ion and CFD Modelling of Ammonia and Urea Production

Edited by Foxit Reader Copyright(C) by Foxit Corporation,2005-2009 Journal of Industrial and Engineering Chemistry 16 (2010) 577–586 For Evaluation Only. Contents lists available at ScienceDirect

Journal of Industrial and Engineering Chemistry journal homepage: www.elsevier.com/locate/jiec

Optimization of ammonia production from urea in continuous process using ASPEN Plus and computational fluid dynamics study of the reactor used for hydrolysis process J.N. Sahu a,b,*, V.S. Rama Krishna Chava a, Shadab Hussain a, A.V. Patwardhan c, B.C. Meikap a,d a

Department of Chemical Engineering, Indian Institute of Technology (IIT), Kharagpur, P.O. Kharagpur Technology, West Bengal 721302, India Department of Chemical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Pin 50603, Malaysia Department of Chemical Engineering, Institute of Chemical Technology (ICT), Mumbai 400019, India d School of Chemical Engineering, University of KwaZulu-Natal, Faculty of Engineering, Howard College Campus, King George V. Avenue, Durban 4041, South Africa b c

A R T I C L E I N F O

A B S T R A C T

Article history: Received 1 November 2009 Accepted 12 January 2010

The present study addresses the methods and means to safely produce relatively small amounts (i.e., up to 50 kg/h) of ammonia. The optimization and simulation study conducted for continuous process and effect of operation conditions like reaction temperature, initial feed concentration and pressure on ammonia production carried out using ASPEN Plus. Also, a computational fluid dynamics (CFD) model was proposed to simulate the hydrolysis of urea for synthesis of ammonia. A series of parametric studies to investigate flow rates, thermal boundary conditions and reactor geometry was performed for hydrolysis of urea and the optimized operating conditions and reactor geometry were obtained. Detailed three-dimensional flow, heat and chemistry simulations of ammonia, carbon dioxide and ammonium carbamate. The study demonstrates that simulation is a useful tool for diagnosing hydrolysis reactor mixing pathologies and for identifying practical countermeasures that could improve process performance. ß 2010 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

Keywords: Hydrolysis of urea Ammonia Computational fluid dynamics (CFD) Simulation Modelling Optimization

1. Introduction Ammonia is an extremely important chemical that has innumerable uses in a wide range of areas, including process industry, and utility uses [1–3]. Many industrial plants require the supply of large quantities of ammonia, which frequently must be transported through and stored in populated areas. Important users among these are industrial furnaces, incinerators and electric power generation industries [4,5]. All of these are faced with a lowering of the amount of nitrogen oxides being discharged to the atmosphere in the combustion gases being emitted from their operations, as required by environmental regulations [6–12]. Another important use is for the so-called ‘‘conditioning’’ of flue gas by which an improved collection and removal of particles matter (fly ash) is obtained [13–22]. But unfortunately, ammonia presents significant danger to human health as a hazardous chemical. Its transportation, storage and handling triggers serious

* Corresponding author at: Department of Chemical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Pin 50603, Malaysia. Tel.: +60 3 7967 5295; fax: +60 3 7967 5319. E-mail addresses: [email protected], [email protected] (J.N. Sahu).

safety and environmental regulatory requirements for risk management plans, accident prevention programs, emergency response plans and release analysis [23–25]. The present study is concerned with the methods and means to safely produce relatively small amounts (i.e., up to 50 kg/h) of ammonia. There are several chemical processes that are used to manufacture ammonia. The three most prevalent methods include the Haber–Bosch process, indirect electrochemical dissociation, and urea decomposition [26]. The Haber–Bosch process reacts gaseous hydrogen and nitrogen over a metal catalyst at high temperatures (e.g., at 748 K) and pressures (e.g., at 20 MPa). This process is a proven large-scale industrial process; however, it uses harsh conditions and has not been proven technically or economically effective below the ton/hour range. The electrochemical dissociation process has been proposed by some in the semiconductor industry as an alternative to the Haber–Bosch process for the generation of ammonia. This process also react hydrogen and nitrogen. However, it is an indirect synthesis via a molten alkali-metal halide electrolyte with nitrogen introduced at the cathode and hydrogen introduced at the anode. The electrochemical dissociation process also operates at elevated temperatures (e.g., at 673 K) but at ambient pressure. While utilizing less harsh operating conditions or parameters than the Haber–Bosch

