Process Engineering & Analysis 212

Project 2 Report

We hereby declare that the report submitted are entirely our own work and have

not been copied from any other student or past year reports.

Group Members Miri ID Perth ID Signature

Chan Wai Mun 7E2A9716 16012114

Foong Siang Ting 7E1A8282 15412991

Thien Hau Ming 7E1A8322 15407308

Yong Wan Wei 7E2A9767 16311109

PROGRAM: Bachelor of Engineering (Chemical Engineering)

GROUP: 2

DATE AND TIME DUE: 4:00pm, Friday, 8th November 2013

DATE SUBMITTED: 8th November 2013

Executive Summary This project is conducted to study the development and manufacturing process of

ammonia at 1,000 ton/day by using the Aspen HYSYS software. A process flow diagram (PFD) of the production of ammonia is produced in order to run the simulation. The recycle loops in the PFDis analysed and the minimum numbers of tear streams needed to tear the flow sheet as well as the tear options are determined. Apart from that, a suitable fluid package is chosen based on the thermodynamic properties of the chemical components. Choosing the right fluid package for the simulation is vital as it will affect the accuracy of the results. For this project, the Soave-Redlich-Kwong (SRK) equation of state is chosen as the property package because SRK able to meet the technical constraint where mass fraction of ammonia in product must be more than 98 %. On the other hand, case studies and spreadsheet are used to solve for the optimization problems. The optimal number of tubes in the reactor is determined in order to maximize the profit. In addition, calculation is performed by case studies to calculate for the optimal number of tubes in the reactor when the purged amount is reduced by 20%. A discussion on the simulation results is also outlined in this report. For example, the technical problems encountered during the simulation, modeling decisions, checking of the simulation, observations on the results and the differences between simulation and reality. Moreover, several recommendations are proposed to improve the accuracy of the simulation and the fidelity of the work.

1.0 ObjectivesThis project studies about the manufacturing process in a plant for the production of

ammonia by using Aspen HYSYS. The major objective of this project is to maximize the profit of the manufacturing ammonia which able to produce a total amount of 1000 ton/day by Case Studies approach in HYSYS simulation. Case Studies can be performed to find the maximum profit by varying the number of tubes in certain reactor and flow ratio in Tee 100 and Tee 101. At the same time, technical constraints such as the mass faction of NH3 in product stream must be more than 0.98 have to be taken into consideration.

Besides that, the minor objective of this project is to study the development of process flow diagram in HYSYS simulation. For instance, a process flow diagram which represents the ammonia plant has been drawn in this project. This project also gives a better understanding of various fluid packages such as Peng Robinson and SRK which are used to determine the thermodynamic properties of components required for this ammonia plant. This project also provides appropriate skills of selecting fluid packages in order to obtain a high reliability of simulation.

1.1 BackgroundAmmonia in an important industrial chemical and is used as the raw material in

the synthesis of fertilizers, cleaning fluids and explosives. It is manufactured from the reaction between hydrogen and nitrogen which is also known as the Haber Process (Ammonia 2013).

The manufacturing process of ammonia is simulated by Aspen HYSYS, which it is a powerful simulation engineering tool created with respect to the engineering capabilities and interactive operation. Selecting a suitable fluid package for the simulation is important to ensure that the results are accurate. The fluid package is used to calculate the thermodynamic properties of the components and mixtures in the simulation such as enthalpy, density, entropy, vapour-liquid equilibrium and others (Hamid 2013). There is a variety of fluid package available in the software, however, the Peng-Robinson and SRK (Soave-Redlich-Kwong) equation of state are recommended in this project. The Peng-Robinson Equation of State is ideal for VLE calculations as well as calculating liquid densities for hydrocarbon systems. Besides, it is the most enhanced model in HYSYS and supports the widest range of operating conditions (Hamid 2013). On the other hand, SRK provides comparable results to Peng-Robinson, but its range of application is significantly more limited and not as reliable for non-ideal systems (HYSYS: Simulation Basis 2005). Both the packages are analysed in the simulation to determine which is the most suitable.

