Computer simulation of Dinitrotoluene Nitration Process

Master of Science in Engineering, Degree Programme in Chemical Engineering

Datasimulering av Dinitrotoluen Nitreringsprocess.

Moses Ruhweza

Faculty of Health, Science and Technology

Subject: Process Engineering

Points: 30 ECTS

Supervisors: Lars Nilsson and Lars Stenmark

Examiner: Lars Järnström

Date: 2018-01-19

II

Computer Simulation of Dinitrotoluene Nitration Process Moses Ruhweza Department of Engineering and Chemical Sciences Karlstad University

Abstract This paper presents an approach for modelling a commercial dinitrotoluene (DNT) production

process using the CHEMCAD simulation software. A validation of the model was performed based

on results of an experimental study carried out at Chematur Engineering AB, Sweden.

Important parameters such as fluid properties, temperature profile and other operating conditions for

CHEMCAD steady state model were selected so as to obtain the crude DNT yield as well as the acid

–and organic phase compositions within the same range as the reference values from the experimental

study. The results showed that the assumption of the steady state model was correct, and that acid –

and organic phase compositions were in good agreement, although with a slightly lower sulphuric acid

concentration than that observed in the experimental study.

Also, a detailed study was carried out to analyse the effects of physicochemical conditions on the

desired product yield. Both the results from the experimental study and the simulated model agree that

the effects of mixed acids or heats of mixing acids contribute significantly to the energy balance.

For the appropriateness of the thermodynamics, a NRTL model was chosen and the reactor system

was optimized by an equilibrium based approach, producing MNT in 99.8% yield and crude DNT in

99.9% yield. An 80.1/19.9 DNT isomer ratio of the main isomers was achieved and a reduction of by-

products in the crude DNT shows a good agreement between the model and the experimental study.

Keywords: Dinitrotoluene, CHEMCAD, thermodynamics, steady state model, MNT

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Datasimulering av Dinitrotoluen Nitreringsprocess.

Moses Ruhweza Department of Engineering and Chemical Sciences Karlstad University

Sammanfattning

I denna rapport presenteras en metod för att modellera en kommersiell nitreringsprocess för

tillverkning av dinitrotoluen (DNT) med simuleringsprogrammet CHEMCAD. En validering av

modellen gjordes baserat på resultat från en experimentell studie utförd hos Chimärer Engineering AB,

Sverige.

CHEMCAD-modellen utgår från ”steady-state” drift av anläggningen. Viktiga parametrar såsom

fluidegenskaper, temperaturprofil och andra driftsbetingelser i CHEMCAD-modellen valdes för att

erhålla ett utbyte av DNT samt sammansättningar av såväl syrafas som organisk fas i god

överensstämmelse med referensvärdena från den experimentella studien.

Resultaten visade att antagandena i modellen var korrekta och sammansättningarna för syrafasen och

den organiska fasen överensstämde med data från den experimentella studien.

Det genomfördes också en detaljerad studie för att analysera effekterna av fysikalisk-kemiska

betingelser på det önskade produktutbytet. Både resultaten från den experimentella studien och data

från anläggning i drift överensstämde med den simulerade modellen avseende utspädningsvärmens

bidrag till energibalansen.

För att erhålla en lämplig beskrivning av reaktionssystemets termodynamik valdes en NRTL-modell

och reaktorsystemet optimerades, vilket gav 99,8 % utbyte av MNT och 99,9 % DNT utbyte. Ett

förhållande på 80,1 / 19,9 mellan de två huvudisomererna av DNT uppnåddes och en minskning av

biprodukter i DNT produktblandningen. Detta är två exempel på en bra överensstämmelse mellan

modellen och experimentstudien.

IV

Acknowledgements I would like to express my sincere gratitude to Chematur Engineering AB for providing me an

opportunity to do my Master’s Thesis at their company.

I sincerely thank my supervisor Lars Stenmark, Development Director at Chematur Engineering AB,

Sweden, for his constructive advice and supervision throughout this project.

I also wish to extend my thanks to Stefan Johansson, Technology Manager Nitroaromatics and

Margareta Dahl, Manager Process Design for their insightful comments and constructive suggestions

to improve the quality of this project work.

With full pleasure, I converge my heartiest thanks to the Process Department as well as all the

employees at Chematur Engineering AB for their invaluable advice and wholehearted cooperation

without which this project would not have seen the light of day.

Lastly, I would like to thank Professor Lars Nilsson for his exemplary guidance and monitoring

throughout this project.

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Table of Contents 1. INTRODUCTION .................................................................................................................... 1

1.1. BACKGROUND .................................................................................................................................. 1 1.2. PURPOSE ......................................................................................................................................... 2 1.3. LIMITATIONS .................................................................................................................................... 2 1.4. METHODOLOGY ............................................................................................................................... 2 1.5. ORGANIZATION OF THE REPORT .......................................................................................................... 3

2. NITRATION THEORY .............................................................................................................. 4

2.1. NITRATION ................................................................................................................................... 4 2.2. NITRATION OF TOLUENE .................................................................................................................... 4

2.2.1. Mononitration ..................................................................................................................... 4 2.2.2. Dinitration.............................................................................................................................. 6

2.3. IMPURITIES ................................................................................................................................... 8 2.4. EFFECTS OF PHYSICOCHEMICAL FACTORS ON NITRATION OF TOLUENE ........................................................ 9

2.4.1. Effect of temperature ................................................................................................................. 9 2.4.2. Effect of mixed acids ............................................................................................................... 10 2.4.3. Effect of Spent Acid ................................................................................................................ 10 2.4.4. Effect of nitro compounds solubility ............................................................................................. 11

3. PROCESS SIMULATION ........................................................................................................ 11

3.1. IMPORTANCE OF SIMULATION ........................................................................................................... 12 3.2. SELECTION OF A THERMODYNAMIC METHOD ....................................................................................... 13 3.3. ANALYSIS OF THE DNT NITRATION PROCESS ........................................................................................ 14

3.3.1. Pump ................................................................................................................................. 14 3.3.2. Separator ........................................................................................................................... 14 3.3.3. Heat Exchangers ................................................................................................................ 14 3.3.4. Reactors ............................................................................................................................. 14

3.4. THERMODYNAMIC MODELS .............................................................................................................. 15 3.4.1. Fugacity ............................................................................................................................. 15 3.4.2. Activity ............................................................................................................................... 16 3.4.3. Equilibrium ........................................................................................................................ 16

3.5. ENTHALPY CHANGES UPON MIXING .................................................................................................... 17 3.6. HEATS OF DILUTION OF MIXED ACIDS .................................................................................................. 20

3.6.1. Enthalpy concentration diagram ....................................................................................... 22 3.7. COMPONENT SPECIFICATION ............................................................................................................ 23 3.8. CREATING NEW COMPONENTS .......................................................................................................... 24

3.8.1. Defining a Hydrocarbon pseudo-component .................................................................... 25 3.8.2. Estimating by the UNIFAC method .................................................................................... 25 3.8.3. Estimating by the Joback method ..................................................................................... 25

3.9. VALIDATING THE COMPONENT ESTIMATION METHOD(S) ........................................................................ 26 3.9.1. Molecular descriptors ........................................................................................................ 28

3.10. PROCESS FLOWSHEET MODELLING ..................................................................................................... 33 3.11. MODELLING PROCESS EQUIPMENT ..................................................................................................... 33

VI

3.11.1. Feed streams ..................................................................................................................... 33 3.11.2. Pumps ................................................................................................................................ 33 3.11.3. Centrifugal Pump-Solution Principal ................................................................................. 33 3.11.4. Reactors ............................................................................................................................. 38 3.11.5. Heat Exchangers ................................................................................................................ 44 3.11.6. Separators ......................................................................................................................... 48

4. RESULTS ............................................................................................................................. 49

4.1. SPENT ACID FROM NITRATION ........................................................................................................... 49 4.2. THE MNT CONTENT ....................................................................................................................... 51 4.3. ACID TO MONONITRATION STAGE ..................................................................................................... 52 4.4. CRUDE DNT .................................................................................................................................. 53 4.5. ENERGY BALANCE ........................................................................................................................... 55 4.6. MASS BALANCE .............................................................................................................................. 56 4.7. HEAT OF DILUTION .......................................................................................................................... 57 4.8. CRITICAL PROPERTIES OF THE NEW COMPONENTS CREATED. ................................................................... 61

5. DISCUSSION ....................................................................................................................... 63

6. CONCLUSION ...................................................................................................................... 65

7. REFERENCES ....................................................................................................................... 66

8. APPENDICES ....................................................................................................................... 70

8.1. APPENDIX A................................................................................................................................... 70 8.2. APPENDIX B ................................................................................................................................... 74 8.3. APPENDIX C ................................................................................................................................... 76 8.4. APPENDIX D .................................................................................................................................. 79

VII

List of Figures

FIGURE 1: THREE ISOMERS FORMED BY NITRATION OF TOLUENE. PERCENTAGES ARE EXAMPLES OF VALUES TYPICAL

FOR ISOTHERMAL CONDITIONS. ............................................................................................................................. 4

FIGURE 2:FORMATION OF NITRONIUM ION (THE POWERFUL ELEECTROPHILE). .............................................................. 5

FIGURE 3: MECHANISM OF THE ELECTROPHILIC ATTACK ON THE AROMATIC SYSTEM .................................................... 6

FIGURE 4: THE SIX ISOMERS OF DNT (8). ....................................................................................................................... 7

FIGURE 5: THIS FIGURE SHOWS THE OXIDATION BY-PRODUCTS FORMED DURING THE DNT NITRATION PROCESS (6). ... 9

FIGURE 6: A PROCESS SYNTHESIS PROBLEM (14,15) . ..................................................................................................... 13

FIGURE 7: THE FIGURE SHOWS THE PROCESS FLOWSHEET FOR THE DNT NITRATION PROCESS. ................................... 14

FIGURE 8: THIS FIGURE SHOWS A SET-UP OF MIXING TWO LIQUIDS. .............................................................................. 17

FIGURE 9: WATER MOLECULES SURROUNDING A SULFATE ION. .................................................................................... 18

FIGURE 10: THE GRAPH OF THE ELECTRIC POTENTIAL FOR CHARGE Q RELATIVE TO THE WATER MOLECULES AT R. .... 19

FIGURE 11: THE POTENTIAL ENERGY FOR A CHARGE Q AT DISTANCE R ........................................................................ 20

FIGURE 12: A SET-UP SHOWING MIXING OF TWO LIQUIDS. ............................................................................................ 21

FIGURE 13: THIS FIGURE SHOWS A DIALOG BOX FOR THE PROPERTY ESTIMATION OF NEW COMPONENTS. ................... 24

FIGURE 14: MOLECULAR STRUCTURE OF TOLUENE (42). ............................................................................................... 26

FIGURE 15: CHEMCAD UNITOPS THAT CALCULATE FLOW AS A FUNCTION OF PRESSURE. ........................................... 34

FIGURE 16: A SET-UP SHOWING THE EFFICIENCY OF A HEAT ENGINE. .......................................................................... 37

FIGURE 17: THE EQUILIBRIUM REACTOR IN CHEMCAD .............................................................................................. 41

VIII

List of tables

TABLE 1: ISOMER CONTENT OF DINITROTOLUENE .......................................................................................................... 6

TABLE 2: RELATIONSHIP BETWEEN THE COMPOSITION OF NITROTOLUENE INTERMEDIATES AND TEMPERATURE. ....... 10

TABLE 3: SOLUBILITY OF DNT IN SULPHURIC ACID. MODIFIED FROM (11). ................................................................... 11

TABLE 4: COMPONENTS DEFINED IN CHEMCAD TO REPRESENT DNT NITRATION PROCESS. ..................................... 23

TABLE 5: PROPERTIES OF THE THREE VERSIONS OF TOLUENE CREATED WITH DIFFERENT METHODS. .......................... 27

TABLE 6: THIS TABLE SHOWS THE NUMBER OF EACH MOLECULAR GROUP WHICH OCCUR WITHIN THE STRUCTURE BEING

ESTIMATED. ......................................................................................................................................................... 28

TABLE 7: THERMODYNAMIC MODELS SUITABLE FOR REGULAR SOLUTIONS. .................................................................. 31

TABLE 8: THIS TABLE SHOWS SUITABLE ENTHALPY MODELS FOR EQUILIBRIA-K VALUES. .............................................. 32