1226-086X/$ – see front matter ß 2010 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.jiec.2010.03.016

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Edited by Foxit Reader Copyright(C) by Foxit Corporation,2005-2009 J.N. Sahu et al. / Journal of Industrial and Engineering Chemistry 16 (2010) 577–586 For Evaluation Only.

Fig. 1. Schematic of urea hydrolysis system used in thermal power plants.

process, the electrochemical dissociation process has not been proven above pilot scale production rates and has a high risk of alkali metal contamination. Another concern with adopting these two processes for generating ammonia it that the Haber–Bosch and electrochemical distribution processes require large amounts of hydrogen, which adds significantly to the risk of operating an ammonia generation facility. An alternative approach to ammonia supply suggested in the late eighties includes using urea feedstock to generate ammonia on site [27]. The method of urea to ammonia conversion by hydrolysis process, urea is an ideal candidate for the manufacture of ammonia [3,23–27]. Urea is an environmentally safe material used primarily as fertilizer. Urea is a non-toxic chemical compound and presents essentially no danger to the environment, animals, plants life and human beings. It is solid under ambient temperatures and pressures. Consequently, urea can be safely and inexpensively shipped in bulk and stored for long periods of time until it is converted into ammonia. It will not leak, explode, be a source of toxic fumes, require pressurization, increase insurance premiums, require extensive safety programs, or be a concern to the plant, community and individuals who may be aware of the transportation and/or storage dangers of ammonia. It has been determined that using urea thermal hydrolysis is the preferred process for converting urea/water solution into a gaseous mixture containing ammonia, carbon dioxide and water vapor [28]. A typical urea hydrolysis process used in industry is shown in Fig. 1. The published information in literature about hydrolysis of urea for production of ammonia is very little detailed and patented [4,5,27–37]. However, in our early laboratory study [38–44] gives clear overview regarding the equilibrium and kinetic study of urea hydrolysis for production of ammonia in batch and semi-batch reactors. Batch and semi-batch reactors were easy to use in the laboratory study, but less convenient for industrial applications. Therefore, we decided to study more thoroughly the continuous process for optimization of operating variable using ASPEN Plus by using all data achieved in early study. Also a modelled, using computational fluid dynamics (CFD) approach to determine the local and instantaneous values of liquid velocity, temperature and reactant concentrations inside the reactor.

Fig. 2. Effect of temperature on production of ammonia in CSTR.

and employs two reaction steps as follows [45–48]: Heat

NH2 CONH2 þ H2 O ! urea

water

NH2 COONH4 ; ammonium carbamate

The ammonium carbamate decomposed then to yield carbon dioxide and ammonia gases: NH2 COONH4 ammonium carbamate

þHeat

! 2NH3 þ ammonia

CO2 ; carbon dioxide

(2)

DH2 ¼ þ177 kJ=mol The first reaction in which urea hydrolyzes to form ammonium carbamate is mildly exothermic, while the second, in which ammonia and carbon dioxide are produced, is strongly endothermic, with the result that the reaction to release ammonia and carbon dioxide requires heat and quickly stops when the supply of heat is withdrawn. Excess water promotes the hydrolysis reaction, the overall reaction for which is as follows: xH2 O þ NH2 CONH2 ! 2NH3 þ CO2 þ ðx 1ÞH2 O;

DHoverall ¼ þ161:5 kJ=mol

2. Reaction pathway The hydrolysis of urea to ammonia is endothermic and proceeds rapidly above a temperature of approximately 373 K. The basic chemistry employed in the process is the reverse of that employed in industrial production of urea from ammonia and carbon dioxide

(1)

DH1 ¼ 15:5 kJ=mol

Fig. 3. Effect of pressure on production of ammonia in CSTR.