2.0 Assumptions and MethodologyTable 1: General Assumptions

Number Assumption Description1 The process flows under steady

stateIn steady state, the molar flow rates of materials enter the flow system is equals to molar flow rates of materials exits the system.

2 Both of the Plug Flow Reactors is adiabatic

There is no heat loss or supplied to both of the plug flow reactors in the simulation.

3 Materials only exit the system through Purge stream

There are no materials lost in other part of the PFD other than purge stream. This is non-achievable in real industrial situation.

4 Constant materials pressure and temperature

Assume pressure and temperature is exactly the same value as given in project brief. This also means that the surrounding factor like temperature is constant throughout the year.

5 The valve and separator are ideal

There is no pressure drop in valve and separator.

Table 2: Methodology

Number Methodology Description1 Simulation Materials balance and tear streams run by HYSYS

simulation automatically after input of streams and components, fluid package, reactions set, reactants and product, etc.

2 Spreadsheet Spreadsheet is used to define new variable which involving the setting of function to relate the imported variable to the new variables.

3 Case Studies By defining independent variables and dependent variables to observe the changes caused by the independent variables. The range and step size of the independent variable is defined by users

4 Critical Analyzing technique

Involve understanding to the process flow diagram in order to establish modification or improvement to achieve requirement and constraints set

3.0 Results

3.1 Question 1

Figure 1: Recycle Loops

Recycle loop is a closed loop of streams that all flow in the same direction. Each recycle loop should have one tear stream. The tear stream can be any of the streams forming the recycle loop. Based on the process flow diagram (PFD) for ammonia plant as shown in the figure above, the process contains 2 recycle loops. Recycle Loop 1 is shown by the orange coloured line and Recycle Loop 2 is shown by the green coloured line. The difference between these two loops started at the exit stream of TEE-100.

The minimum number of tear stream needed to tear the entire flowsheet is one tear stream only. The possible tear streams can be S1, S-7,S-8, S-9, Vap, S-10, or Recycle. Those streams are able to tear because all of them are the common streams for Recycle Loop 1 and Recycle Loop 2.

3.2Question 2a)

Figure 2: HYSYS PFD Printout

b)

Table 3: Input SummaryFLUID PACKAGE Basis-1Property Package Type SRKComponent List-1 Nitrogen

HydrogenAmmoniaArgon

Reaction Set Global Rxn Set Rxn-1Reactants Nitrogen, StoichCoef = -0.5

Hydrogen, StoichCoef = -1.5Ammonia, StoichCoef = 1

Basis Basis = Partial PresComponent = NitrogenPhase = Vapour PhaseBasis Units = atmRate Units = kg mole/m3-s

Kinetic Parameters FwdFreq Factor =10000Fwd Activation Energy = 91000

FLOWSHEET: Main

FLUID PACKAGE: Basis-1

Table 4: Flowsheet Base Case

Syngas (Material Stream) R* (Material Stream)Temperature=250℃Pressure=16211.9995kPaMolar Flow =100 kg mole/hCost Factor=0.0787365222Cost Flow Basis = Mass Flow

Temperature = 285℃Pressure = 16211.9995kPaMolar Flow =354.482524 kg mole/h

Composition Basis (In Mole Fractions):Nitrogen =0.248Hydrogen =0.744Ammonia = 0Argon=0.008

Composition Basis (In Mole Fractions):Nitrogen = 0.234089082Hydrogen = 0.705290064Ammonia = 0.0188098153Argon = 0.0418110385

S-3 (Material Stream) S-9 (Material Stream)Temperature = 275 ℃ Temperature = -20 ℃Product (Material Stream) R (Material Stream)Cost Factor = 0.295261958 Temperature =285℃Cost Flow Basis = Mass Flow

UNIT OPERATIONMix-100 (Mixer) Tee-100 (Tee)Feed Stream = SyngasFeed Stream = R*Product Stream = S1

Feed Stream = S1Product Stream = S-2Product-Stream = S-4

Heater-100 (Heater) Mix-101 (Mixer)Feed Stream = S-2Product Stream = S-3Energy Stream = H-DUTY1Pressure Drop = 0 kPa

