Study of product distribution in parallel reaction in plug flow; DwSim.CRE Chemical engineering Reaction

1. Study of product distribution in parallel reaction
in plug flow; DwSim.
12020121 30 Patil Rushikesh
11910969 33 Parth Patle
12020195 36 Puri Ashutosh
12020172 42 Rankhamb Shubham
12020015 48 Sanap Rajkumar
Presented by : Guided by :
Prof. (SMT). Gayatri Gawande
06-04-2022
CHEMICAL REACTION ENGINEERING 1

2. INTRODUCTION
 multiple reactions can be considered to be combinations
of two primary types:
 Parallel reactions
 Series reactions
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3.  It is more convenient to deal with concentrations rather
than conversions.
 In examining product distribution the procedure is to
eliminate the time variable by dividing one rate equation
by another.
 We use two distinct analyses, one for determination of
reactor size and the other for the study of product
distribution
CONTINUED….
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4. QUALITATIVE DISCUSSION ABOUT PRODUCT DISTRIBUTION
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Consider the decomposition of A by either one of the two paths :
With corresponding rate equations
𝑟𝑅 =
ⅆ𝐶𝑅
ⅆ𝑡
= 𝑘1𝐶𝐴
𝑎1
𝑟𝑆 =
ⅆ𝐶𝑆
ⅆ𝑡
= 𝑘2𝐶𝐴
𝑎2

5.  Dividing previous equations then, we
get:
𝑟𝑅
𝑟𝑆
=
ⅆ𝐶𝑅
ⅆ𝐶𝑆
=
𝑘2
𝑘1
𝐶𝐴
𝑎1−𝑎2
• We wish this ratio to be as large as possible.
• Now concentration is the only factor in this equation
which we can adjust and control.
• Rate costant (K) and order of reaction (a) are constant
for a specific system at given temperature
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6.  We can keep CA low by :
• Using a mixed flow reactor
• Maintaining high conversions
• Increasing inerts in the feed Increasing inerts in the feed
• Decreasing the pressure in gas-phase systems
 We can keep CA high by:
• Using a batch or plug flow reactor
• Maintaining low conversions
• Removing inerts from the feed
• Increasing the pressure in gas-phase systems.
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7.  For the reactions of fist equation let us see whether the concentration of A should be kept high
or low.
 If a1 > a2, or the desired reaction is of higher order than the unwanted reaction, our last one
shows that a high reactant concentration is desirable since it increases the R/S ratio.
 As a result, a batch or plug flow reactor would favor formation of product R and would require
a minimum reactor size
 If a1 = a2, or the two reactions are of the same order,
Previous equation becomes:
𝑟𝑅
𝑟𝑆
=
ⅆ𝐶𝑅
ⅆ𝐶𝑆
=
𝑘2
𝑘1
= 𝑐𝑜𝑛𝑠𝑡𝑎𝑛𝑡
Hence, product distribution is fixed by k1/k2 alone and is unaffected by type of reactor used
 We also may control product distribution by varying k2/k1. This can be done in two ways:
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8.  We also may control product distribution by varying
k2/k1. This can be done in two ways:
• 1:By changing the temperature level of operation. If By changing the
temperature level of operation. If the activation energies of the two
reactions are different, k2/k1 can be made to vary.
• 2: By using a catalyst. One of the most important features of a
catalyst is its selectivity in depressing features of a catalyst is its
selectivity in depressing or accelerating specific reactions. This may
be a much more effective way of controlling product distribution than
any of the methods discussed so far.
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9.  We summarize our qualitative findings as follows:
• For reactions in parallel, the concentration level of reactants is the key to proper
control of product distribution. A high reactant concentration favors the reaction
of higher order, a low concentration favors the reaction of lower order, while the
concentration level has no effect on the product distribution for reactions of the
same order.
• When you have two or more reactants, combinations of high and low reactant
concentrations can be obtained by:
• Controlling the concentration of feed materials
• Having certain components in excess
• Using the correct contacting pattern of reacting fluids
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10.  Contacting patterns for various combinations of
high and low concentration of reactants in
continuous flow operations
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11. Quantitative Treatment of Product Distribution and
of Reactor Size
 If rate equations are known for the individual reactions, we can
quantitatively determine product distribution and reactor-size
requirements.
 For convenience in evaluating product distribution For
convenience in evaluating product distribution we introduce two
terms, φ (instantaneous fractional yield) and Φ (overall fractional yield).
 Consider the decomposition of reactant A, and let φ be the
fraction of A disappearing at any instant which is transformed into
desired product R .
 We call this the instantaneous fractional yield of R.
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12. Thus at any CA,
φ=
𝑚𝑜𝑙𝑒𝑠 𝑅 𝑓𝑜𝑟𝑚𝑒𝑑
𝑚𝑜𝑙𝑒𝑠 𝐴 𝑟𝑒𝑎𝑐𝑡𝑒𝑑
=
ⅆ𝐶𝑅
− ⅆ𝐶𝐴
• For any particular set of reactions and rate equations φ is a
function of CA
• Since CA in general varies through the reactor, φ will also
change with position in the reactor
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.

