Reactor Design & Process Control – Hire Academic Expert

Department of Chemical and Environmental Engineering
Faculty of Engineering – University of Nottingham UK
1

FINAL CLASSIFICATION GRADE:

 

STUDENT ID
STUDENT NAME
MODULE CODE AND TITLE CHEE3048 Reactor Design & Process Control
(Modern Control Engineering)
MODULE CONVENOR Alex Conradie
ASSESSOR (if different to MC)

GROUPWORK: [ ] INDIVIDUAL: [X] IN-CLASS: [ ] (Tick as appropriate)

HAND OUT DATE 09/12/2021
SUBMISSION DATE 13/01/2022 3PM
FEEDBACK DATE

 

Accreditation Learning Outcomes
A2.3.3 Be competent in the use of numerical and computer methods, including industry standard
chemical engineering software, for solving chemical engineering problems.
A2.5.3 Understand system dynamics, be able to predict the response to changes in a dynamic
system, and be able to design and determine the characteristics and performance of measurement
and control functions.
ASSESSMENT CRITERIA
1. A technical report of no more than 1500 words, addressing the mark sheet requirements.
2. All Matlab Simulink files supporting the report and recommendation must be submitted.
ALL Assessment Criteria met (Y / N) :
ALL Assessment Criteria MUST be met to achieve a pass.

Student declaration: I certify that this assignment is my own work.
Student signature: ____________________________________
Date: ___________________________________

Department of Chemical and Environmental Engineering
Faculty of Engineering – University of Nottingham UK
2
INDIVIDUAL ASSESSMENT MARK SHEET

ASSESSOR FEEDBACK – to improve your grade in future assignments you will need to:

 

FINAL ASSIGNMENT GRADE: 1ST 2:1 2:2
REFFERAL
ASSESSOR SIGNATURE: DATE:

 

STUDENT FEEDBACK and COMMENTS:

Department of Chemical and Environmental Engineering
Faculty of Engineering – University of Nottingham UK
3
Modern Control Engineering
CHEE3048 – Course Work
You’ve started your first job with an innovative UK company, Mitsubishi Chemical UK
(
https://mitsubishichemical.co.uk/), and are very much looking forward to making a difference
during your first year of employment. MCUK has a vision to revolutionise the production of
polymethylmethacrylate, by decoupling feed supply from fossil reserves. Currently, their Alpha
Technology is reliant on fossil-derived propylene as a feedstock. MCUK is collaborating with the
Scottish Association for Marine Science (SAMS) on a project to use renewable seaweed as a
feedstock to produce a precursor to methacrylic acid, isobutyraldehyde. The next chemo-catalytic
step in the process is to oxidise the isobutyraldehyde to isobutyric acid (IBA) using air in excess in
isothermal operation.
Figure 1 – Slurry Reactor process schematic.
You’ve joined a dynamic project team of scientists and engineers, who have designed a slurry
reactor for this oxidation step as outlined in Figure 1. The CSTR reactor has two possible feed
streams, w
1 and w2, where w1 (Cb1 = 24.9 [kmol/m3]) is from a more concentrated supply than w2
(Cb2 = 0.1 [kmol/m3]) in process water. These two feed streams originate from upstream unit
operations, where their nominal concentrations are subject to concentration disturbances given the
complexity of these upstream unit operations. The suspended catalyst is retained within the reactor
and the outlet flow rate, w
o, is determined by the liquid height in the reactor. For the reactor design,
the team has settled on a reactor radius,
R, of 2.5 [m] (hard constraint). An existing SCADA control
Department of Chemical and Environmental Engineering
Faculty of Engineering – University of Nottingham UK
4
system, which can only implement PID controllers, is also available without incurring additional
capital expense.
Reaction 1 represents stoichiometry. In turn, reaction 2 represents the kinetics of the slurry reactor,
where
Cb is the isobutyraldehyde concentration in the reactor and the other model parameters are
outlined in Table 1.