Feed Stream = S-6Feed-Stream = S-5Product Stream = S-7

R-1 (Plug Flow Reactor ) VLV-100 (Valve)Feed Stream = S-3Product Stream = S-6Reaction Set = Global Rxn SetDelta P = 0 kPaTube Length = 1 mTube Diameter = 0.2 m

Feed Stream = S-4Product Stream = S-5Pressure Drop = 0 kPa

Mix-101 (Mixer)Feed Stream = S-6Feed Stream = S-5Product Stream = S-7

R-2 (Plug Flow Reactor)Feed Stream = S-7Product Stream = S-8Reaction Set= Global Rxn SetDelta P = 0 kPaTube Length = 1 m

Tube Diameter = 0.2 mSep (Separator) Cooler-1 (Cooler)Feed Stream = S-9Vapour Product = VapLiquid Product = Product

Feed Stream = S-8Product Stream =S-9Energy Stream = C-DUTYPressure Drop = 0 kPa

Recycle (Recycle)Inlet Stream = ROutlet Stream = R*Vapour Fraction Sensitivity = 0.01Temperature Sensitivity = 0.01Pressure Sensitivity =0.01Flow Sensitivity = 0.01Enthalpy Sensitivity = 0.01Composition Sensitivity = 0.01Entropy Sensitivity = 0.01

Tee-101 (Tee)Feed Stream = VapProduct Stream = S-10Product Stream = PurgeHeater-101 (Heater)Feed Stream = S-10Product Stream = REnergy Stream = H-DUTY2

c) Stream Tables :

Figure 3: Material Stream, Energy Stream and Composition Information

d) The desired production of ammonia, NH3 is 1,000 ton/day, however, the desired production is unable to achieve with 1 tube in each reactor. This is because the conversion of reactants to product is just 12.24%when 1 tube is used. Therefore, it is not sufficient to perform the production of ammonia to reach the targeted production of 1,000 ton/day. Hence, the number of tubes required in R-2 to reach the desired mass flow rate of ammonia will be explained in Question 3 (Step 2).

3.3 Question 3The approaches used for Question 3 are as below:

1. Use the process flow diagram produced in Question 2 using the information given in the project briefing. Then, click inside the Syngas and Product stream and select Cost Parameters, key in$300/ton for product stream and $80/ton for the syngas stream.

2. The desired product is 1000 ton/day. The maximum product mass flow rates in Question 2 is 17.15 ton/day when the molar flow rates of syngas is 100 kgmol/hr (Assume value), which in turns give a percentage conversion of 12.24%. Therefore, an adjust stream is needed to achieve the target ammonia production rate of 1000ton/day. Set the target variable as Product: Mass Flow Rates to 1000 ton/day by adjusting the variable Syngas: Molar Flow rate. After the adjusting, it can be seen that the maximum production rate(during maximum number of tube in R-2) is 1000 ton/day and the Syngas Molar Flow Rate is 6035 kgmol/hr, which gives a conversion percentage of 18.66%.

3. After we obtain the syngas flow rates to obtain 1000 ton/day of ammonia production, delete the adjust stream and adjust the number of tube back to 1. When the number of tube changed to 1, it can be observed that the Product Mass Flow Rates will be equals to 0 because the conversion is too small (The reason is explained in Question 2(d)).

4. Insert a Spreadsheet. Inside the Spreadsheet Connections import the following variables: (1) Syngas- Cost flow, (2) Product – Cost flow, (3) PFR-101 – Reactor Volume. After that, press Spreadsheet tab (where users can set their own variable using various function). The following variables are created:

A2 : Product cost flow, $ (imported)A3 : Syngas cost flow, $ (imported)A4 : PFR-101 Reactor Volume, m3 (imported)B2 : Number of tube = A4/B2B2 : Volume of one tube = (0.2m/2)^2*1m = 3.142e-2C2 : Cost of one tube per year = $100000C3 : Operating hours (hours/year)C4 : Cost of tubes ($/hr) = B3*C2/C3D2 : Overall Profit ($/hr) = A2-A3-C4

The spreadsheet is named as SPRTSHT-1. All variables above are shown in Figure 4.