TABLE 9: EQUIPMENT SUMMARY TABLE FOR THE DNT NITRATION PROCESS ................................................................ 38

TABLE 10: REACTIONS USED TO REPRESENT THE DNT NITRATION PROCESS. ............................................................... 42

TABLE 11: EQUIPMENT SUMMARY TABLE OF THE EQUILIBRIUM REACTORS .................................................................... 44

TABLE 12: EQUIPMENT SUMMARY TABLE FOR HEAT EXCHANGER ................................................................................ 47

TABLE 13: EXPERIMENTAL RESULTS VERSUS SIMULATION PREDICTIONS FOR SPENT ACID. ............................................ 50

TABLE 14: THIS TABLE SHOWS THE COMPOSITION OF THE RECOVERED SULFURIC ACID. .............................................. 50

TABLE 15: THIS TABLE SHOWS THE RECOVERED DNT. ................................................................................................. 50

TABLE 16: THE COMPOSITION OF THE ACID PHASE IN THE ORGANIC PHASE AND MNT YIELD ...................................... 51

TABLE 17: THE COMPOSITION OF THE ORGANIC PHASE IN THE ACID PHASE. ................................................................. 52

TABLE 18: THIS TABLE SHOWS THE COMPOSITION OF THE RECOVERED NITRIC/SULPHURIC MIXTURE ........................... 53

TABLE 19: A COMPARISON OF THE COMPOSITION OF CRUDE DNT WITH THE RESULTS OBTAINED FROM THE SIMULATED

MODEL AND AVAILABLE INDUSTRIAL DATA (IN PARENTHESIS) OR EXPERIMENTAL DATA. .................................... 54

TABLE 20: THE OVERALL ENERGY BALANCE OF THE DNT NITRATION PROCESS. .......................................................... 55

TABLE 21: THIS TABLE SHOWS THE OVERALL MASS BALANCE OF THE DNT NITRATION PROCESS. ................................. 56

TABLE 22: SULPHURIC ACID MIXED WITH WATER. .......................................................................................................... 57

TABLE 23: SULPHURIC ACID MIXED WITH 50 WT.-% SULPHURIC ACID............................................................................. 58

TABLE 24: NITRIC ACID MIXED WITH WATER. ................................................................................................................ 59

TABLE 25: NITRIC ACID MIXED WITH 20 WT.-% NITRIC ACID ......................................................................................... 60

TABLE 26: THIS TABLE SHOWS A COMPARISON OF THE CRITICAL PROPERTIES OF THE NEW COMPONENTS WITH VALUES

(SEE APPENDIX C). .............................................................................................................................................. 61

1

1. Introduction This master’s thesis concerns the development of a simulation model and optimization technology for

industrial DNT nitration process. All of the simulation/analysis was done using CHEMCAD, version

7.1. I chose CHEMCAD because it enables one to quickly build fundamental steady-state models of

chemical process. The work was done at Chematur Engineering AB.

1.1. Background Computer simulation of dinitrotoluene (DNT) production facility is the main subject of this master’s

thesis. A study regarding the use of CHEMCAD for designing and analysing process equipment and

benefits of process simulation, is also a focus in this thesis.

Nitration of aromatic hydrocarbons such us benzene and toluene has been extensively studied, mainly

due to its industrial importance in the manufacturing of organic synthetic compounds, and its role in

the development of our present understanding of organic reactions, particularly electrophilic

substitution (1–3).

Commercially, the nitration of toluene is mostly performed to produce toluene diisocyanate (TDI) via

DNT and toluenediamine (TDA).

In a DNT production facility, nitration of toluene is performed in two stages with the production of

nitrotoluene intermediates in the first stage which is known as mononitration and the production of

DNT in the second stage, also known as dinitration.

With a sharp rise in market demand for chemicals such as TDI, many companies have implemented

process simulation technology in order to maximize production capacity, improve safety and

environmental management among others (4).

An example of a company that can provide such an excellent process technology service to their

customers is Chematur Engineering AB (CEAB).

Chematur engineering AB has its headquarters in Karlskoga, Sweden, where it was founded by Alfred

Nobel in the late 19th century. The company has an extensive experience (tracing back to the days of

Alfred Nobel and his achievements) in modelling and simulation of chemical plants. This in turn has

made CEAB the global provider of excellent technology and therefore a forerunner in providing

engineering expertise.

In a recent work, CEAB did a research and developed their existing technology of producing toluene

diisocyanate (TDI) by optimizing their proprietary pump nitration process for continuous production

of Dinitrotoluene (DNT).

2

The DNT production was done in pilot scale experiments using a bench scale pump nitration unit

installed at their Technology Centre.

This master thesis presents a computer simulation model of CEABs pump nitration process for

continuous production of DNT.

1.2. Purpose

The aim of this master’s thesis: The purpose of this master’s thesis was to build a simulation model for the production of DNT using

CHEMCAD. A steady-state model is used as a basis for the simulation, and it is desired to see how

well this model predicts the process characteristics (e.g. flowrates, compositions, nitration temperature,

properties, equipment sizes, etc.) of the DNT nitration process compared to an experimental study.

1.3. Limitations

Although the master’s thesis has reached its aims and was completed within the limits of the

assignment’s due date, there were some unavoidable limitations. The vast majority of the literature was

over 50 years old and some related secondary sources cited in those literature were difficult to locate

and retrieve. As a result, those secondary sources couldn’t be entered in the reference list, but they are

all cited in the body of the paper. Also, during the assembly of the model it became apparent that some

process units could not be directly modelled. For instance, the use of an output stream that goes

directly to the recycled stream in the process could not be done since CHEMCAD does not allow

multiple streams to be sent directly into other process units. To solve this situation a stream divider

was added to the model so the separation unit sent its output to the stream splitter, which was then

the input for the decanter.

1.4. Methodology Several methods to build a simulation model for the production of DNT (for determining the

solvability of the process system) were considered: Hand calculations, spreadsheet and CHEMCAD.

Hand calculations were only used to solve easy problems and the method was not used for complex

problems due to the number of calculations required and the need to re-work the entire process if

design conditions were changed.

The advantage of using a spreadsheet is that it is fairly easy to update changes in it. However, it is time

consuming to set-up and it can be difficult to add or change some steps.

3

The designing of the simulation model was divided into smaller activities: obtaining information,

backbone assembly, workarounds, error checking and updates. The information gathered for use

included, among others, physical properties of chemicals, experimental records and process diagrams

(PFD and P&ID). Once the information was gathered, an agreement was reached on how to build the

model.

The backbone of the simulation model was reviewed by my supervisor and experienced process

engineers from CEAB’s process department

1.5. Organization of the report This report consists of six chapters which will cover the designing of a simulation model for the DNT

nitration process. Here is an overview of each presented chapter:

Chapter One: presents the introduction of the thesis. This chapter also discusses the purpose

of the study, the methodology of the study and its limitations.

Chapter Two: covers the scientific literature review and relevant information used to

accomplish the project work.

Chapter Three: this chapter explains the details of the simulation development and selected

methodology used for the process.

Chapter Four: presents the results predicted by CHEMCAD

Chapter Five: presents a discussion of the process simulation

Chapter Six: discusses the conclusion and future work to improve this study.

4

2. Nitration Theory

2.1. Nitration Nitration has a long history of industrial application and an extensive research on its mechanisms (5) .

Today, nitration is the main reaction used to synthesize one of the most important and largest groups

of industrial chemicals, namely aromatic nitro compounds.

A typical industrial nitration is mainly carried out by a mixed-acid reaction of concentrated sulfuric

acid and nitric acid (6). The reaction generates nitronium ions (NO2+) which are added onto aromatic

substrates via electrophilic substitution. In this way, benzene, toluene and phenol are converted into

the simplest of all aromatic nitro compounds, namely, nitrobenzene, nitrotoluenes, and nitrophenols

(3,5,7).

2.2. Nitration of Toluene

2.2.1. Mononitration Toluene undergoes nitration on reaction with a mixture of concentrated sulfuric acid and concentrated

nitric acid. In this way, three different isomers of mononitrotoluene (MNT) are formed (8). See Figure

1 for details.

Figure 1: Three isomers formed by nitration of toluene. Percentages are examples of values typical for isothermal conditions.

5

2.2.1.1. Generation of the electrophile To initiate this reaction, we need to form a powerful electrophile, namely the nitronium ion (NO2

+).

𝐻𝑁𝑂3 + 2𝐻2𝑆𝑂4 ⇋ 𝑁𝑂2+ + 2𝐻𝑆𝑂4

− + 𝐻3𝑂+

The first step of this reaction is protonation of the OH-group and the reason is to make it a good

leaving group so that we can generate a powerful electrophile see Figure 2. After protonation, the

negative oxygen forms a double bond and expels water (second step), giving a powerful electrophile,

which is, as said before, the nitronium ion (3,5,8) . The sulphuric acid acts as a catalyst in this reaction.

Figure 2:Formation of nitronium ion (the powerful eleectrophile).

2.2.1.2. Electrophilic Attack on Aromatic System The third step (Figure 3) is that the nitronium ion attacks the aromatic ring of toluene, giving an

unstable intermediate (arenium ion). The nitro (-NO2) group can now be added on the ortho position.

It should be noted that when toluene undergoes electrophilic substitution, most of the substitution

takes place at its ortho and para positions, because the methyl group on toluene is an ortho-para

director (3).

The last step (re-aromatization) is to remove the hydrogen atom and this is done by using hydrogen

sulphate (HSO4- ) or excess water in the mixture. The hydrogen sulphate grabs the hydrogen and

reforms a double bond, giving ortho-nitrotoluene. All the three isomers are formed but the nitration

proceeds with predominant formation of the ortho isomer, but the para and meta product is formed

as well (3,8).

6

Figure 3: Mechanism of the electrophilic attack on the aromatic system

2.2.2. Dinitration The second nitration step, dinitration, takes place in the same way as mononitration but it’s more

difficult to achieve because of steric hindrance and deactivation of the aromatic ring by the nitro group.

As a result, a higher temperature and a higher sulfuric acid concentration is required (8).Several isomers

are formed of which 2,4- and 2,6-DNT are the most important, see Figure 4 and Table 1.

Table 1: Isomer content of dinitrotoluene

Isomers Organic product

(Wt.-%)

2,4-DNT 76.1

2,6-DNT 19.8

3,4-DNT 2.25

2,3-DNT 1.23

2,5-DNT 0.54

3,5-DNT 0.08

7

Figure 4: The six isomers of DNT (8).

8

2.3. Impurities

In the industrial production of DNT, impurities are formed and the formation rates of these impurities

are significantly affected by the initial reaction conditions, including nitration temperature and-, initial

sulfuric and nitric acid concentration in the mixed acid (5,8).

The presence of the methyl group in toluene makes it easier to be oxidized to nitrocresols. According

to (9), nitration of toluene to MNT generates on average about 0.7 wt% nitrocresols, which are mainly

dinitro-para and ortho-cresol (80% 2,6-dinitro-p-cresol). Benzoic acid products, nitrogen dioxide

(NO2) and, carbondioxide (CO2) are also formed due to the oxidative power of the acid (9,10).

Oxidative degradation of nitrocresols leads to the formation of nitrous acid, mainly during dinitration.

9

Figure 5: This figure shows the oxidation by-products formed during the DNT nitration process (6).

It is important to minimize the formation of by-products during nitration of toluene as this causes a

reduction in yield (6).

2.4. Effects of physicochemical factors on nitration of toluene

2.4.1. Effect of temperature The nitration temperature is a crucial parameter as it influences the yield of the mononitro isomers.

The nitration temperature also influences the reaction rate but at a considerably lower degree (8).

10

Pictet’s study, as cited in (11), showed that when nitrating toluene with a mixture of nitric and sulfuric

acids at lower temperatures, relatively more para-nitrotoluene could be obtained than at higher

temperatures. A similar study by Orlova, also as cited in (11), concluded that a lower nitration

temperature causes an increase of the para-nitrotoluene content while the meta-nitrotoluene and the

ortho-nitrotoluene content decreases Table 2.

Table 2: Relationship between the composition of nitrotoluene intermediates and temperature.