(3)


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Fig. 6. Effect of pressure on production of ammonia in PFR.

Fig. 4. 3D combine effect of pressure and temperature on production of ammonia in CSTR.

The completion of the reaction is favored by high temperature, stirring speed and high reaction pressure. The overall reaction is endothermic and the first reaction, i.e. urea to ammonium carbamate reaction is a slow reaction and the second reaction is very fast and goes towards completion [47,48]. 3. Results and discussion 3.1. ASPEN Plus simulations ASPEN Plus is widely accepted in the chemical industry as a design tool because of its ability to simulate a variety of steadystate processes ranging from single unit operation to complex processes involving many units [49–53]. Consequently, ASPEN Plus

Fig. 5. Effect of temperature on production of ammonia in PFR.

was chosen as a framework for the development of a hydrolysis process simulation. Since there is no hydrolysis of urea model provided by ASPEN PLUS, we must develop our own using the tools offered by ASPEN Plus 15, 16. In addition to its conventional reactor models, ASPEN Plus has the flexibility to allow the insertion of Fortran blocks and user kinetic subroutines into the simulation. In this work, it was optimized and simulation for a continuous process to produce 50 kg/h ammonia from urea. It determined the type of reactor to be used as continuous stirred-tank reactor (CSTR) or plug flow reactor (PFR) and also it found out the process variables optimization. The ammonia output from a reactor depends on four factors. They are (i) feed input, (ii) temperature, (iii) pressure, and (iv) reactor volume. It has two types of reactors that are generally used viz. CSTR and PFR. So for choosing the type of reactor it need to check which reactor gives more ammonia output under same conditions of feed flow, temperature, pressure and reactor volume. The simulations for the reactors CSTR and PFR

Fig. 7. 3D combine effect of pressure and temperature on production of ammonia in PFR.

J.N. Sahu et al. / Journal of Industrial and Engineering Chemistry 16 (2010) 577–586

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Table 1 Optimization of production of ammonia from urea. Initial feed concentration (wt%)

Pressure (atm)

Temperature (K)

Feed rate (kg/h)

Urea in feed (kg/h)

Water in feed (kg/h)

Ammonia (kg/h)

CO2 (kg/h)

30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50

4 4 4 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 8 8 8 8 8 3 3 4 4 4 4 4 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 3 3 3 3 3 4 4 4 4 4 5 5 5 5 5 6 6 6 6

403 413 423 393 403 413 423 433 393 403 413 423 433 393 403 413 423 433 393 403 413 423 433 413 423 393 403 413 423 433 393 403 413 423 433 393 403 413 423 433 383 393 403 413 423 433 383 393 403 413 423 433 443 423 433 393 403 413 423 433 393 403 413 423 433 393 403 413 423 433 393 403 413 423

530 520 520 500 440 420 420 460 450 400 370 370 400 420 370 350 340 360 400 360 340 330 330 470 460 440 380 350 340 380 380 330 300 300 320 340 300 280 270 280 380 320 280 260 260 260 360 300 270 250 250 250 270 260 260 450 370 320 310 350 350 290 260 250 270 300 260 230 230 240 270 240 220 210

159 156 156 150 132 126 126 138 135 120 111 111 120 126 111 105 102 108 120 108 102 99 99 188 184 176 152 140 136 152 152 132 120 120 128 136 120 112 108 112 152 128 112 104 104 104 144 120 108 100 100 100 108 104 104 225 185 160 155 175 175 145 130 125 135 150 130 115 115 120 135 120 110 105

371 364 364 350 308 294 294 322 315 280 259 259 280 294 259 245 238 252 280 252 238 231 231 282 276 264 228 210 204 228 228 198 180 180 192 204 180 168 162 168 228 192 168 156 156 156 216 180 162 150 150 150 162 156 156 225 185 160 155 175 175 145 130 125 135 150 130 115 115 120 135 120 110 105