2·C
4H8O + O2 2·C4H8O2 with air in excess (isothermal)
𝒓𝒃 =
𝑘
1·𝐶𝑏
(1+𝑘2·𝐶𝑏)2
(1)
(2)

Table 1 – Model parameter data for the proposed slurry reactor.

Description Value Engineering Unit
Reactor radius, R, where the working volume level, h ≤
40·R (hard constraint)
2.5 [m]
Dilute isobutyraldehyde feed concentration, Cb2 0.1 [kmol/m3]
Concentrated isobutyraldehyde feed concentration, Cb1 24.9 [kmol/m3]
Kinetic constants
Reaction Rate Constant, k1 1 [1/min]
Adsorption Equilibrium Constant, k2 1 [m3/kmol]

The process engineers in the team have formulated the below ordinary differential equations
(Equations 3 – 4) to model the two state variables of the slurry reactor (Figure 1). The state variables
are (1) the liquid level,
h, and (2) the isobutyraldehyde concentration, Cb. The available manipulated
variables are summarised in Table 2.

𝑑ℎ
𝑑𝑡 = 𝑤
1 + 𝑤2 – 0.2 · ℎ0.5
𝑑𝐶𝑏
𝑑𝑡 = (𝐶𝑏1 – 𝐶𝑏) ·
𝑤
1
ℎ + (𝐶𝑏2 – 𝐶𝑏) ·
𝑤
2
ℎ –
𝑘
1 · 𝐶𝑏
(1 + 𝑘2 · 𝐶𝑏)2
(3)
(4)

Table 2 – Available manipulated variables.

Manipulated variable ranges Engineering Unit
0 w1 10 [m/min]
0 w2 10 [m/min]

One of your team members has a PhD in optimisation and she has formulated the objective function
as in equation 5; with the Net Production Value,
P, and the Fixed Capital Investment, FCI, defined in
equation 6 and equation 7 respectively. Table 3 outlines the economic parameters.

ℎ,𝐶𝑏,𝑤𝑚𝑎𝑥 1,𝑤2 𝜙 = 𝑃 – 𝑅𝑂𝑅 · 𝐹𝐶𝐼 (5)
𝑃 = 𝑃𝑡 · (𝑐1 · 𝐶𝐼𝐵𝐴 · 19.635 · 0.2 · ℎ0.5 – 𝑐2 · 19.635 · 𝑤1 – 𝑐3 · 19.635 · 𝑤2) (6)

Department of Chemical and Environmental Engineering
Faculty of Engineering – University of Nottingham UK
5

𝐹𝐶𝐼 = 1.18 · [𝐹𝑏𝑚,𝑣 · 𝐵𝑣 · 𝑉0.724] (7)

Table 3 – Economic parameters associated with the slurry reactor unit operation.

Economic Parameters Unit Value
c1 [$/kmol] 5
c2 [$/m3] 10.8
c3 [$/m3] 200
Fbm,v [-] 4.5
Bv [$/(m3)0.724] 1836.5
Operation time, Pt [min/annum] 504,000
Annual Rate of Return, ROR [1/annum] 0.15
Fixed Capital Investment, FCI [$]
Reactor Working Volume, V [m3]
Net Production Value, P [$/annum]

You’ve been tasked to optimise the slurry reactor design and process control strategy,
demonstrated over a minimum of 500 [min] of simulated time. Additionally, MCUK’s R&D laboratory
are currently running scale-down experiments to further characterise the process outlined in Figure
1. The lab has used two initial condition at outlined in Table 4 for the state variables in their
experiments. They’d very much like you to help optimise the control response starting from both
initial conditions.
Table 4 – Initial condition for state variables and laboratory manipulated variables.

Initial condition Unit Value
Initial Condition 1
h [m] 40
Cb [kmol/m3] 0.1
w1 [m/min] 1
w2 [m/min] 1
Initial Condition 2
h [m] 40
Cb [kmol/m3] 7.0
w1 [m/min] 1
w2 [m/min] 1