Temperature

(°𝑪)

Composition of the product

Ortho-isomer Para-isomer Meta-isomer

30 56,9 39,9 3,2

60 57,5 38,5 4,0

For safety reasons and for the purity of the product, it is of great importance to keep the nitration

temperature as low as possible and constant. Using too high temperature causes the reaction to proceed

violently and by-products, especially oxidation products, are easily formed (11). Therefore, the nitration

temperature should not exceed 40 ℃ during mononitration and 70 ℃ during dinitration, since above

this “safety” limit both the methyl group and the aromatic nucleus are attacked oxidatively, leading to

an increased formation of by-products, including nitrocresols and nitrophenols (11) .

2.4.2. Effect of mixed acids The composition of the mixed acid depends on the compound being nitrated and the number of nitro

groups to be introduced. For instance, if more nitro groups are to be added (e.g., during dinitration),

then the acid concentration should be higher.

The ratio of the nitric acid, sulfuric acid and water should be chosen wisely. Otherwise nitration of

toluene might be incomplete. Since water is formed during nitration and it dilutes the mixed acid, the

amount of sulfuric acid must be chosen in such a way that it binds up all the water formed (11).

It is preferable to use a very slight excess of nitric acid (e.g., 1-2% in both nitration stages), to avoid

oxidation processes (11).

Higher concentration of sulfuric acid increases the rate of the reaction by increasing the concentration

of the electrophile, nitronium ion (3).

2.4.3. Effect of Spent Acid The acid leaving the dinitration stage is re-used for the nitration of toluene to mononitrotluene. This

in turn affects the nitration reaction and the formation of the nitrotoluene intermediates (11).

11

One method of adding the acid from dinitration to mononitration stage is by mixing the spent acid

with concentrated nitric acid and sulfuric acid.

A disadvantage of this method is an increment of temperature, mainly due to the heat of dilution of

the mixed acid (11).

2.4.4. Effect of nitro compounds solubility The solubility of nitro compounds is an important factor in the nitration process.

The more easily the organic phase dissolves in the acid phase, the higher the reaction rate, and the

degree of nitration that can be obtained in a given time.

For example, nitrobenzene and trinitrotoluene (TNT) dissolve easily in concentrated sulfuric acid.

However, TNT dissolves with difficulty in mixed acids but its solubility might be high when the

content of nitric acid falls to a few percent, as in the spent acid (11).

The solubility data for DNT in sulphuric acid of various concentrations are tabulated in Table 3.

Table 3: Solubility of DNT in sulphuric acid. Modified from (11).

Concentration

% H2SO4

Solubility of DNT in sulphuric acid

g DNT/ 100 g sulphuric acid

40°𝐶 50°𝐶 70°𝐶

80 - 2.5 3.8

83.6 3.6 4.7 6.3

88.7 10.0 12.8 -

90 - 16.8 20.0

3. Process simulation In this modern age of powerful computers, the role of process simulation in the chemical industry has

grown immensely, and with good reason.

Process simulation is a computer presentation of a real-world process plant or system by a

mathematical model which is then solved to obtain information about the performance of the process

(12).

12

3.1. Importance of simulation Process simulation allows engineers to model processes in extreme detail without having to spend the

time, manpower and money for physically testing the design in a real-world industrial environment.

For instance, consider being asked to design a distillation column to produce a mixture of benzene

and toluene into an overhead product containing 95% benzene and a bottom product containing 90%

toluene. This process can be designed by hand calculations (e.g., calculating the condenser and reboiler

duties, mass and energy balances and estimating tray efficiencies) or by physically building a pilot plant

of the process. However, when the design conditions are changed (e.g., 95% toluene and a feed rate

of 850kg/h instead of 750kg/h), it takes time and becomes costly to test the potential designs.

With the help of commercial process simulators (e.g., Aspen Plus, Aspen HYSYS and CHEMCAD)

however, a tremendous amount of time and money can be saved.

Therefore, in the ever more competitive world of processing and manufacturing, process engineering

services are no longer complete without the presence of process simulators (13).

Process simulators are extensively being used as powerful tools to increase, among others, the

production capacity, profits of a company, competitiveness and to reduce the build-up time for new

manufacturing process. It can also be used to reduce the capital equipment costs by optimizing the

process.

Chemical engineers use process simulation tools among others Aspen Plus and CHEMCAD to design

complex process plants such as large-scale process and manufacturing industries, where energy use is

measured in megawatts, costs and profits are measured in hundreds of millions of dollars and materials

measured in thousands of tons.

Another benefit of process simulation tools is that it allows chemical engineers to predict capital cost

expenditures, evaluate optimization options and determine the overall effects of potential process

changes in one area. Furthermore, chemical engineers rely on process simulation to answer what-if

questions asked by operational staff or management of the process plant. All in all, chemical engineers

use process simulation tools to accurately predict the outputs of the process when the process inputs

and outputs are given.

13

Figure 6: A process synthesis problem (14,15) .

3.2. Selection of a thermodynamic method Just like the foundation of a building, the methods used for estimating thermodynamic and transport

properties determine the perfect conditions of a chemical process simulation. These days, the process

industry or engineers rely on using simulators to perform their computations, and all commercial

simulators today are equipped with a countless of property packages with property estimation methods

such as NRTL, SRK, UNIQUAC, and many more. It is of great importance to know which property

package is appropriate for one’s process computation. The objective of this section is to provide some

accurate and deep understanding into the performance of those property packages and selection of a

proper method to represent the various physical and chemical phenomena under a given set of

operating conditions where mononitration and dinitration occurs. Another aim is to enable the reader

to make the correct selection of property method.

CHEMCAD has several property packages that each consist of different computational methods that

are used to estimate thermodynamic and transport properties (16).

What kind of thermodynamic and transport properties are of interest in process simulation?

If we take a look at the pump nitration process which is Chematur’s process for production of DNT,

we find that the process involves separating, moving of fluids, vaporizing etc. (5,8).

To select the correct property method, the pump nitration process was analysed and the properties

required to execute some computations were identified (Figure 7, appendix D).

14

Figure 7: The figure shows the process flowsheet for the DNT nitration process.

3.3. Analysis of the DNT nitration process

3.3.1. Pump A pump increases the pressure of a liquid stream by adding work to it. Like most pumps, a centrifugal

pump converts input power to kinetic energy of the fluid by accelerating fluid in an impeller (17,18).

Therefore, the required properties include heat capacities, liquid density and pressure.

3.3.2. Separator In the design of the separator, it was necessary to understand how the chemical components partition

themselves between the two liquid phases and to set up the mass relationships of the phases. Also, it

was important to understand how much liquid and vapour are produced at the operating temperatures

and pressures. This means that the separation process required the properties of vapour and liquid

densities, enthalpies and pressures (17,18).

3.3.3. Heat Exchangers Heat exchangers in the pump nitration process allow the fluids to be cooled. The properties required

to represent the cooling process are: liquid vapour pressure, heat of vaporisation, liquid heat capacities,

densities, more (19).

3.3.4. Reactors The reactor allows the reactants to undergo a chemical reaction. Hence, the required properties include

heat of formation, heat of reaction, enthalpies, densities etc. (20).

15

3.4. Thermodynamic models CHEMCAD has over 50 phase equilibrium-K (K-value) models and about twelve enthalpy models

stored in its library. In other words, the phase equilibrium-K and enthalpy models are methods used

for the prediction of vapour-liquid or vapour-liquid-liquid phase equilibrium (called the phase

equilibrium-K) and the heat balance, which is called the enthalpy-H (16,21,22).

It should be noted that a selection of an inappropriate property method, leads to convergence

problems and erroneous results. Therefore, it was fundamental to consider, among others:

The process species and compositions.

The phases involved in the system.

Temperature and pressure operating ranges.

Nature of the fluids.

To understand why a particular property method is prefered in any process simulation, you must

understand some thermodynamic relationships among others:

Fugacity

Activity

Equilibrium

Enthalpy

3.4.1. Fugacity

Fugacity is the tendency of a substance to prefer one phase (liquid, solid and gas) over another. In

other words, fugacity is sort of or acts as a correction factor of pressure in real systems (23,24).

Fugacity can be estimated or determined from gases that are closer to reality than an ideal gas. Real

gases behave differently from ideal gases. An ideal gas is made up of molecules whose only interactions

are elastic collisions. Therefore, these molecules have no intermolecular forces between them contrary

to real gases. As a result, the ideal gas law may not hold for most gases and vapours encountered in

reality (25,26).

To solve this problem and accurately calculate chemical equilibria for real gases, pressure is replaced

by fugacity. So, fugacity is related to how non-ideal a gas behave and it is derived from equation of

states (e.g. Van der Waals, NRTL, UNIQUAC, and SRK) or other expressions that can describe non-

ideal systems.

16

For two-phases of a species to be in equilibrium, the pressure, temperature and the chemical potential

must be equal in both phases. Similarly, for pure species co-existing as liquid and vapour, if they are to

be in equilibrium, then the temperature, pressure and fugacity in both phases must be the same (27).

3.4.2. Activity Activity is a ratio of fugacity to the fugacity of the standard state of a material (pure component,

mixture or solution) at the same temperature and pressure (28,29). The variation of the activity of

component (activity coefficient) with temperature and composition is important in thermodynamic

process because it used to determine the Gibbs energy of mixing of a component, which in turn is

used to determine the equilibrium state of any chemical reaction.

3.4.3. Equilibrium At equilibrium, all thermodynamic properties such us free energy (U), Helmholtz free energy (A),

Gibbs free energy (G), amongst others., are minimized (30). To minimize the free energy functions,

i.e., A, U, and G we need to have a method for determining vapour-liquid/liquid-liquid

equilibrium(31).

17

3.5. Enthalpy changes upon mixing When two liquids for example sulphuric acid and water are mixed, the resulting enthalpy is not

necessarily the sum of the pure component enthalpies since the unlike interactions between molecules

is most likely different than the like interactions. In other words, if the H2SO4 – H2O interactions are

stronger than the H2SO4 – H2SO4 and H2O - H2O interactions, then the mixing process will be

exothermic. The task of this section is to study the change in enthalpy that occurs when mixing occurs.

The change of enthalpy upon mixing two liquid streams is shown in Figure 8

Figure 8: This figure shows a set-up of mixing two liquids.

Two different inlet streams with moles of liquid 1 (n1) are mixed with moles of liquid 2 (n2) in a mixer

and the resulting mixture leaves the process unit at a temperature T3. The energy balance for this

process can be defined as follows:

𝑞 = (𝑛1 + 𝑛2)ℎ3 − 𝑛1 ℎ1 − 𝑛2ℎ2 (1)

Heat of mixing may either be positive or negative. If it is positive then the reaction is endothermic

(meaning heat absorbed because the mixture has a higher enthalpy than the pure component) and if

its negative then the reaction is exothermic (heat given off because the mixture has a lower enthalpy

than the pure component).

From the conclusion above, you can tell from different types of molecular interactions in case heats

of mixing will contribute significantly to the energy balance. Nonideal mixtures have a fairly large heat

of mixing. For instance, the mixing of sulphuric acid and water produces so much heat because the

energy level of the system goes down and it releases heat.

18

In details, let us assume a very concentrated solution like 18 moles of sulfuric acid in one litre of

solution. The small amount of the water molecules will surround the sulphate ions very quickly since

there are so many sulphate ions. Therefore, the initial energy that is given off is enormous and of

course that energy will raise the temperature, causing the solution to boil vigorously.

Figure 9: Water molecules surrounding a sulfate ion.

The positive ends of water molecule attract themselves to the negative ions (sulfate ions) in the

solution, resulting to a lower energy state. So, the enthalpy of dilution is a negative quantity i.e., it is an

exothermic reaction which expels heat (energy is taken away from the ions and expelled to the

solution). Figure 9, shows one way to look at why that happens.

The negative charge has an electrical field around it and so that means that the electrical potential V

around the negative charge increases as the positive charge gets closer to it (34).

𝑉 =

𝑘𝑄

𝑟

(2)

where k is Coulomb’s constant

19

Figure 10: The graph of the electric potential for charge Q relative to the water molecules at r.

The electric potential energy for a charge q at r is then given as:

𝑈 =

𝑘𝑄𝑞

𝑟

(3)

20

Figure 11: The potential energy for a charge q at distance r

Notice that the charge q is positive which means that the electrical potential energy goes down as the

charge gets closer. In other words, the potential energy gets expelled and turns into heat when the

positive charge comes closer.

Again, in a mixture (e.g., water and an acid solution) the enthalpy of dilution is negative as a result of

a lower energy state.

3.6. Heats of dilution of mixed acids 2 kg of pure water at 21.1 ℃ was mixed adiabatically with 1 kg of 80% wt.-% sulphuric acid solution

at 21.1℃.