50.5 50.5 50.0 50.4 50.5 50.8 50.4 50.0 50.4 50.7 50.1 50.5 51.0 50.5 50.0 50.3 50.0 50.9 50.7 50.5 50.6 50.5 50.0 50.6 50.6 50.2 50.1 50.2 49.9 50.1 50.8 50.8 49.98 50.7 50.6 50.44 50.6 50.7 49.9 49.5 50.2 50.8 50.2 49.8 50.9 49.4 50.7 50.3 50.3 49.6 50.8 50.0 50.0 50.9 49.4 50.2 50.5 50.85 50.5 50.2 50.7 50.2 50.2 49.4 49.5 50.5 50.9 49.4 50.3 49.9 50.2 50.8 50.4 49.2

65.3 65.3 64.6 65.07 65.3 65.7 65.1 64.6 65.1 65.4 64.8 65.2 65.9 65.3 64.5 65.0 64.6 65.8 65.4 65.2 65.3 65.3 64.7 65.4 65.4 64.8 64.8 64.9 64.4 64.7 65.6 65.68 64.58 65.5 65.4 65.2 65.4 65.5 64.5 63.9 64.8 65.6 64.8 64.4 65.7 63.8 65.5 64.9 65.0 64.0 65.7 64.5 64.6 65.7 63.8 64.8 65.2 65.7 65.27 64.9 65.5 64.8 64.8 63.9 63.99 65.3 65.7 63.9 65.1 64.5 64.8 65.7 65.1 63.6


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Table 1 (Continued ) Initial feed concentration (wt%)

Pressure (atm)

Temperature (K)

Feed rate (kg/h)

Urea in feed (kg/h)

Water in feed (kg/h)

Ammonia (kg/h)

CO2 (kg/h)

50 50 50 50 50 50 50 50 50 50 50 50 50 50

6 7 7 7 7 7 7 8 8 8 8 8 8 8

433 393 403 413 423 433 443 383 393 403 413 423 433 443

220 250 220 210 200 210 230 290 240 220 200 200 200 220

110 125 110 105 100 105 115 145 120 110 100 100 100 110

110 125 110 105 100 105 115 145 120 110 100 100 100 110

49.6 49.8 49.5 50.3 49.0 50.0 50.7 50.5 50.1 51.0 49.5 50.5 49.6 51.2

64.1 64.3 63.9 65.0 63.4 64.6 65.5 65.2 64.7 65.9 64.0 65.3 64.0 66.1

for calculating the output of ammonia varying the temperature, pressure, input feed rate and reactor volume in ASPEN Plus. 3.1.1. Continuous stirred-tank reactor The single effect of temperature on production of ammonia study for CSTR is presented in Fig. 2. The ammonia output increase with increase in temperature initially and reaches a maximum after which it starts decreasing with increase in temperature. Thus it will have a point of maximum output for ammonia at a particular temperature when other parameters (pressure, feed rate, reactor volume) are kept constant. This maximum output will be at temperature around 423 K. The effect of pressure on production of ammonia can be seen from Fig. 3 keeping temperature, feed flow rate and reactor volume constant. It observed that there is increase in output of ammonia with pressure till some point and after this change in output will become very less with increase in pressure. After crossing this point it can consider that ammonia output does not vary with pressure. The three dimensional response surfaces which were constructed to show the most important two variables (reaction

Fig. 8. 3D geometry of reactor with meshing created in Gambit (front view).

temperature and pressure) on the production of ammonia at constant reaction time and constant reactor volume is shown in Fig. 4. A maximum production of ammonia achieved 64 kg/h at inlet feed concentration 50 wt% of urea and pressure 6 atm in the CSTR.

Fig. 9. (a) Plot of velocity vector colored by velocity magnitude along the wall of reactor (m/s); (b) plot of velocity vector colored by velocity magnitude along the impeller of reactor (m/s).

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Edited by Foxit Reader Copyright(C) by Foxit Corporation,2005-2009 J.N. Sahu et al. / Journal of Industrial and Engineering Chemistry 16 (2010) 577–586 For Evaluation Only. increase in output of ammonia with pressure till some point and after this change in output will become very less with increase in pressure. After crossing this point it can consider that ammonia output does not vary with pressure. In Fig. 7 shows the three dimensional response surfaces, the combined effect of reaction temperature and pressure on production of ammonia at constant reaction time and inlet feed concentration. A maximum production of ammonia achieved 80 kg/h at inlet feed concentration 50 wt% of urea and pressure 6 atm in the PFR.