13. • So let us define Φ as the fraction of all the reacted A that has been
converted into R, and let us call this the overall fractional yield of R.
• The overall fractional yield is then the mean of the instantaneous
fractional yields at all points within the reactor; thus we may write
• φ=
𝑎𝑙𝑙 𝑅 𝑓𝑜𝑟𝑚𝑒𝑑
𝑎𝑙𝑙 𝐴 𝑟𝑒𝑎𝑐𝑡𝑒𝑑
=
𝐶𝑅𝑓
𝐶𝐴𝑂−𝐶𝐴𝑓
=
𝐶𝑅𝑓
−Δ𝐶𝐴
= φ 𝑖𝑛 𝑟𝑒𝑎𝑐𝑡𝑜𝑟
• It is the overall fractional yield that really concerns us for it represents
the product distribution at the reactor outlet.
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14. overall fractional yield of PFR
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𝜙𝑃 =
−1
𝐶𝐴0−𝐶𝐴𝑓 𝐶𝐴0
𝐶𝐴𝑓
φ ⅆ𝐶𝐴
=
1
Δ𝐶𝐴 𝐶𝐴0
𝐶𝐴𝑓
φ ⅆ𝐶𝐴

15.  Simulation of PFR
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16.  Effect of temperature on conversion of
the reaction
Temperature Conversion
150 88.7606
175 87.0713
200 85.29
225 83.55
250 81.84
275 80.16
300 78.53
325 76.5
350 75.39
375 73.84
400 72.44
0
10
20
30
40
50
60
70
80
90
100
0 100 200 300 400 500
conversion
%
temperature ℃
Temperature vs Conversion
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17.  Effect of temperature on Residence
time
Temperature
Residence time in
Hr
150 2.77597
175 2.61021
200 2.46408
225 2.33414
250 2.21774
275 2.1128
300 2.01765
325 1.93094
350 1.85157
375 1.77862
400 1.71133
0
0.5
1
1.5
2
2.5
3
0 100 200 300 400 500
Residence
time
in
hr
temperature ℃
Temp Vs Residence time
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18. CONCLUSION
• Model significant reaction biogas into bio gasoline was successfully run
in DwSim software.
• Reaction of biogas into biogas line series follows the pattern of first-order
reaction value of the reaction rate constants for the two reactions are
relatively similar.
• We find maximum conversion up to 75% at 350 ℃ and residence time of
1.85157 hour.
• The reaction conversion is increases as we decrease the temperature up to
certain extent. The residence time is increases for lower temperature.
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19. REFERENCE
1. Chumaidi, Achmad & Murdani, Anggit & Hendrawati, Nanik. (2015). Parallel Reaction
Kinetic Modelling Of Biogas To Biomethanol With Zno/Sio 2 Nanoparticles.
International Journal of Engineering Research and Development. 11. 2278-800.
2. Levenspiel, Octave. Chemical Reaction Engineering. Design for Parallel Reactions.
New York: Wiley, 1999.
3. Buren (2009) , Catalytic conversion of Methanol to Gasoline Range Hydrocarbons,
Catalysis Today. 96 (2004) 155-160.
4. Dube and Carlson (2011) , Transformation of Methanol to Gasoline Range
Hydrocarbons using copper oxide impregnated HZSM-5 Catalysts. Korean J. Chem.
Engg. 22 (3) (2005) 353-357.
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20. 06-04-2022
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