21

Figure 12: A set-up showing mixing of two liquids.

The mass is conserved and if we assume that there is no accumulation in the mixing unit then the:

Total mass balance: 𝑚3 = 3𝑘𝑔

To find the composition at the outlet stream, a balance equation was used based on sulphuric acid.

Notice that the balance equation can be used on either sulphuric acid or water.

𝑥𝑆𝐴𝑚1 = 𝑥3𝑆𝐴𝑚3 → (0.8 ∗ 1) = (𝑥3𝑆𝐴 ∗ 3) (4)

𝑥3𝑆𝐴 = 0.27 → 𝑥3𝑊 = 0.73 (5)

To find the outlet temperature of the mixture, an energy balance equation is needed.

Recall that for an adiabatic process 𝑑𝑞 = 𝑑𝐻 = 0

If a change in enthalpy is zero, that implies that the inlet enthalpy is the same as the outlet enthalpy

(32).

𝐻𝐼𝑁 = 𝐻𝑂𝑈𝑇 (6)

22

So, as seen earlier from equation (1) the specific enthalpy of the acid mixture can be solved from

𝑚1ℎ1 + 𝑚2ℎ2 = 𝑚3ℎ3 (7)

Since the inlet streams are both at 21.1 ℃, we should be able to use an enthalpy concentration diagram

to find the specific enthalpy of these solutions at a specific temperature and concentration.

3.6.1. Enthalpy concentration diagram Reference 55 shows the specific enthalpy of the solution in units of kJ/kg as a function of mass fraction

of sulphuric acid. The specific enthalpy of the solution is shown for several isotherms (each curve

represents different temperatures). In this case, both the inlet streams are mixed at a temperature of

21.1℃. The second stream is pure water, so the mass fraction of sulphuric acid is zero and the

isotherm is 21.1 ℃. The specific enthalpy can then be found by tracing the curve up to when the x-

axis is equal to zero. By visual inspection, this is approximately ℎ2 = 99 𝑘𝐽/𝑘𝑔. The first stream is at

80 wt.-% and also at 21.1 ℃. The 21.1 ℃ isotherm can also be traced up to where the x-axis is equal

to 80 wt.-%. This gives approximately ℎ1 = −240 𝑘𝐽/𝑘𝑔, also by visual inspection. The values can

then be substituted in equation (24) and the specific enthalpy of the mixture ℎ3 = −14 𝑘𝐽/𝑘𝑔 .

Therefore, the temperature at which sulphuric acid solution of 𝑥3𝑆𝐴 = 0.27 mass fraction equal to

ℎ3 = −14 𝑘𝐽/𝑘𝑔 can be found at the intersection of a horizontal line from ℎ3 = −14 𝑘𝐽/𝑘𝑔 , and

a vertical line from 𝑥3𝑆𝐴 = 0.27. By visual inspection the outlet temperature is 48 ℃ since it is in-

between 37.80 ℃ 𝑎𝑛𝑑 65.60 ℃ .

The found values by hand calculation are quite consistent with CHEMCAD values. The predicted

temperature by CHEMCAD was 48.90 ℃ (less than 2 % error). Many solutions with different

compositions of mixed acids were modelled with CHEMCAD and the overall values agree with

literature values.

23

3.7. Component specification In CHEMCAD, process engineers often use the word component when they talk about chemicals.

This section will illustrate how to create or add a new component into the databases of CHEMCAD

and the different steps as part of creating the new component.

The components present in feed streams and possible products are defined in the components

specification menu and are listed in Table 4.

Table 4: Components defined in CHEMCAD to represent DNT nitration process.

Name MF Name MF

Toluene C7H8 2,3-Dinitrotoluenea C7H6N2O4

m-Nitrotoluene C7H7NO2 Sulfuric acid H2SO4

o- Nitrotoluene C7H7NO2 Nitric acid HNO3

p- Nitrotoluene C7H7NO2 Nitrous acida HNO2

2,4-Dinitrotoluene C7H6N2O4 Water H2O

2,5- Dinitrotoluene C7H6N2O4 Nitric oxide NO

2,6- Dinitrotoluene C7H6N2O4 Nitrogen dioxide NO2

3,4- Dinitrotoluene C7H6N2O4 Carbon oxide CO

3,5- Dinitrotoluene C7H6N2O4 Carbon dioxide CO2

Nitrogen N2 m-Dinitrobenzene C6H4N2O4

Oxygen O2 2,4,6-Trinitrotoluene C7H5N3O6

Benzene C6H6 o-Xylene C8H10

Nitrobenzene C6H5NO2 6-Nitro-m-Cresola C7H7NO3

Nitrobenzoic acida C7H5NO4 4,6-Dinitro-o-Cresola C7H6N2O5

Nitrocresola C7H6NO3 Cresol C7H8O

a Chemicals that did not exist in the databases of CHEMCAD. MF: molecular formula.

Defining or specifying chemical components is something that typically precedes the initialisation of

process simulation (35). CHEMCAD is equipped with a component database known as

CHEMCAD component database/library which has over 1500 chemical components

from Design Institute for Physical Properties (DIPPR) databases (16,21). However, not all chemical

components are available in CHEMCAD component database. Therefore, the user must define the

missing chemical components before making use of them in CHEMCAD.

24

To define or create the chemicals that are not present (User-defined components) in the CHEMCAD

library, it is important to know the basic properties of the chemical component. For instance, when

you define the normal boiling point and molecular weight of toluene CHEMCAD will estimate the

rest of the missing properties based on different estimation methods among others, Joback and

UNIFAC group contribution method (36,37).

High accuracy is not claimed but if more chemical properties are provided, for instance the specific

gravity or API gravity, the other properties predicted or generated by CHEMCAD have an acceptable

percent error (less than 2% error).

Figure 13: This figure shows a dialog box for the property estimation of new components.

3.8. Creating new components It is of great importance to make sure that the properties of chemical components are being estimated

appropriately. In fact, the selection of a proper method to estimate the properties of a component is

one of the most important tasks that will affect the rest of the simulation. Therefore, it is important to

consider the choice of methods used to estimate different chemical properties.

25

The estimation of chemical components in CHEMCAD relies mostly on the group contribution

method. These methods are employed because it is not always possible to find experimental values of

properties for the chemical components of interest.

In these estimation methods, different specific formulas are used to estimate certain physical and

thermodynamic properties based on the groups present in the chemical structure (37–39).

There are five different methods used to estimate properties of pure components with CHEMCAD

(electrolyte, combustion solid, hydrocarbon-pseudo-component, Joback and UNIFAC method) but

only three of them will be discussed.

3.8.1. Defining a Hydrocarbon pseudo-component This method estimates from correlations suited for hydrocarbon pseudo-components. It requires only

the normal boiling point, molecular weight and the specific gravity as input data to generate reasonable

properties of a molecule. This method was not chosen for creating new components and therefore will

not be considered further.

3.8.2. Estimating by the UNIFAC method The UNIFAC method is a functional group contribution method that estimates physical properties

for all kinds of compounds(mainly organic compounds) based on their molecular weight and molecular

structure (40,41). CHEMCAD has data for all functional groups present in a molecule and therefore

generates an accurate value of critical properties among others temperature (TC) and pressure (PC).

3.8.3. Estimating by the Joback method The Joback Method is a group contribution method similar to the UNIFAC method.

When the molecular weight, normal boiling point and the number of each molecular group which

occur within the structure being estimated is provided, the Joback method estimates other properties

with a much higher accuracy (37).

Consider; toluene which has the chemical structure as shown in Figure 14.

To estimate properties for toluene you would:

Choose a “CH3” group and enter a 1 for the occurrence

Choose a “=C<” group and enter a 1 for the occurrence

Choose a “=CH-” group and enter a 5 for the occurrence

26

Once you have entered the basic properties and your structure’s groups, CHEMCAD

estimates the properties and creates the new component.

Figure 14: Molecular structure of toluene (42).

3.9. Validating the component estimation method(s) New components (see Table 4) were created because they did not exist in CHEMCAD’s databases.

Before creating the new components, multiple copies of other components were created based on

toluene which is a well-defined component in CHEMCAD. This was done to compare and select the

best estimation method.

Table 5 shows the properties of three versions of toluene that were created using three different

predictive methods, Psuedo-component method, Joback method and the UNIFAC method.

27

The three methods considered the estimation of density, critical properties, enthalpy and other

properties when the mass flow rate, pressure and temperature were fixed to be 100kg/h, one bar and

30 C respectively.

Further, the molecular weight and the normal boiling point of toluene were given as input data for all

the three versions of toluene.

The properties of toluene were then generated by CHEMCAD and used as reference.

Firstly, the pseudo-component method was selected and the basic properties of toluene, i.e. molecular

weight and the normal boiling point were entered manually. Also, the specific gravity of toluene was

specified to give more predicting power. CHEMCAD then used the information to create a new

component. The predicted component did not have the density parameters because the density was

predicted from the specific gravity and the boiling point instead of being calculated by temperature

dependent equation. This is not a very accurate predictive method for aromatic compounds and

therefore was not used. Note that the pseudo-components use a method which is used for only simple

alkenes.

Secondly, the group contribution methods were selected and the number of groups which occur within

the structure of toluene were entered manually in CHEMCAD. These two methods could predict the

critical properties, liquid density, the ideal gas heat of formation and Gibbs of formation among others.

It turned out that reliable results could be obtained with the Joback method. Also, the UNIFAC

method gave a reasonable result. However, the UNIFAC method depended critically on the manual

input of specific gravity. As a result, the Joback method was chosen over the UNIFAC method.

The critical properties were estimated by equations listed below.

Table 5: Properties of the three versions of toluene created with different methods.

Comparison of toluene library properties with CHEMCAD’s estimation methods

Methods

Name Library Pseudocomponent Joback UNIFAC

Temp C 30 30 30 30

Press bar 1 1 1 1

Enth MJ/h 14.057 -41.130 12.473 -1.5201

Mass flow kg/h 100 100 100 100

28

Liq vol m3/h 24.3254 24.3254 24.3254 24.3254

TC C 320 314.563 320.795 317.074

PC bar 41.08 40.463 41.143 40.092

CP Kj/kg-K 1.712 1.709 1.712 1.888

Density kg/m3 859.351 857.979 858.951 858.049

Th cond W/m-K 0.131 0.127 0.133 0.134

3.9.1. Molecular descriptors The number of molecular descriptors on the components that were created (see Table 6) was

determined and entered manually in CHEMCAD. Once that was done the Joback method was selected

and the estimations of density, ideal gas of Gibbs of formation, critical properties (e.g. TC and PC) etc.

were of a precision comparable to the actual properties of the pure components. The Joback method

was chosen because the it predicts properties based on the molecular structure (43).

Table 6: This table shows the number of each molecular group which occur within the structure being estimated.

Occurrences

Joback Groups NCa DNCa DNTa Cresol NBA NiA

=C< (ring) 3 4 3 3 2 -

-NO2 1 2 2 1 1 -

-CH3 1 1 1 1 -

-OH (phenol) 1 1 - 1 - -

=CH- (ring) 1 2 3 3 4 -

-O- (nonring) - - - - - -

>C=O (nonring) - - - - 1 -

-N= - - - - - 1

-OH (alcohol) - - - - 1 1

=O - - - - - 1

aNC= Nitrocresol, NiA=Nitrous acid, DNC= Dinitro cresol, DNT=2,3-Dinitrotoluene, Cresol=6-Nitro-M-Cresol

29

To process the chemical components mentioned above, it is important to understand how the state of

the components change with respect to pressure and temperature.

Since the DNT nitration process involves liquid phases, another consideration in selecting a suitable

thermodynamic model for the simulation was to know what was happening in the liquid phases. Liquid

solutions are classified into five categories:

Ideal solutions

Regular solutions

Polar solutions (highly non-ideal)

Electrolyte solutions, and

Special solutions.

Electrolyte and special solutions are not considered in detail here.

3.9.1.1. Ideal solution Ideal solution is a solution in which the entropy of mixing is assumed to be

∆𝑆𝑚𝑖𝑥 = −𝑅 (𝑥𝐴𝑙𝑛𝑥𝐴 + 𝑥𝐵𝑙𝑛𝑥𝐵) (8)

where 𝑥𝐴𝑎𝑛𝑑 𝑥𝐵 are the mole fractions of two components, and the enthalpy of solution is zero.

