdups, pressure drop and the bed porosity is studied for different sizes of glass beads at 35°C.
Fuzzy logic
A fuzzy logic (FL)-based expert system (ES) works based on the principle of fuzzy set theory, and it is a potential tool for dealing with imprecision and uncertainty. The FL-based ESs has been developed by various researchers, after realizing their potential in solving real world complex problems. The performance of an ES mainly depends on its KB, which consists of a data base and a rule base. Thus, designing a proper KB is very important, which is difficult too. In this paper fuzzy logic is used to predict gas holdup and liquid holdup for glass beads and gypsum particles for different sizes with varying liquid flow rates by keeping the gas flow to be constant.
Results and Discussion
The hydrodynamic parameters of interest in a three phase fluidized bed are: bed porosity (ε), solid holdup (εs), gas holdup (εg), Liquid holdup (ε1) and fluidized bed pressure drop (ΔP) were calculated using experimental data for both glass beads and gypsum particles [2,3]. The hydrodynamic characteristics like gas holdup and liquid holdup were predicted using fuzzy logic [4] (Tables 1-1.12).
Bed porosity (ε)
The results indicate that the expanded bed voidage depends on phase velocities, properties of solids and the other two phases [5-7]. As the gas phase Modified Reynolds number increases the bed voidage increases; the increase is high at low Modified Reynolds number, whereas it is less at higher Modified Reynolds numbers as shown in the figures. Higher flow rates of the phases lead to larger bed expansion which in turn increases the bed voidage (Figure 2.1 and 2.2). Miura et al. reported increase of bed voidage with increase in superficial liquid velocities and superficial gas velocities. The influence of phase flow rates on ε seems to be considerable at low Modified Reynolds numbers, where it is marginal at high Modified Reynolds numbers.
Solid holdup (εs)
It has been observed that εs decreases steeply as the gas phase Modified Reynolds number increases as well as liquid phase Modified Reynolds number increases (Figure 2.3). Ik-Sang Shin et al. reported similar trends. These trends may be explained as follows; when either liquid velocity or gas velocity is increased, there would be higher drag forces exerted on the solid particles, leading to more bed expansion; this results in reduction of solids holdup in the expanded bed. However, the decrease is considerable at low Modified Reynolds numbers and εs seem to be approaching a constant value at high gas phase Modified Reynolds numbers. Since εs = (1- ε) and ε increase with Modified Reynolds number (gas or liquid) as explained in section 1, εs should decrease with an increase in Modified Reynolds number (Figure 2.4).
Gas holdup (εg)
The gas holdups are found to be increasing with the increase in gas phase Modified Reynolds number and also with the increasing liquid phase Modified Reynolds number as shown in the Figures 2.5 and 2.6; this increase is higher at low Modified Reynolds number (gas or liquid) and approaching a constant value at higher Modified Reynolds number. The gas and liquid phases are moving co-currently through the column; however the liquid phase velocities are higher than gas phase velocities obtained in this work. So, since the gas passage through the column is slower, more gas accumulation occurs in the column compared to liquid accumulation resulting in an increase in the gas holdup, gas holdup vs Modified Reynolds number follows similar trends for all the temperatures. The influence of temperature on phase properties causes a slight decrease of εg with an increase in temperature.
Liquid holdup (ε1)
It is observed that ε1 is decreasing with increasing gas phase Modified Reynolds number as well as liquid phase Modified Reynolds number and approaching a constant value at higher Modified Reynolds numbers (Figure 2.7). The gas and liquid phases are moving cocurrently through the column; however the liquid phase velocities are higher than gas phase velocities obtained in this work. So, since the liquid passage through the column is faster, less liquid accumulation occurs in the column and this accumulation decreases with increase in liquid velocity; this results in reduction in liquid holdup as the liquid phase Modified Reynolds number increases (Figure 2.8).
Pressure drop (ΔP)
The results show that the pressure drop increases with increase in Modified Reynolds number (both gas and liquid) (Figures 2.9 and 2.10). An increase is observed with lower liquid phase Modified Reynolds number whereas the increase is gradual with high liquid phase Modified Reynolds number. Pressure drop is higher for large particle sizes.
Simulation
A training data set, which is required to design the optimal knowledge base of the fuzzy logic-based expert system [8-13], is collected by conducting experimental studies on hydrodynamics characteristics of co-current three phase fluidization [14] (as discussed in the earlier section) using fluidized bed for different combinations of parameters [15,16].
To develop a fuzzy logic-based expert system for the above problem, four parameters, namely Euler’s number (Figures 3.1 and 3.2), Reynolds number, particles diameter, liquid and gas flow rates are considered as inputs where gas holdup and liquid holdup as two outputs [17]. Five linguistic terms are considered for each of the input and output variables, namely Very Low (V_LOW), Low (LOW), Medium (MED), High (HIGH) and Very High (V_HIGH). For simplicity, the shape of the membership function distributions is assumed to be triangular. As there are five linguistic terms for element size and shape ratio each, a total of 25 (i.e., 5.5) rules are to be considered.
Thus, a typical rule will look as follows:
IF EU is V_HIGH AND NRE is V_LOW AND DIA is LOW AND GFR is V_LOW, THEN GHP is MED
Conclusion
Improvement of mixing between liquid and solid particle in a fluidized bed can be achieved by a simple and effective method. Phase holdups, bed porosity and pressure drop in a gas-liquid-solid fluidized bed showed a marked variation with particle size and liquid flow rate at constant gas flow rate. Pressure drop is higher for large particle sizes. In the break-up regime, the gaseous phase forms a uniform dispersion of small bubbles. The gas holdup is greater in smaller particle and increase with increase in gas flow rate. Bed porosity increase with increase in gas flow rate and it is high in small particle. It is found that design calculations regarding three phase fluidized beds are based on phase holdups, flow pattern of the fluid phase and extent of mixing. The system mainly depends on good contact between solid and liquid. Fuzzy logic based expert system is used to predict the phase holdups.
For Future Work
Genetic algorithm may be used to tune fuzzy knowledge base to improve performance of the expert system.
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Tables and Figures at a glance

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Table 1.1   Table 1.2   Table 1.3   Table 1.4   Table 1.5   Table 1.6
 
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Table 1.7   Table 1.8   Table 1.9   Table 1.10   Table 1.11   Table 1.12

 

Figures at a glance

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Figure 1   Figure 2.1   Figure 2.2   Figure 2.3   Figure 2.4
 
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Figure 2.5   Figure 2.6   Figure 2.7   Figure 2.8   Figure 2.9
 
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Figure 2.10   Figure 3.1   Figure 3.2  
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