Fig. 10. Contours of static pressure (Pascal) along the impeller of reactor (front view).

3.1.2. Plug flow reactor It can be seen from Fig. 5 that the production of ammonia is function of temperatures. It increases exponentially with increase in temperatures. The ammonia output increases with increase in temperature initially and reaches a maximum after which it starts decreasing with increase in temperature. Thus it will have a point of maximum output for ammonia at a particular temperature when other parameters (pressure, feed rate, reactor volume) are kept constant. From Fig. 6 it can seen that the effect of pressure on production of ammonia in PFR. The simulation run keeping temperature, feed flow rate and reactor volume constant. It was observed that there is

3.1.3. Comparison of reactors performance From the above study, it observe that for same reaction conditions and same feed rate, the output of ammonia is slightly more in the case of PFR than in CSTR. But there are certain problems that are associated with use of PFR. Handling of Plug Flow reactor is difficult. Also there is the chance of solid deposition (ammonium carbamate) which will cause problems to the flow in case of PFR. But this does not happen in case of CSTR as there is continuous agitation. Therefore to avoid the above said problems it decided to use CSTR for the hydrolysis process even though yield is slightly more in case of PFR. Now it needs to find out optimization the reaction conditions and feed rate that should be given for obtaining 50 kg/h ammonia as product in CSTR. There may be different sets of conditions possible. It needs to consider the cost as well as the problems that arise in each case. 3.1.4. Optimization production of ammonia Table 1 gives the temperature and feed rate required in a pressure range of 3–8 atm to give the desired output of 50 kg/h ammonia production at various concentrations of urea in water. It observed as the concentration of urea is increased there is large

Fig. 11. Contours for temperature plots at different reaction times (a) 1.5 min, (b) 2.5 min, (c) 5 min, and (d) 7 min.


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Fig. 12. Contours for production of ammonium carbamate plots at different reaction times (a) 3 min, (b) 12 min, and (c) 30 min.

decrease in the amount of water in the solution required and also a small amount of decrease in case of urea also. With decrease in the quantity of water the heat requirement will also be lessened greatly along with the requirement of urea which is desirable. But it cannot go beyond 50% concentration as the problem of solubility of urea in water arises. So it will fix our concentration to be 50% urea by weight. In each case it can see that the optimum temperature is 413–423 K as this is the range where the minimum amount of urea is required to get the desired output. Also the optimum pressure will be between 5 atm and 6 atm. From the ASPEN Plus simulations it finds out that the volume of the reactor required to carry out the process must be 20 l. 3.2. CFD simulations A computational technology that enables us to study the dynamics of things that flow is CFD. Using CFD, we can build a computational model that represents a system or device that we want to study. Then apply the fluid flow physics and chemistry to this virtual prototype, and the software will output a prediction of the fluid dynamics and related physical phenomena. Therefore, CFD is a sophisticated computationally based design and analysis technique. CFD software gives us the power to simulate flows of gases and liquids, heat and mass transfer, moving bodies, multiphase physics, chemical reaction, fluid-structure interaction and acoustics through computer modeling [54–57]. In the present work, the system investigated consists of a flat bottom stirred cylindrical reactor (diameter, T and liquid height, H both equal to 132 mm) with impeller having two sets of blades on.