Figure 4: Spreadsheet variable

5. Select DataBook, insert the following variables:

PFR-101 - Reactor Volume (m3) SPRDSHT-1 A2: Cost FlowProduct Mass Flow [tonne/day] SPRDSHT-1 A3: Product

Cost Flow SPRDSHT-1 A2: Syngas Cost Flow SPRDSHT-1 B3: Number of tubes SPRDSHT-1 C4: Cost of tubes ($/hr) SPRDSHT-1 D2: Overall Profit ($/hr)

6. Press Case Studies, click add to add a new case studies and select Reactor Volume as the independent variable and set other variables as dependant variable. After that, click into the case studies to set the value of low bound = 3.14159e-2, high bound = 1.570795, step size = 3.14159e-2. Next click Start, click Results and then view the result in the form of Transpose Table. The table is then extracted out to Excel by clicking Copy with labels and then insert to the report. Only a part of the table (State 18-21) is shown in this report in Table 4 as the original table is too long.

7. From Table 5, a maximum profit is found when number of tubes = 22, reactor volume = 0.6911498 m3which is $ 7833 per hour. Therefore the answer to Question 3 is n2 = 22.

8. Furthermore, a graph is plotted using the data obtained from the case studies to observe the pattern Overall Profit, Syngas and Product cost flow and cost of tubes against number of tubes. The graph is shown in Figure 5.

Table 5: Case Studies Transpose Table

State

PFR-101 - Reactor

Volume [m3]D1: Profit

($/hr)

B2: Number of

tubeA1: Cost

Flow(Products)A3: Cost

Flow(Syngas)

State 21 0.6597339 7548.587793 21 11938.73562 4124.99631

State 22 0.6911498 7833.865189 22 12236.63928 4124.99631

State 23 0.7225657 7821.071961 23 12236.47231 4124.99631

0 5 10 15 20 25 30 35 40

-6000-4000-2000

02000400060008000

10000

Graph of Profit against Number of tubes

Net Profit ($/hr)

Number of tubes

Cost

($/h

r)

Figure 5: Graph of Profit and costing against number of tubes

3.4 Question 4Approaches to solve question 4:

1. Use the Process Flow Diagram (PFD) in question 2 and modified it by adding an extra Tee component named “TEE-102” at the purge streamand name the top stream as “Purge out” and bottom stream as “Purge back” as shown in Diagram 2.

2. Double click the New Tee then click Parameters and set the flow ratio of 0.8 for Purge out and 0.2 for Purge back. This is because the question stated that the purge amount is to be reduced by 20%. In other words, 80% of the purge amount is needed to be removed and the 20% is flowing back to the PFD.

3. Next, add an extra mixer component named “MIX-102” with the inlet streams are Purge back and S-10*. The output stream will be S-10.

4. Use back the same spreadsheet in solution 3.

5. Select DataBook, insert the following variables:

TEE-100 – Flow Ratio (Flow Ratio_1) TEE-101 – Flow Ratio (Flow Ratio_1)

6. Press Case Studies, click add to add a new case studies and select Reactor Volume and both of the Flow Ratio (Flow Ratio_1) as independent variables and set other variables as dependant variables. Click Case Studies to set the value of low bound = 3.14159e-2, high bound = 1.570795, step size = 6.38218e-2 for Reactor Volume. For TEE-100 Flow Ratio (Flow Ratio_1) set low bound = 0.1, high bound = 0.1, step size = 0.1 and for Tee-101 Flow Ratio (Flow Ratio_1) set low bound = 0.01, high bound = 0.1, step size = 0.01. Next click Start, click Results and then view the result in the form of Transpose Table. The table is then extracted out to Excel by clicking Copy with labels and then paste to excel file and a graph is plotted (please refer to excel file Question 4).

7. Create nine case studies. Each case study with increasing TEE-100 Flow Ratio (Flow Ratio_1) from 0.1 to 0.9 and repeat step 6 to collect all the data.