∆𝐻𝑚𝑖𝑥 = 0 (9)

As a result, the vapour phase of ideal solution behaves as an ideal gas (low pressures) and all the

molecules in the liquid phase are made up of species of similar molecular size and chemical nature (44).

It should also be added that these are typically solutions with no intermolecular forces of attraction

that form ideal mixture in which the activity coefficient becomes close to one throughout the

concentration range.

If the liquid phases are ideal solutions and the vapour phase is an ideal gas, Raoult’s law describes the

distribution of species between the phases as:

𝑃𝑖 = 𝑌𝑖𝑃 = 𝑥𝑖𝑃𝑖0 , 𝑎𝑡 𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑇 (10)

Where:

𝑃𝑖 is the partial pressure,

30

𝑃𝑖0 is the vapour pressure at saturation

𝑃 is the system pressure.

The vapour-liquid equilibria can be determined using Raoult’s law:

𝐾𝑖 =

𝑃𝑖0

𝑃

(11)

For these systems, it is recommended to use the ideal vapour pressure model (VAP model) for phase

equilibrium-K and SRK for enthalpies. An example of this is the acetonitrile/nitromethane system.

3.9.1.2. Regular solutions Unlike ideal solution, regular solution assumes that the enthalpy of mixing is not zero. It depends on

compositions.

∆𝐻𝑚𝑖𝑥 = 𝛽𝑥𝐴𝑥𝐵 (12)

where B is the interaction parameter. It should be noted that the entropy of mixing is the same as that

for the ideal solution.

These systems are best modelled using SRK, Peng-Robinson, API SRK, BWRS and MSRK. It is

recommended to use Peng-Robinson and SRK for all hydrocarbon systems, except for certain

processes with wide boiling values and heavy hydrocarbons at low pressures.

MSRK is recommended for chemicals such as branch-chained hydrocarbons, halogenated

hydrocarbons, some polar compounds, etc.

CHEMCAD calculates equilibrium values using fugacity coefficients

𝐾𝑖 =

𝑌𝑖

𝑋𝑖=

∅𝑙𝑖

∅𝑣𝑖

(13)

31

Table 7: Thermodynamic models suitable for regular solutions.

Equilibrium Enthalpy Process Application

PR or SRK PR or SRK All hydrocarbon systems for pressures > 10 bar

GS LK Hydrocarbon processes with a wide boiling range −18℃ 𝑡𝑜 430℃

ESSO LK Processes with heavy end hydrocarbons at pressures > 7 bars

Temperatures (90℃ 𝑡𝑜 200℃)

MSRK SRK Branch-chained hydrocarbons, halogenated hydrocarbons and polar

compounds

3.9.1.3. Polar solution These are solution systems in which the non-ideal behaviour of the liquid phase arises from molecular

interactions. The vapour phase is assumed to be a regular solution and CHEMCAD allows the user to

model the system with activity coefficient methods, which require binary interaction parameters (BIPs)

for accuracy (45).

The methods that suit for activity coefficients include NRTL, UNIFAC, Van Laar, UNIQUAC,

Wilson, T.K. Wilson, Margles and GMAC. It is recommended to use NRTL, UNIQUAC and Wilson

when the data available is sufficient (>50%) and UNIFAC when the data is incomplete (<50%).

3.9.1.4. Electrolyte solution These solutions are treated as true species (molecules and ions) and CHEMCAD requires binary

interaction parameters (BIPs) for accurate modelling.

The recommended thermodynamic model is NRTL and the enthalpy model is LATE.

For the DNT nitration process (non-ideal solutions), the main thermodynamic model (K model)

selected for this study was the non-random-two-liquid (NRTL). NRTL is a K-value model that uses

binary interaction parameters (BIPs) and serves to model the non-ideal behaviour in the liquid phase.

It is a suitable model because the system exhibits vapour-liquid-liquid equilibrium and operates at a

pressure of less than 20 bars with an assumption of the media as an electrolyte (46). Other suitable

models for two liquid phases are UNIQUAC and UNIFAC LLE.

The enthalpy model chosen was latent heat. Further, the nitration process required an equation of state

approach. The Redlich-Kwong-Soave (SRK) equation of state with the phase option of

32

vapour/liquid/liquid was used to calculate the phase equilibria during nitration (47,48). SRK was also

chosen to calculate the fugacity.

A general recommendation when selecting an enthalpy method is given in Table 8:

Table 8: This table shows suitable enthalpy models for equilibria-K values.

If the phase equilibria-K method is: Use this for enthalpy:

Peng-Robinson (PR)

Peng-Robinson (PR)

BWRS

BWRS

SRK.API SRK, MSRK, TSRK, VAP, ESD, SAFT

SRK

ESSO, Grayson-Streed (GS)

Lee-Kesler (LK)

NRTL, PSRK, WILS, T.K. Wilson, UNIQ,

VANL, HRNM

Latent Heat

Amine

Amine

PPAQ SRK or Latent Heat

33

3.10. Process Flowsheet modelling The process flowsheet window in CHEMCAD allows the user to construct the flowsheet graphically.

CHEMCAD is equipped with an array of process units, connectors and controllers from which a

process plant and its sections can be designed.

3.11. Modelling process equipment

3.11.1. Feed streams The feeds were designed to provide a feed flow control system in which the other feeds (nitric acid,

recovered sulphuric acid, nitric/sulphuric mixture and recovered DNT feed) were remotely controlled

from the toluene feed, a master control feed. In other words, the feed flow control system was used

to maintain the flow rate of the master control feed at a specified proportion relative to that of the

other feeds in the DNT nitration process.

3.11.2. Pumps The pump in CHEMCAD was used to increase the pressure of the fluid stream. The desired pressure

was controlled by the piping system and the process involved, whereas the total flow rate in each stage

was controlled by feed-backward controllers in the downstream process units, unit operations

(UnitOps). A feedback controller is a mathematical controller that is used to adjust the required

variables. The total mass flow rate of each loop was adjusted by the controller until the temperature

increase over the reactor system was approximately 10 ℃.

Prior to using the feed-backward controllers, two process units (a stream reference and a feed-forward

controller) were combined to connect the loop. The process units connect two flows to maintain a

defined ratio and enable the simulation to forward all the properties of the upstream process units to

downstream units.

There are many different types of pumps in CHEMCAD. However, these can be classified in two

basic types: positive displacement pumps and centrifugal pumps. The type of pump used in

CHEMCAD to model the DNT nitration process was a centrifugal pump with an electrical motor as

a drive.

3.11.3. Centrifugal Pump-Solution Principal The two liquid phases enter the centre of the pump and exit perpendicular to the inlet. On the inside

of the centrifugal pump, there’s an impeller which rotates at thousands of revolutions per minute (rpm)

and behind the centrifugal pump there’s an electrical motor which is responsible for spinning the shaft

34

that rotates the impeller. When the fluid enters the centre of the centrifugal pump, the impeller blade

flings the fluid outward towards the pump casing and the work done on the fluid results in an increase

in pressure and temperature as the fluid leaves the centrifugal pump. This pressure increase is critical

for moving the fluid upward or across long lengths of piping from one process unit to another.

If the inlet or discharge conditions of one-, two-, or three-phase liquid flows are unknown,

CHEMCAD allows the user to specify the known variables on a pipe network system and therefore

solves for the unknown variables on the flowsheet. For fluid flow through a unit operation, flow rate

may be calculated as a function of the inlet and outlet pressure. CHEMCAD is equipped with many

unit operations that calculate flowrate as a function of pressure see Figure 15.

Figure 15: CHEMCAD UnitOps that calculate flow as a function of pressure.

The flow through the pipe system is calculated by CHEMCAD from this equation below (49):

�̇� = 𝑘√∆𝑃𝜌𝑑5

𝑓𝐿

(14)

P=pressure drop

p=fluid density

35

d=pipe inside diameter

f=pipe friction factor

k=constant

L=equivalent length

Prior to designing a pump, CHEMCAD pipe sizing tool was used to size a piping system for design

flowrate through the pipe, at 40℃ − 70 ℃. A piping system represents the flow of fluids through

many unit operations. If, for example, variables such as flow rate and pressure are specified on the

system, CHEMCAD calculates the unknown variables.

A flow method known as Beggs and Brill’s two-phase method was chosen for the piping system. The

fluid flow method considers the effect of vapour and liquid phases on pressure recovery due to

elevation change (50). Also, a feedback controller was added to the piping system in order to control

the pressure.

The pipe parameters (length, elevation, diameter etc.), outlet pressure and the pump efficiency were

specified and CHEMCAD simultaneously calculated the flowsheet to converge on the unknown

pressures and updated the state variables of the inlet stream. CHEMCAD also calculated the NPSHA

(Net Positive Suction Head Available) which is the absolute pressure at the suction port of the pump.

The NPSHR (Net Positive Suction Head Required) which is the minimum pressure required at the

suction port of the pump to prevent it from cavitation, is a function of the pump and its value is

provided by the pump manufacturer. More pressure at the suction side must be available than the

pump requires in order to prevent cavitation. In other words, the NPSHA must be greater than the

NPSHR. If the pressure at the inlet is below the vapour pressure of the liquid, pump cavitation occurs.

The occurrence of pump cavitation damages the pump. For instance, the pump becomes noisy, it loses

its capacity and it also experiences pitting damages which in turn reduce the operational life of the

pump.

NPSHA is calculated by CHEMCAD from the equation below.

𝑁𝑃𝑆𝐻𝐴 = 𝐻𝐴 ± 𝐻𝑍𝐻𝐴 − 𝐻𝐹 + 𝐻𝑉 − 𝐻𝑉𝑃 (15)

HA=the absolute pressure on the surface of the liquid in the feed.

HZ= the vertical distance between the surface of the liquid in the feed and the centreline of the pump.

HF=Friction losses in the suction piping.

36

HV=Velocity head at the pump suction port

HVP=Absolute vapour pressure of liquid at the pumping temperature.

The efficiency specified was lower than the default efficiency and this caused the temperature of the

liquid to increase because the work added went into the fluid. It should be noted that if there is vapour

inside the pump, CHEMCAD will issue a warning and when the efficiency is at default (efficiency=1),

ideal work is calculated. Pumps should not be used to pressurise vapours, otherwise the CHEMCAD

will bypass the pump. In a real industrial environment the pump will be damaged by cavitation (50).

3.11.3.1. Efficiency In order to find the best option which results in the highest efficiency and lowest long-term cost, it

was necessary to understand the nature of the fluid, inlet and outlet pressure, flow rate and the electric

power needed when designing the centrifugal pump.

When selecting the appropriate material of construction, it was important to consider the cost and the

durability of the material since the DNT nitration process involves high temperatures (particularly

dinitration) which in turn increases the likelihood of the reaction between the process stream and the

surface material (51). The appropriate material chosen from the CHEMCAD Cost Estimation tab was

stainless steel and this is because stainless steel can resist corrosion and reactivity with many acids and

bases (52).

The 316 SS was chosen as the preferred material for the pump because the process streams have a

high concentration of acids going through them.

The work done on the fluid is calculated by CHEMCAD as:

𝑊 = 𝐹 ∗ 𝑉 ∗

∆𝑃

𝐸

(16)

Where:

F= flowrate of the input stream

V =molar volume of the stream

∆𝑃 = pressure increase

The efficiency in the dinitration stage was set at default (eff=1) to validate if the process units in

CHEMCAD follow the thermodynamic rules, see Table 9.

37

From the second law of thermodynamics, we can conclude that heat cannot be converted directly and

efficiently at 100% level into work.

So just to justify the statement above, assume for example a system whereby there is a large source of

heat in a bath. Can the heat be put into some engine, for example a pump and generate work at 100%

efficiency?

Figure 16: A set-up showing the efficiency of a heat engine.

The work from the engine is defined as:

𝑊 = 𝑄1 − 𝑄2 (17)

𝐸𝑓𝑓 =

𝑂𝑈𝑇

𝐼𝑁=

𝑊

𝑄1= 1 −

𝑄2

𝑄1

(18)

The second term 𝑄2

𝑄1 is a fraction that is less than one but positive. So the efficiency is going to be less

than 100%. In other words, the efficiency of an engine which converts heat into work must always be

less than 100%. Otherwise, the engine will not work. The ideal work serves only as a basis for

thermodynamic calculations and does not exist in industrial processes.

3.11.3.2. Suggestions In order to ensure that your NPSHA pressure will be adequate to cover the required pressure, it’s

advisable to get NPSHR value from the pump manufacture. The NPSHR value used as a reference for

this thesis was that of an actual plant of DNT nitration process.