The shaft (diameter is 5 mm) of the impeller is concentric with the reactor axis and extends to a distance of 10 mm from the bottom of the reactor. A standard Rushton turbine (diameter, D = T/ 3 = 100 mm) is used in all the simulations. The impeller offbottom clearance is (C = 10 mm) measured from the agitator midplane. A commercial grid-generation tool (GAMBIT 2.0 of Fluent Inc., USA) is used to model the geometry and to generate the body-fitted grids. It is very important to use an adequate number of computational cells while numerically solving the governing equations over the solution domain. With the available dimensions of the reactor three-dimensional geometry is created. For meshing, tetrahedral meshes are used for reactor. Based on our previous experience and some preliminary numerical experiments, about 300 computational cells are used for the simulations. As the whole study is based on the reaction in the reactor, following is a gambit diagram of a 3-D reactor, which has impellor with two sets of blades on it as shown in Fig. 8. Using Fluent the created geometry by Gambit can be read and simulation is done. For analysis of the results the contour plots and vector plots are analyzed. Residual plot is observed continuously during simulation. Accuracy and convergence are very important during simulation. Current study involves two things: one is to create three-dimensional geometry in Gambit along with the meshing, and second is to know the general procedure to simulate this reactor. Analysis of the result is also important to know the flow field and pressure distribution. Computations are carried out for constant impeller rotational speed of 1200 rpm. For the given operating condition, the flows in the stirred vessel are in a turbulent region. Wall functions are used

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Fig. 13. Contours for production of ammonia plots at different reaction times (a) 2 min, (b) 4 min, (c) 10 min, (d) 12 min, (e) 16 min, (f) 20 min, and (g) 30 min.

to specify the wall boundary conditions. The top surface of the liquid pool is assumed to be flat and is modeled as symmetry (zero normal velocity and zero shear stress). All the computations are carried out until the desired convergence criteria are satisfied

(residues less than 106). Fig. 9(a) shows the velocity magnitude plot indicted along the rector wall, where Fig. 9(b) shows the velocity magnitude plot indicated along the impeller. Fig. 9(a) and (b) shows the velocity magnitude plot indicated by the velocity


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Fig. 14. Contours for production of carbon dioxide plots at different reaction times (a) 3 min, (b) 8 min, and (c) 10 min.

vectors and it is observed that the turbulent flow which goes inside our batch reactor. This turbulence only ensures the proper mixing and the uniformity of temperature and reactants throughout the reactor. This distribution of the absolute pressure contour can also be seen from Fig. 10. Colors indicated in this figure have the same significance as that of Fig. 9 (b). This model also indicates that at the operating conditions with an assured almost perfect mixing. The model was developed through simulation helps to answer a lot of questions about the dependency of the reaction on its parameters. Although the assumptions in the model tilt it towards the ideal side, it still able to predict the nature of the reaction and the changes, in accordance to the variation it brings about in the reaction parameters. The simulation was performed for different reaction times, keeping other parameters constant, as temperature 423 K, initial feed concentration equals to 50 wt% of urea and stirring speed equals to 1200 rpm. The effect of temperature at different reaction time can be seen from Fig. 11. The model predicts the contours temperature plots performance of the reactor more accurately, see also Fig. 11. It is evident from Fig. 12 that, the percent conversion of ammonium carbamate increases with increase in reaction time. Fig. 13 shows the contours for ammonia i.e. the initial molar concentration of urea and its concentration after reaction time at constant reaction temperature with constant stirring speed, 1200 rpm, and initial feed concentration 50 wt% to urea. Also from Fig. 14, it is clear that with the increase the reaction time the production of carbon dioxide increases. From the figure, it has been a very clear idea about the dependence of the reaction on time. As the contours are based on region wise concentrations, therefore in order to get the numerical value of concentration, it assumed it to be averaged over the entire area.

4. Conclusions A model was developed for the hydrolysis of urea for production of ammonia using the ASPEN Plus simulator. To provide such a hydrolysis model, several ASPEN Plus unit operation blocks were combined and, where necessary, kinetic expressions and hydrodynamic model were developed using data and models from the early study. It found out the output of ammonia varying temperature, pressure, initial feed flow rate at various concentration of urea solution with the help of Aspen Plus. In both CSTR and PFR, it observed that the output of ammonia will increase with increase in temperature up to a certain point and then decreases when the other parameters (pressure, feed flow, reactor volume) are kept constant. Also the output increases with increase in pressure but after some point the increase is very small. It was observed that for same reaction conditions and same reactor volume, the output of ammonia is slightly more in case of PFR than in CSTR. But it end up using CSTR in design as the reactions is heterogeneous and deposition of solids may occur in PFR. But this deposition does not take place in CSTR as there is continuous agitation. Also a computational fluid dynamics model was used to simulate the hydrolysis of urea for synthesis of ammonia. The study capable of modeling fluid flow, heat transfer, and chemical reactions in complex reactor geometries. Detailed parametric studies were performed to improve the urea conversion in the presence of double impeller and thermal conditions. A detailed fluid flow, heat transfer, and chemical reactions simulation of ammonia was also performed. The simulations revealed various details about mixing non-idealities inside the reactor chamber.