8. Based on Table 5, the maximum profit is found when number of tubes = 38, reactor volume = 1.1938042 m3, TEE-100 Flow Ratio (Flow Ratio_1) = 0.2, and TEE-101 Flow Ratio (Flow Ratio_1) = 0.02. Therefore the optimal n2 = 38.

9. Furthermore, a graph is plotted using the data obtained from the case studies to observe the pattern Profit against number of tubes as shown in Figure 6.

Figure 6: Hysys PFD Printout 2

Table 6: Case Studies Transpose Table

StateTEE-101 - Flow

Ratio (Flow Ratio_1)

PFR-101 - Reactor Volume

[m3]

C3: Operating cost ($/hr)

D1: Profit ($/hr)

B2: Number of tube

State 87 2.00E-02 1.1623883 467.1717172 12905.12862 37State 88 2.00E-02 1.1938042 479.7979798 13106.42311 38State 89 2.00E-02 1.2252201 492.4242424 9344.635986 39

Figure 7: Graph of Profit against Number of Tubes

3.5 Question 5(a) Technical Problems Encountered

No. Problems Solutions1 The molar flow rates in the

simulation do not converge and appeared to be negative values.

Perform thorough checking on the input values of the properties of the components and ensure that the stream turns dark blue (ready) before proceeding to the next component.

Create a new case and draw the PFD again.

2 The desired production of ammonia at 1,000 ton/d is not achieved.

Change the number of tubes in the second PFR manually to 100 tubes.

Adding an Adjust block to the simulation plant by setting the Syngas Molar Flow as the adjusted variable and Product Mass Flow as the target variable.

3 The number of tubes in the reactor is not affecting the mass flow of the product stream.

Initially, the stoichiometry of the chemical components in the reaction set is entered in the form of whole numbers.

After changing the stoichiometry to the fraction form as given in the project description, the problem is solved.

4 The reactor volume is unable to be set as the

Delete the number of streams and enter value for volume of one tube manually into

Syngas (F)1270 ton/d

independent variable in the case studies.

PFR-101 rating so that reactor volume turns into blue colour and is able to be adjusted.

(b) Modelling Decisions

Fluid Package

The fluid packages suggested for this plant simulation are SRK and Peng-Robinson. Both fluid packages generates similar outcome in the process flow diagram, however, SRK is chosen as the fluid package in this project instead of Peng-Robinson. The main reason is SRK satisfies the technical constraints more accurately than Peng-Robinson. SRK produces more ammonia product than Peng-Robinson where SRK is 99.62% mass fraction whereas Peng-Robinson is 96.15% mass fraction. Hence, SRK is chosen as it has higher production efficiency and better product quality.

Solving for Optimization Problem

Case studies and spreadsheet function in HYSYS is chosen to solve for the optimal number of tubes needed in the PFR to maximize the profit. This is because spreadsheet allows user to create new variable which is not calculated in the PFD. For example, the volume of one tube in the reactor, the operating cost and the net profit gained. Case studies is then used to solve for the optimal number of tubes needed which gives the maximum profit. By using case studies, variables from the PFD and spreadsheet can be imported. After selecting the independent and dependent variables, HYSYS will perform the calculation automatically and the result can be analysed from the graph plotted or the transpose table generated by HYSYS. Thus, case studies and spreadsheet are chosen to ease the optimization process and save time.

(c) Checking of Simulation Results

Evidence 1

In order to check for the validity of the simulation results, material balance of the overall system is calculated. The inlet feed steam is syngas where the outlet streams consist of the product ammonia and purge.

Product (P) 1000 ton/d

Purge (W) 269.4 ton/d

Figure 8: Material Balance of the Overall System

F = P+W

LHS = 1270 ton/d

RHS = P+W = 1000 + 269.4 = 1269.4 ton/d

As shown above, it is proven that LHS=RHS. Thus, the simulation result is proven to be correct.

Evidence 2

The base component in this simulation is nitrogen, therefore, the conversion of the nitrogen in the second plug flow reactor is manually calculated to compare with the simulation results in HYSYS. The boundary for the calculation of material balance is set at R2.

Stream S7 (27380kgmol/h) Stream S8 (24960 kg mol/h)

Comp. MolFrac.