38

It is recommended to use a NODE unit operation on the flowsheet when using CHEMCAD to

calculate NPHSA. This helps to measure pressure and flow balances between unit operations.

In a recycle loop, it is recommended to specify the outlet pressure instead of the pressure increase. If

the pressure increase is specified, then the pressure will be increased every time the loop passes the

pump and this in turn causes the loop not to converge since the pressure is raised on every iteration.

The efficiency of the pump should not be set at default because at the default value ideal work is

calculated and this does not represent a value that can be used to size an actual industrial pump.

Table 9: Equipment summary table for the DNT nitration process

Centrifugal pumps

Name CCT1 CCT2

Type Centrifugal Centrifugal

Drive Electric Electric

Material Stainless steel 316/304 Stainless steel 316/304

Flowrate(kg/hr) 747827 788260

Fluid Density (kg/m3) 1574 1694

Shaft Power(kW) 145 44

Efficiency 0.8 0.8

Stream properties

Inlet p (bar)

6.5 6.5

Outlet p (bar)

6.5 6.5

Inlet T (℃)

38.6 67.7

Outlet p (℃) 38.9 67.8

3.11.4. Reactors Since the reaction kinetics for the process are not well documented for the experimental studies at

Chematur, kinetics based models were not used. Therefore, the Equilibrium reactor in CHEMCAD

39

was the only reactor model suitable for simulating the nitration of toluene to DNT. The reactor

considers simultaneous phase and chemical equilibria and calculates Liquid-Liquid-Vapour equilibrium

(31).

A computer model was designed based on the composition of input data from an experimental study.

The composition of the input stream in the simulation is listed in Table 4 and the equipment summary

is tabulated in Table 11.

There are several different models of reactors available in CHEMCAD and each model requires

different specifications.

The models are:

Stoichiometric reactor Simulate one reaction, for a given set of stoichiometric factors, key component and fractional

conversion.

These are reactors where reaction kinetics are unknown but stoichiometry and extent of reaction are

known.

Equilibrium reactor Simulates reactors with multiple reactions defined by conversion or equilibrium ratios.

These are reactors with simultaneous chemical equilibrium and phase equilibrium.

Gibbs reactor Performs chemical and phase equilibrium by Gibbs energy minimization.

These are reactors with simultaneous phase and chemical equilibrium.

Kinetic reactor Models continuous stirred tank reactor and plug flow reactor.

One-, two, or three-phase reactors with rate-controlled and equilibrium reactions in any phase based

known stoichiometry and kinetics.

3.11.4.1. The Equilibrium Reactor (EREA) With the equilibrium reactor model, CHEMCAD allows you to simulate reactors with up to 300

simultaneous reactions that are defined by conversion or equilibrium ratios. The equilibrium reactor

model calculates the product stream flow rates, compositions, and thermal conditions by solving the

equilibrium equation along with the mass and energy balances

40

ln(𝑘𝑒𝑞) = 𝑙𝑛

(𝑃1)(𝑥1) ∗ (𝑃2)(𝑥2) … … … . (𝑃𝑖)(𝑥𝑖)

(𝑅1)(𝑦1) ∗ (𝑅2)(𝑦2) … … … . (𝑅𝑗)(𝑦𝑖)= 𝐴 +

𝐵

𝑇+ 𝐶𝑙𝑛(𝑇) + 𝐷𝑇 + 𝐸𝑇2

(19)

where:

Pi=partial pressure of product component i.

Ri =partial pressure of reactant component j.

Xi=power coefficient of the product component i i.e. stoichiometric coefficient (always positive).

Yi=power coefficient of the reactant component j i.e. stoichiometric coefficient (always negative).

T=Temperature, absolute degrees.

A, B, C, D, E=coefficients of the equilibrium reaction equation.

The reaction completion was defined based on user-specified reaction stoichiometry and specified

conversion of a key component (reactant).

41

Figure 17: The equilibrium reactor in CHEMCAD

The equilibrium reactor is equipped with three different types of reactors, namely general, shift –and

methanation reactor:

General equilibrium reactor A reactor where the user must supply all data apart from the heat of reaction, which is calculated by

CHEMCAD.

Shift reactor and Methanation reactor For the shift reactor and the methanation reaction, all of the required equilibrium data and

stoichiometry for the water-gas shift reaction and methanation reaction are stored within CHEMCAD

database; therefore, the entry of the equilibrium data is not required.

The reactions modelled are:

𝐶𝑂 + 𝐻2𝑂 ↔ 𝐶𝑂2 + 𝐻2 (𝑊𝑎𝑡𝑒𝑟 − 𝐺𝑎𝑠 𝑆ℎ𝑖𝑓𝑡 𝑅𝑒𝑎𝑐𝑡𝑖𝑜𝑛) (20)

𝐶𝑂 + 3𝐻2 ↔ 𝐶𝐻4 + 𝐻2𝑂 (𝑀𝑒𝑡ℎ𝑎𝑛𝑎𝑡𝑖𝑜𝑛 𝑅𝑒𝑎𝑐𝑡𝑖𝑜𝑛) (21)

42

Note that the phase for the shift and methanantion reactors is always assumed to be vapour, regardless

of what the user enters as the reaction phase. In CHEMCAD, any equilibrium reactor (general, shift,

or methanation) can be defined as isothermal, adiabatic or having a specified heat duty.

Once again, an equilibrium reactor was the most appropriate reactor for the nitration of toluene to

DNT (53) because the nitration of toluene to DNT involves multiple reactions and mass transfer

phenomena that occur simultaneously. The general equilibrium reactor was specified as the reactor

model and the equilibrium coefficients as well as conversions for each reaction were entered on the

reaction data menu.

The reactions that takes place in the reactor are as follow:

Table 10: Reactions used to represent the DNT nitration process.

Descriptions Reactions occurring

Nitration of toluene Toluene + HNO3 --> MNT + H2O

Oxidation of toluene to cresol Toluene + HNO3 --> Cresol + HNO2

Nitration of cresol Cresol + 2 HNO3 --> DNOC + 2 H2O

Total oxidation of DNOC DNOC + 13 HNO3 --> 15 HNO2 + 2 H2O + 2CO + 5CO2

Dissociation of HNO2 2 HNO2 --> NO + NO2 + H2O

Nitration of MNT MNT + HNO3 --> DNT + H2O

These reactions were specified as series reactions and the equilibrium reactor solved the reactions

successively. The nitration of toluene and MNT were performed based on the process feed stream

whereas the rest of the reactions were performed based on the composition after the nitration process

had occurred. This calculation mode is similar to using several stoichiometric reactors in series for each

reaction. Note that the stoichiometric reactor in CHEMCAD simulates only one reaction whereas the

equilibrium reactor simulates several reactions and is therefore more effective.

The reactions were operated adiabatically and the heat of reaction was calculated from the heat of

formation. In other words, the reaction process was assumed to be adiabatic and this implies that the

reactor unit was well insulated and there is no heat exchange with the surroundings. Any heat that is

absorbed or released upon mixing is transferred to the final mixture.

43

3.11.4.1.1. Heat of reaction

∆𝐻𝑅𝑥𝑛0 = ∑ 𝑉𝑗

𝑆

𝑗=1

∗ 𝐻𝑓,𝑗0

(22)

Where:

∆𝐻𝑅𝑥𝑛0 = heat of reaction at reference state.

𝑉𝑗= stoichiometric coefficient of component j (always negative for reactants and positive for products).

𝐻𝑓,𝑗0 = heat of formation of component j at standard state

S= number of chemical species involved in reaction

J= subscript of chemical species involved in reaction, from 1 to S.

3.11.4.1.2. Heat Duty of reactor

𝐻 = (𝑅 ∗ ∫ 𝐶𝑝.𝑟𝑒𝑎𝑐 ∗ 𝑑𝑇𝑇𝑟𝑒𝑓

𝑇𝑖𝑛

) + (𝑃 ∗ ∫ 𝐶𝑝.𝑝𝑟𝑜𝑑 ∗ 𝑑𝑇𝑇𝑜𝑢𝑡

𝑇𝑟𝑒𝑓

) + ∆𝐻𝑅𝑥𝑛(𝑇𝑟𝑒𝑓) (23)

Where:

H=heat duty

R= total reactant flow rate

CP= heat capacity of mixture

Hf= heat of formation at reference temperature

M= moles reacted

P= total product flow rate

T= temperature

Tref = reference temperature

After completing the UnitOp specifications for the equilibrium reactor, CHEMCAD computed outlet

composition by completing mass and energy balances based on input streams and reactions along with

the equilibrium coefficients.

44

Table 11: Equipment summary table of the equilibrium reactors

Reactors

Name CCT1 CCT2

Orientation Vertical Vertical

Materials of Construction 316 SS 316 SS

Flowrate (kg/h) 747827 788260

Inlet temperature (C) 39 68

Outlet temperature (C) 50 80

Inlet pressure (bar) 6.5 6.5

Outlet pressure (bar) 6.5 6.5

Vapour fraction 0 0

Heat of reaction (MW) 2156 2079

3.11.5. Heat Exchangers Heat exchangers in CHEMCAD are used to heat or cool process streams. Heat exchangers rely on

convective and conductive heat transfer across a surface.

Heat exchangers have two inlet streams:

1. Utility stream

2. Process stream

Utility stream The purpose of the Utility stream was to cool down the Process stream. The temperature change in

utility streams across the heat exchanger should be greater than around 5C but not more than 20C

and the reason for this is that if the process streams are cooled down too much, it leads to an excessive

energy requirement on the process unit supplying the utility stream to the process. In other words, the

energy intensity equipment involved in maintaining the heat utility stream will not be designed or used

optimally. Also, a difference in temperature of less than 5 C for utility stream requires an excessively

high utility flow rate, which in turn would mean that a cooling tower or a steam boiler will be needed,

because the temperature is only decreasing and increasing by a couple of degrees. So, in order to

achieve the desired utility temperature change, the flowrate of the utility stream was adjusted by

feedbackward- controllers.

45

Process stream A shell and tube heat exchanger is the most common type of heat exchanger used in a chemical plant

environment. The heat exchangers used had two separate sides; for the two different streams. The

tube side is normally used for the process stream and the shell side is used for the cooling or heating

media.

CHEMCAD does not choose a type of heat exchanger for the user, so in order to select the best type,

consider the cost, stream conditions and stream properties.

There are many varieties of heat exchangers available in CHEMCAD for any process and each variety

are most appropriate based on specific process requirements.

There are three main types of shell and tube heat exchangers:

Fixed Head Fixed head heat exchangers feature tubes which are fixed on tube sheets inside a shell. Hot or cold

fluid enters the tube side of the heat exchanger while the opposite fluid, either hot or cold flows

to the shell side.

Floating Head Floating head heat exchangers are very similar to fixed head heat exchangers, except they feature

tubes which are on a floating head, which allows them to expand and contract.

U-Tube U-Tube heat exchangers feature U-shaped tubes, which allow for some expansion and contraction and

allow fluids to flow more easily through the heat exchanger.

The benefit of using these types of heat exchangers is that they can accommodate high flow rate

streams and a wide range of heat exchanger areas up to 1000 m2 and a wide range of temperatures and

pressures.

When selecting a heat exchanger, it’s necessary to narrow down the choices based on the most limiting

factors:

Area required for heat transfer, which was determined by using CHEMCAD. Hand

calculations could also determine the area.

Type of fluid (viscous, corrosive, reactive, fouling?)

A special material is required to avoid reactivity with the heat exchanger since the process

involves oxidizers, acids, bases etc.

46

Temperature and pressure ranges for both streams

The temperature and the pressure of either stream going through the heat exchanger was

examined if it was excessively high or low since these conditions require special materials.

Once the choices were narrowed down, the cost of each feasible option to make a final decision

was calculated by CHEMCAD.

A fixed head heat exchanger was chosen because the streams have a moderate log mean temperature

difference, so we can except a low thermal expansion and contraction.

The area is calculated in CHEMCAD by using this formula

𝑄 = 𝑈 ∗ 𝐴 ∗ ∆𝑇𝐿𝑀 (24)

where Q is the heat duty or the energy required to cool down the process stream to the desired

temperature, U is the overall heat transfer coefficient which is generally a measure of the effectiveness

of the heat exchanger in transferring heat from one fluid to another, A is the heat transfer surface area,

∆T (log mean=LM) represents the temperature driving force for heat transfer.