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This study demonstrates that CFD simulation is a useful tool for diagnosing hydrolysis reactor mixing pathologies and for identifying practical countermeasures that could improve reactor performance. Acknowledgements The authors would like to gratefully acknowledge the financial support to the National Thermal Power Corporation (NTPC), New Delhi, India, has extended towards them for this work. References [1] Won-Joon Choi, Byoung-Moo Min, Byung-Hyun Shon, Jong-Beom Seo, KwangJoong Oh, J. Ind. Eng. Chem. 15 (5) (2009) 635. [2] Gang-Woo Lee, Byung-Hyun Shon, Jeong-Gun Yoo, Jong-Hyeon Jung, KwangJoong Oh, J. Ind. Eng. Chem. 14 (4) (2008) 457. [3] Young-Ok Park, Keon-Wang Lee, Young-Woo Rhee, J. Ind. Eng. Chem. 15 (1) (2009) 36. [4] H.B.H. Cooper, H.W. Spencer, U.S. Patent Application No. US 6,730,280 B2 (2004). [5] H.W. Spencer, H.J. Peters, U.S. Patent Application No. US 6,436,359 B1 (2002). [6] R.M. Heck, Catal. Today 53 (1999) 519. [7] F. Nakajima, I. Hamada, Catal. Today 29 (1996) 109. [8] P. Forzatti, Catal. Today 62 (2000) 51. [9] M. Devadas, O. Kro¨cher, M. Elsener, A. Wokaun, N. So¨ger, M. Pfeifer, Y. Demel, L. Mussmann, Appl. Catal. B: Environ. 67 (3/4) (2006) 187. [10] J.H. Goo, M.F. Irfan, S.D. Kim, S.C. Hong, Chemosphere 67 (4) (2007) 718. [11] H. Bai, Ind. Eng. Chem. Res. 33 (1994) 1231. [12] K.P. Resnik, J.T. Yeh, H.W. Pennline, Int. J. Environ. Technol. Manage 4 (2004) 89. [13] A. Jaworek, A. Krupa, T. Czech, J. Electrostat. 65 (2007) 133. [14] J.H. Harker, P.M. Pimparkar, J. Inst. Energy 61 (8) (1988) 134. [15] K.J. McLean, Inst. Electr. Eng. Rev. 135 (6) (1988) 347. [16] G.S.P. Castle, IEEE Trans. Ind. App. 16 (2) (1980) 297. [17] J. Dalmon, D. Tidy, Atmos. Environ. 6 (1972) 721. [18] W.A. Baxter, J. Air Pollut. Control Assoc. 18 (12) (1968) 817. [19] J.T. Reese, J. Greco, J. Air Pollut. Control Ass. 18 (8) (1968) 523. [20] R.R. Crynack, in: Proceedings of the 6th International Conference on Electrostatic Precipitation, Budapest, (1996), p. 394. [21] J.S. Chang, H. Thompson, P.C. Looy, A.A. Berezin, A. Zukeran, T. Ito, S. Jayaram, J.D. Cross, in: Proceedings of the 6th International Conference on Electrostatic Precipitation, Budapest, (1996), p. 2. [22] E.B. Dismukes, J. Air Pollut. Control Ass. 25 (2) (1975) 152. [23] R. Salib, R. Keeth, Presented at the 2003 Mega Symposium, 2003. [24] H.W. Spencer, J. Peters, J. Fisher, Presented at the 2001 Mega Symposium, 2001.

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ion and CFD Modelling of Ammonia and Urea Production

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