Molar Flow

N2 0.2368 6483.58H2 0.7127 19513.73

Figure 9:Material balance at R-2

Conversionof N2=6483.58−5274.05

6483.58×100 %=18.655 %

Based on the manual calculation of the conversion of N2 as shown above, 18.655% of N2 is converted. From the HYSYS simulation, the percentage of N2

conversion is 18.66%. The error between the simulation and the manual calculation is 0.027%, which is significantly small and negligible. Thus, it is proven that the simulation result is valid.

Comp. MolFrac.

Molar Flow

N2 0.2113 5274.05H2 0.6363 15882.05

(d) Observation on Simulation

Observation 1

More than 98% of ammonia product is produced in the form of liquid whereas a trace amount of ammonia is separated into the vapour stream in the separator unit. Both the streams have very low temperature which is -20°C.

Observation 2

The C-Duty2 in Cooler-2 requires an energy flow of 4.091E8 kJ/h to cool stream 8 from 437.6°C to -20°C in stream 9. A large amount of energy is needed to power the cooler for a large temperature drop. On the other hand, the H-Duty1 in Heater-1requires an energy flow of 1.945E8 kJ/h to heat stream 10 from -20°C to 285°C in stream R.

Observation 3

The process of production of ammonia involves exothermic reaction. By the observation in the PFD, stream 3 enters R-1 with a temperature of 275°C and the outlet of R-1, stream 6 has a temperature of 281.4°C. Besides, the temperature of the inlet stream of R-2 is 278.9°C while the temperature of the outlet stream is 437.6°C. This shows that both the reactors are operating in an exothermic condition as heat is released.

(e) Differences between Simulation and Reality

No. Simulation Reality1 The process is assumed to be in

an ideal condition where there is no heat loss from all the object units and pipelines.

In the real situation, there will be some heat loss to the surroundings from the tanks and pipelines during the reaction process and heating.

Hence, the temperature of the outlet stream will be affected and causes alteration of the thermodynamic properties of the stream.

2 The entire process of ammonia production is assumed to be at a steady state.

In practical situation, some of the reactions may become unsteady as time passes, which result in the difference of the flow rates, temperature and product yield from the simulation.

3The pressure drop is zero for some of the components in the simulation plant such as heater, cooler and mixer.

In reality, there is pressure drop in the components especially during heating and cooling as the sudden change of temperature will affect the pressure in the components.

The size and diameters of the pipelines in the real plant are not consistent and thus causes pressure drop.

4 The results of the simulation such as the properties of the components and streams calculated by the chosen fluid package are accurate.

The results obtained from the simulation are approximated values and may be differ from the real situation.

The errors might accumulate and contribute to the inaccuracy of the process as well as the decrease in the product yield.

5 The plug flow reactors are ideal with 100% efficiency in which the chemical components are mixed in a radial direction and the flow is constant.

In real practice, there will be a minimal longitudinal dispersion of the mixture in the plug flow reactor which will affect the flow in the reactor (Sperling 2007).

A small amount of mixture might accumulate in the reactor and thus affect the reaction and the flow rate of the reactor.

6 The plant cost comprises of the cost of feed (syngas), reactor tube cost and operating cost.

In reality, there are a lot more costing aspects which are required to be included in the estimation of the capital cost. For example, the labour cost, maintenance cost, insurance, fuel cost, utility cost and others.

4.0 Conclusions

In conclusion, all the problems are solved and stated the solutions by usingAspen HYSYS.This simulation is ableto predict the properties of mixtures from simple hydrocarbon systems to complex mixtures with non-ideal chemical system. Besides, it is also able to perform optimization to maximize profit in production of a product. Choosing the best fluid package will able to give the ideal result to ensure accurate simulation with all the requirements are met such as product quality.

Fluid package of SRK is chosen instead of Peng – Robinson is because SRK is able to meet the technical constraint where the mass fraction of the ammonia product of the plant is more than 98% which is also means that the purity quality of the product is very good. On the other hand, using Peng – Robinson have lower percentage of the mass product compared to SRK which will reduce the quality of the product. Furthermore, conversion percentage is taken into consideration to determine the number of tube of a reactor to have maximum profit.