CHEMCAD does not provide materials of construction. This meant that I had to select the

appropriate materials by balancing the cost and the durability required to withstand the temperature

and chemical exposure to the streams.

47

Table 12: Equipment summary table for Heat Exchanger

Heat Exchangers Mononitration Stage Dinitration Stage

Type Floating Head Floating Head

Heat Duty (kW) 4600 4500

Materials of Construction 316 SS 316 SS

Flowrate(kg/h) 747835 788260

Inlet Temperature (C) 40 70

Outlet Temperature (C) 49.92 80

Inlet Pressure (bar) 6.50 6.50

Outlet Pressure (bar) 6.50 6.50

48

3.11.6. Separators The separator is a rigorous separation model that combines input streams and separates the results

into two output streams of different composition and thermal conditions.

By specifying split fractions and split flow rates for each component, almost any kind of separation

can be performed by the CHEMCAD separation model. The CHEMCAD separator provides various

output temperature specifications for the product streams that include bubble point, subcooled, dew

point and superheated conditions. This module can be used to design a separator, such as setting apart

a pure component from a mixture or separating the components from a process stream.

The component separator is useful when trying to model steady state conditions of unusual separation

equipment and conditions. The heat balance is made by setting the UnitOp duty equal to the difference

between the inlet and the outlet streams. However, the outlet flow systems of the separators do not

bear any resemblance to the actual plant separators. In the actual plant the recycled acid is separated

off first whereas in the simulated model the recycled acid and the spent acid are separated in the last

step. Notice that; the recycle acid in the actual plant is separated from the two-phase liquid system

consisting of crude organics and excess spent acid. In other words, the separators perform a liquid-

liquid extraction (LLE).

Liquid-liquid extraction is a separation technology that separates chemical components based on their

relative solubility in two immiscible liquids. The fluids are fed into the separator, where the phases are

immiscible or slightly miscible with each other. A formation of a dispersion occurs and one of the

liquids is dispersed as droplets in the other liquid.

At the interface or between the dispersed phase (droplets) and the surrounding liquid, a mass transfer

occurs. When the relative densities of the liquids are different, the droplets accumulate below or above

the surrounding liquid, and this in turn leads to a subsequently separation of the two liquids.

The process of simulating separation in CHEMCAD is straightforward once the user knows the

compositions of the outlet to a separation or has a fully specified feed.

49

4. Results The results from the experimental study and available industrial data were used to validate the

simulated model. Both the available industrial data (given in parenthesis) and the experimental data are

complementary.

The abbreviation “n.d.” in the tables below stand for “not detected”. In other words, the values weren’t

measured or considered in the experimental study.

4.1. Spent acid from nitration As it can be seen in Table 13, the composition of the spent acid has a good agreement between the

experimental study and the predicted data from CHEMCAD. The predicted composition of the spent

acid has a concentration of approximately 69.0 wt.-% sulphuric acid, 1.5 wt.-% nitric acid and 1. 0 wt.-

% organic compounds (MNT/DNT). Although the concentration of the sulphuric acid is slightly

lower than the observed experimental value of 70.40 wt.-%, the predicted values still indicate that the

simulated model does not differ significantly from the real-world process.

The composition of the spent acid is the same as the composition of the recycled stream but the flow

rates are different. The flow rate of the spent acid in the simulated model was 21723 kg/hr at 40 C

and at a pressure of 3 bars.

The spent acid is treated in a separate process to a final concentration of approximately 93 wt.-%

sulphuric acid. As a result, 116.720 tons of sulphuric acid per year is recovered for recirculation to

the process (Table 14). The main organic content of the spent acid, MNT/DNT, are also recovered

and reused in the process (Table 15).

50

Table 13: Experimental results versus simulation predictions for Spent Acid.

a The DNT nitration process was conducted without the recovered acid mixture(NAR) and recovered DNT (Rec DNT).

bDNT nitration process conducted with NAR and

Rec DNT.

Table 14: This table shows the composition of the Recovered Sulphuric Acid.

Recovered Sulfuric Acid

Composition:

H2SO4 93.0 wt.-%

HNO3 0.5 wt.-%

MNT/DNT 0.2 wt.-%

Flow rate 14590 kg/hr

Temperature 40 C

Pressure 300 kPa

Table 15: This table shows the Recovered DNT.

Recovered DNT

Composition

DNT (mainly) + MNT saturated with water

Flow rate 221.1 kg/hr

Temperature 50 C

Pressure 300 kPa

Spent Acid Composition

Component Experimental study Simulated model

(%)a (%)b

H2SO4 70.40 69.0

HNO3 0.70 1.50

HNO2 1.70 0.00

Organics 1.00 0.98

Water 27.30 29.02

51

4.2. The MNT Content In Table 16, the MNT composition in the experimental study was reported as 89.60 % whereas the

predicted value from the simulation model was 92.70 wt.-%.

The MNT contains 0.02 wt.-% cresols and phenols (other organics) which is reasonable good

compared to the expected value of 0.05 wt.-%. Also, the MNT contains 1.44 wt.-% acid content which

is similar to the expected traces in the actual plant of the DNT nitration process.

An increase of cresols and phenols favours the formation of effluent gas from nitration. As it can be

observed in Table 16, the simulated model doesn’t indicate a complete conversion of toluene. The

unreacted toluene in the mononitration stage helps in correcting the Delta T.

The production rate of the MNT was 1600 kg/hr at 40 C.

Table 16: The composition of the acid phase in the organic phase and MNT yield

Crude MNT Composition

Component Experimental study Simulated model

(%) (%)

MNT 89.60 92.70

DNT 7.80 0.00

Toluene 2.30 (6) 6.00

H2SO4 n.d (1.2) 1.00

HNO3 n.d (0.6) 0.14

HNO2 n.d (0.2) 0.02

Water n.d (0.3) 0,29

Other Organics 0.19 (0.05) 0.02

52

4.3. Acid to Mononitration Stage The composition of the acid stream flowing to the mononitration circuit is the same as the composition

of the stream recycled back to the reactor system in CCT2. The rate of the acid to the mononitration

circuit was 17200 kg/hr. at 70 C. The acid stream contained approximately 0.2 wt.-% organic phase

and the concentration of the sulphuric acid was approximately 80 wt.-%, see Table 17.

The simulation model accounted for the recovered nitric/sulfuric acid mixture as well as the recovered

DNT which in turn caused the sulphuric acid concentration and the nitric acid concentration in the

mononitration stage to decrease and increase respectively. The sulphuric acid concentration decreased

to about 68 wt.-% whereas the nitric acid increased to about 3 wt.-%. To maintain the acid

concentration in the mononitration stage, an increase of 1-3 wt.-% of the sulphuric acid concentration

in the dinitration stage is required. The low content of the nitrous acid is due to a high fractional

conversion of its dissociation to nitric oxide, nitrogen dioxide and water.

Table 17: The composition of the organic phase in the acid phase.

Acid Composition

Component Experimental study Simulated model

(%) (%)

MNT n.d 0.20

DNT n.d <0.01

H2SO4 78.60 79.58

HNO3 1.30 1.92

HNO2 1.50 <0.01

Water 18.80 18.32

53

4.4. Crude DNT With the operating conditions, the simulation shows that annually 175.000 tons of Crude DNT with a

cresol/phenol content of 0.03 wt.-% can be produced. The crude DNT contains a MNT content of

approximately 0.1 wt.-% and a TNT content of 0.03 wt.-% which is less than what is obtained in the

industrial plant.

The acid content in the crude DNT is approximately 1.2 wt.-%, and it has therefore to be further

treated. As a result, 32.000 tons of nitric/sulfuric acid mixture (50 wt.-% acid content) per year is

accessible for recirculation in the process, Table 18. The isomer distribution of 2,4-DNT and 2,6-DNT

is 80.49 wt.-% and 19.51 wt.-% respectively. This ratio is similar to the values (80.1-and 19.9 wt.-%)

obtained from the experimental study.

The flow rate of crude DNT was 21989 kg/hr. at 70 C.

Table 18: This table shows the composition of the recovered nitric/sulphuric mixture

Nitric/Sulfuric acid mixture

Composition

HNO3/ H2SO4 50 wt.-%

HNO2 0.2 wt.-%

Water Balance

Flow rate 4000 kg/h

Temperature 40 C

Pressure 300 kPa

54

Table 19: A comparison of the composition of Crude DNT with the results obtained from the

simulated model and available industrial data (in parenthesis) or experimental data.

Crude DNT Composition

Component Experimental study Simulated model

(%) (%)

DNT 99.64 98.64

MNT 0.22 0.09

TNT 0.14 0.03

H2SO4 n.d (0.22) 0.22

HNO3 n.d (0.26) 0.36

HNO2 n.d (0.10) <0.01

Water n.d (0.51) 0.63

O.org (cresol/phenol) <0.01(0.05) 0.03

55

4.5. Energy balance The energy balance error is approximately 4%.

Table 20: The overall energy balance of the DNT nitration process.

Overall Energy Balance kW

Input Output

Feed Streams -57675.5

Product Streams -69495.1

Total Heating 0

Total Cooling -10515.7

Power Added 189.3

Power Generated 0

Heat of Reaction -3976

Total -71978 -69495.1

56

4.6. Mass balance As observed from Table 21, the overall mass balance has a relative percent error of 0.001%.

Table 21: This table shows the overall mass balance of the DNT nitration process.

Overall Mass Balance

kmol/h

kg/h

Input Output Input Output

Toluene 119.382 0 11000 0.001

o-Nitrotoluene 0.508 0.956 69.645 131.143

p-Nitrotoluene 0.335 0.68 45.898 93.218

m-Nitrotoluene 0.028 0.063 3.839 8.623

2,4-Dinitrotolue 0.535 92.313 97.473 16813.55

2,6-Dinitrotolue 0.155 22.38 28.144 4076.115

3,4-Dinitrotolue 0.016 2.327 2.857 423.77

2,3-Dinitrotoluene 0.004 1.483 0.686 270.125

2,5-Dinitrotolue 0.001 0.543 0.102 98.952

3,5-Dinitrotolue 0 0.044 0 7.972

Sulfuric Acid 142.753 152.2 14001.05 14927.65

Nitric Acid 242.028 6.423 15250.9 404.705

HNO2 0.186 0.011 8.763 0.533

Water 178.26 357.638 3211.359 6442.84

Nitric Oxide 0 0.002 0 0.048

Nitrogen Dioxide 0 0.047 0 2.162

Carbon Monoxide 0 0.012 0 0.323

Carbon Dioxide 0 0.018 0 0.8

Nitrogen 0 0.091 0 2.54

Oxygen 0 0.1 0 3.196

Nitrocresol 0 0.023 0 3.582

Trinitrotoluene 0 0.028 0 6.298

DNOC 0.005 0.002 0.99 0.351

NBA 0 0.007 0 0.725

Cresol 0 0.02 0 2.212

Total 684.195 637.409 43721.7 43721.43

57

4.7. Heat of dilution The heat of dilution of mixing acid solutions agrees with literature values. As seen in the tables

below, the relative percent error is between 2-5% which is acceptable.

𝜎𝑒𝑟 =|𝑥𝑛 − 𝑥𝑠𝑚|

𝑥𝑠𝑚× 100%

Where:

Xn value from the numerical calculation,

Xsm value from the simulated model.

The diagram of enthalpy versus weight percent was used for the sulphuric acid and water solution

whereas for the nitric acid and water solution numerical calculations and available literature data was

used to analyse the results.

Table 22: Sulphuric acid mixed with water.

Stream Name SA Feed Water Feed Outlet (SA 50)

Temp C 1 1 112

Pres bar 1 1 1

Total kmol/h 0.0102 0.0555 0.0657

Total kg/h 1 1 2

Flow rates in kg/h

Sulfuric acid 1 0 1

Water 0 1 1

Nitic acid 0 0 0

58

Table 23: Sulphuric acid mixed with 50 wt.-% sulphuric acid.

Stream Name SA Feed SA50 Feed Outlet (SA 75)

Temp C 1 1 75

Pres bar 1 1 1

Total kmol/h 0.0102 0.0329 0.0430

Total kg/h 1 1 2

Flow rates in kg/h

Sulfuric acid 1 0.5 1.5

Water 0 0.5 0.5

Nitic acid 0 0 0

With hand calculations, the temperature increase for the case in Table 24 was found to be 58 C.