Using spreadsheet and case studies able to perform severalcalculations by selecting any variables that is needed to be found and maximised such as profit, costs flow, and operating cost with varying of number of tubes, flow ratios, and reactor volume.

In question 2, it is not suitable for number of tube for both reactors are in one. It is found out that the conversion of product is too low which is 12.24%. After using spreadsheet and perform calculation using case studies in question 3, it is found that the maximum number of tube for second plug flow reactor R-2 is 21 to have the maximum profit of $ 7874 per hour. In question 4, with adjustable value of flow ratio 1 and 2, it is found out that optimal number of tube in R-2 is 38 with flow ratio 1 is 0.2 and flow ratio 2 is 0.02 and the profit is $ 28701 per hour. It is very clear that this whole process plant is profitable and worth to invest as the profit is very high to cover up all the expenses that are needed to run this process.

Next, temperature rose across both of the reactorswhich show that the production of ammonia is an exothermic reaction and kinetic is a suitable reaction type based on the given parameters involving forward and reverse rate.

In reality, many conditions and results are different compared to using simulation in HYSYS. In simulation, it is assume that the pressure drop is zero and the whole process is under steady state whereas in reality, it is needed to taken into consideration as

many factors will affect the pressure drop to be changed and the process might not be in steady state anymore.

Lastly, Aspen HYSYS is a very useful software for chemical engineers to perform simulation and modeling to have a better understanding of how can it be applied to an exact plant in reality.

5.0 RecommendationsAlthough the simulation results have achieved all the requirements and fulfilled the technical constraints, there are still several differences between the real process plant and the simulation. To improve the accuracy of the simulation and to minimise any possible errors which might occur during the real practice, several recommendations are proposed as below:

i. Include the approximation for heat loss and pressure drop. In practice, there is heat loss and pressure drop in the vessels and object units such

as heater and cooler. If both the parameters are included in the calculation of the simulation, the results will be more accurate.

For heat loss, a set of calculation to approximate the heat loss can be developed. The approximate heat loss duty should be added to the energy duty in the simulation to be recalculated.

As for the pressure drop, the pressure across the vessels should be analysed at a specific temperature and be included in the simulation.

ii. Increase the sensitivity of the simulation. The results in the simulation are calculated by using numerical method. Hence,

the step size and tolerance can be altered to a smaller value rather than using the default value.

As the step sizes become smaller, the iteration errors will be stepped down and thus the solution will be more accurate.

iii. Apply pinch technology to the simulation plant. To further improve the efficiency and maximise the profit of the plant, pinch

technology can be applied. This is because pinch technology provides a systematic methodology for energy saving in chemical processes and total sites by using thermodynamics principles (March 1998).

Moreover, pinch technology is able to minimise the energy requirement by maximising the process-to-process heat recovery.

6.0 ReferencesAmmonia. 2013. Accessed November 2,

http://www.bbc.co.uk/schools/gcsebitesize/science/ocr_gateway/chemical_resources/ammoniarev1.shtml.

HYSYS: Simulation Basis. 2005. Aspentech. Accessed November 2,

http://www.ualberta.ca/CMENG/che312/F06ChE416/HysysDocs/AspenHYSYSSimulationBasis.pdf.

Hamid, Mohammad Kamaruddin Abdul. 2013. HYSYS: An Introduction to Chemical

Engineering Simulation. Johor, Malaysia: UTM Department of Chemical Engineering.

March, Linnhoff. 1998. Introduction to Pinch Technology. Accessed October 19,

http://www.ou.edu/class/che-design/a-design/Introduction%20to%20Pinch

%20Technology-LinhoffMarch.pdf.

Sperling, Marcos Von. 2007. Biological Wastewater Treatment: Volume 3.

London, UK: IWA Publishing. March, Linnhoff. 1998. Introduction to Pinch Technology. Accessed October 19,http://www.ou.edu/class/che-design/a-design/Introduction%20to%20Pinch%20Technology-LinhoffMarch.pdf.