This means that the predicted temperature of the model (60 C) has an acceptable percent error of

4.7%. The heat of dilution predicted by CHEMCAD is 422 kJ/kg.

�̇�𝐼𝑁∆𝐻 = �̇�𝑂𝑈𝑇𝐶𝑃∆𝑇

∆𝑇 =1𝑘𝑔/ℎ𝑟(0 − 403.2)𝑘𝐽/𝑘𝑔

2𝑘𝑔/ℎ𝑟 ∗3.4607𝑘𝐽

𝑘𝑔℃

= 58 ℃

59

Table 24: Nitric acid mixed with water.

Stream Name NA Feed Water Feed Outlet (NA 50)

Temp C 1 1 60

Pres bar 1 1 1

Total kmol/h 0.0159 0.0555 0.0714

Total kg/h 1 1 2

Cp kJ/kg 1.7558 4.2248 3.4607

Flow rates in kg/h

Sulfuric acid 0 0 0

Water 0 1 1

Nitic acid 1 0 1

With hand calculations, the temperature increase for the case in Table 25 was found to be 53 C.

This means that the predicted temperature of the model has an acceptable percent error of 2.2%.

The heat of dilution of 60% nitric acid is 358 kJ/kg. That is approximately 2.2 % error from a

literature value of 350.7 kJ/kg

60

∆𝑇 =1𝑘𝑔/ℎ𝑟(0 − 350.7)𝑘𝐽/𝑘𝑔

2𝑘𝑔/ℎ𝑟 ∗3.3809𝑘𝐽

𝑘𝑔℃

= 52 ℃

Table 25: Nitric acid mixed with 20 wt.-% Nitric acid

Stream Name NA Feed NA 20 Feed Outlet (NA 60)

Temp C 1 1 53

Pres bar 1 1 1

Total kmol/h 0.0159 0.0476 0.0635

Total kg/h 1 1 2

Cp kJ/kg 1.7558 3.7648 3.3809

Flow rates in kg/h

Sulfuric acid 0 0 0

Water 0 0.8 0.8

Nitic acid 1 0.2 1.2

61

4.8. Critical properties of the new components created. The critical properties of nitrocresol and NBA deviate from literature data but the critical properties

of the other components have a relative percent error of less than 1%.

Table 26: This table shows a comparison of the critical properties of the new components with values (see Appendix A).

DNOC Literature values Predicted values

Molecular weight 198.130 198.130

Critical T [C] 786.610 786.605

Critical P [bar] 49.874 49.873

Critical V [m3/kmol] 0.450 0.449

Tboil [C] 507.35 507.35

Cresol Literature values Predicted values

Molecular weight 108.140 108.140

Critical T [C] 422.000 424.400

Critical P [bar] 50.054 50.055

Critical V [m3/kmol] 0.290 0.282

Tboil [C] 190.900 191.000

Nitrocresol Literature values Predicted values

Molecular weight 153.14 153.140

Critical T [C] 810.520 978.890

Critical P [bar] 50.086 50.085

Critical V [m3/kmol] 0.370 0.368

Tboil [C] 623.680 610.520

Nitrous acid Literature values Predicted values

Molecular weight 47.013 47.013

Critical T [C] 248.160 248.159

Critical P [bar] 76.409 76.408

Critical V [m3/kmol] Not found 0.082

62

Tboil [C] 81.830 81.830

NBA Literature values Predicted values

Molecular weight 167.120 167.120

Critical T [C] 650.070 567.865

Critical P [bar] 50.514 64.204

Critical V [m3/kmol] 0.430 0.304

Tboil [C] 415.96 335.770

63

5. Discussion

In this project, the simulation of the DNT nitration process was built in CHEMCAD using an

equilibrium reactor. A good agreement between the simulation data and experimental data or available

industrial data was found. However, some differences appeared in the flow rate of product streams,

organic phase and acid phase. These differences were caused by a change in the design conditions.

Differences of the simulation and experimental compositions for spent acid, acid to mononitration

stage and crude DNT can be explained by the liquid-liquid equilibria.

In the case of the experimental study, the separation utilized differences in solubilities. The phase

separation is achieved under gravity because of a density difference between the phases. For simulation,

CHEMCAD couldn’t solve the liquid-liquid phase equilibria. The separation was based on split

fractions instead of mass transfer from one liquid phase to another, so, this fact influences the phase

equilibria.

The mass balance over the heat exchanger in the mononitration stage and dinitration stage has a small

error (0.001%), so; small differences between calculated results in the streams occur. These differences

are observed in the amount of water, sulphuric acid and nitric acid in the streams and consequently in

the energy balance. This inaccuracy is caused by a tolerance error (0.01) of the flow rate measurements.

The default mode accuracy (0.001) for flow rate measurements is better. However, a high accuracy

slows down the simulation. The DNT nitration process involves many parameters, control loops and

reactions, so, convergence is difficult to achieve with a high accuracy mode. To overcome this issue,

the error tolerance is set to 0.1% accuracy which is usually sufficient for the overall mass and energy

balances.

Recycle streams, electrolyte model, pressure drops and increased number of iterations were also some

factors that drastically slowed down the simulation.

It was observed that the recovered nitric/sulphuric acid mixture lowers the concentration of sulphuric

acid in the spent acid. To achieve a concentration of 70 wt.-% sulphuric acid, the concentration of the

recovered sulphuric acid in the dinitration circuit was increased to approximately 80%.

64

When setting up the flowsheet, a stream splitter was added after the separation units because multiple

streams couldn’t be sent out of them.

In the dinitration stage, the outgoing streams were of the same composition. However, the streams

had different flow rates. The recycled stream to the reactor system had the highest flow rate and this

meant that DNT from the separation unit could not be traced in the mononitration stage. For this

reason, the separation unit was specified to separate all (0.99 split fraction) the DNT from the process

stream. Usually, most process units (e.g., reactors, pumps and separators) do not allow multiple streams

to be sent directly into other process units. Therefore, a stream splitter is required but the flowsheet

will not bear an accurate resemblance of the actual plant.

The heat exchanger selected was easy to control and operate but the fluids in the heat exchanger are

exposed to a much smaller surface area which in turn affects the overall heat transfer coefficient and

therefore the capacity of the heat transfer. From an industrial perspective, a plate heat exchanger is the

most suitable. The plate heat exchanger has a major advantage over the fixed head in that the fluids

are exposed to a much larger surface area since it is equipped with metal plates in which the fluids are

spread out over.

The hydraulic pump flow rate in both stages are expected to be at approximately 600 m3/hr instead of

500 m3/hr as observed in the model. This error can be explained by the performance of the controller

that adjusts the flowrate in the system downstream of the pump. The controller is set to adjust the

flow rate until the temperature increase across the reactor is 10 ℃ but instead it adjusts it to 11 ℃.

Without the use of the controller, it was observed that the hydraulic pump flow rate and the

temperature increase matched the expected values accurately.

65

6. Conclusion Commercial simulation software CHEMCAD has been used for modelling the DNT nitration process.

The simulation model has been validated with experimental data and actual plant records. An

agreement between the simulation results and the experimental or actual plant records was obtained.

Therefore, CHEMCAD can be used to model the DNT nitration process. It proved that it could

describe chemical reactions and provide valuable output. If the characteristics of the feed streams (e.g.,

composition) are known and thermodynamic models are selected wisely, the results of the heat and

material balance will be accurate.

It was shown that employing stream reference and controllers were beneficial for estimating recycle

streams and therefore promoting faster convergence.

Concerning the material balance, it is best to set the recycle fraction of the stream splitter, rather than

the exact material flow rate of the recycle stream. Setting the flow rate prevents the convergence of

the recycle stream. Also, in the recycle loop it is beneficial to specify the outlet pressure instead of the

pressure increase. Otherwise, the pressure over the pump will be raised on every iteration.

An efficient time use was made for this project due to the fact that this project was carried out at

CEAB who in turn had engineers (with process expertise) that could help.

The model for the DNT nitration process and the project work was reasonable for both parties.

Therefore, it can now be easily updated for improvements of the DNT nitration process. For

equipment sizing, it is necessary to continue validating each process unit since this validation was only

based on an actual plant with a capacity of 50,000 kg/year. Also, in future the separation unit can be

corrected to account for mass transfer of liquid-liquid separation. Enhancements or updates to process

units can be done by Chemstations on customer’s request. It is therefore necessary to request for

updates.

66

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8. Appendices

8.1. Appendix A

71

72

73

74

8.2. Appendix B

This figure shows CHEMCAD’s utility process tools, which are used in building and running

flowsheets.

Flash command at a stream

The Flash button on a stream dialog allows for a quick flash calculation. Properties of each and every

component available in CHEMCAD database can be seen in the stream properties report, or by

hovering over the stream line with the Flowsheet Quickview feature turned on. This setup helps when

comparing the properties of the components in CHEMCAD library with literature data.

For instance, if we define the stream by specifying the composition of sulphuric acid and two variables

(T, P, or vapour fraction), that is, specify Stream 1 vapor fraction = 0.5 and P = 1 bar. Clicking Flash

will show you the temperature, density, thermal conductivity etcetera at this condition.

Feed-backward and Feed-forward Controller:

In Feed-backward mode, the controller behaves as a solver. In this example, the controller (Unit 2)

adjusts the thermal specification inside the heater (i.e., temperature out) until the vapor fraction of

stream 5 is 50% vaporized. The controller will change the adjusted variable and run until stream 5

reaches the 50% vapor target, then determine if the solution has been found.

In Feed-forward mode, the Controller unit allows a variable (i.e., split ratio) to be transferred forward

to another location on the flowsheet.

Stream Reference:

This unit can transfer stream information to another process stream.

75

Node:

Nodes are used to measure pressure and perform hydraulic balances between unit operations

on the flowsheet. They are placed upstream and downstream of pumps, and control valves

in piping systems.

76

8.3. Appendix C

Thermodynamic Model Selection- Application Tables

Hydrocarbons

K-value Method Application Enthalpy Method

Soave-Redlich-Kwong

(SRK) (1)

Pressure >1bar General

hydrocarbon

SRK

API SRK (1)

Pressure >1bar General

hydrocarbon

SRK

Peng-Robinson (PR) (1)

Pressure >10 bar Cryogenics <

-70ºC

PR

Benedict-Webb-Ruben-

Starling (BWRS) (1)

Pressure>1bar Single species

BWRS

Grayson-Streed (GS) (1)

Moderate P >7bar < 200 bar

Temperature –18C to 430C

Heavy end hydrocarbons

Lee-Kessler (LK)

ESSO (3)

Pressure < 7bar Temperature

90 - 200ºC Heavy end

hydrocarbons

Lee-Kessler (LK)

Elliott, Suresh, Donohue

(ESD) (1)

Hydrocarbon –water

Hydrocarbon-gases

SRK

77

SAFT (1)

Hydrocarbon –water

Hydrocarbon-gases

SRK

Modified SRK (MSRK) (1)

Halogenated aliphatics

SRK

Chemicals

K-value Method Application Enthalpy Method

Vapour Pressure (VAP) (3)

Ideal solutions

SRK

UNIFAC (2) P (0-4atm) T (275-475ºK)

Non-ideal - two liquid phases

Heterogeneous azeotrope

Group Contribution Predictive

LATE

Wilson (2)

Non-ideal solution with

dissolved solids Homogeneous

azeotrope

LATE

NRTL (2)

Highly non-ideal - two liquid

phases Heterogeneous

azeotrope

LATE

UNIQUAC (2)

Highly non-ideal - two liquid

phases Heterogeneous

azeotrope

LATE

78

Margules (2)

Highly non-ideal - two liquid

phases Homogeneous

azeotrope

LATE

T.K.Wilson(2)

Highly non-ideal - two liquid

phases Homogeneous

azeotrope

LATE

Hiranuma (HRNM) (2)

Highly non-ideal - two liquid

phases

LATE

Regular Solution (2)

Moderately non-ideal

(Predictive)

SRK

Van Laar (2)

Moderately non-ideal

Homogeneous azeotrope

LATE

Modified SRK (MSRK) (1)

Polar compounds in regular

solutions

SRK

Predictive SRK (PSRK) (1)

Polar compounds in non-ideal

solutions Better than UNIFAC

at high pressures

LATE

(1) Equation of State Model

(2) Activity Coefficient Model

(3) Empirical Meth

79

8.4. Appendix D

CHEMCAD flowsheet for DNT nitration process.