Program for North American Mobility In Higher Education

1
NAMP
Program for North American Mobility In Higher
Education
Module 9
Introduction to Steady State Simulation
PIECE
Introducing Process integration for Environmental
Control in Engineering Curricula
2
PIECE
Process integration for Environmental Control in
Engineering Curricula
NAMP
Program for North American Mobility in Higher
Education
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Module 9
This module was created by
Amy Westgate
From
Host University
Richard Ezike
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Project Summary

• Objectives
• Create web-based modules to assist universities
  to address the introduction to Process
  Integration into engineering curricula
• Make these modules widely available in each of
  the participating countries
• Participating institutions
• Six universities in three countries (Canada,
  Mexico and the USA)
• Two research institutes in different industry
  sectors petroleum (Mexico) and pulp and paper
  (Canada)
• Each of the six universities has sponsored 7
  exchange students during the period of the grant
  subsidised in part by each of the three
  countries governments

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Structure of Module 9

• What is the structure of this module?
• All modules are divided into 3 tiers, each with a
  specific goal
• Tier I Background Information
• Tier II Case Study Applications
• Tier III Open-Ended Design Problem
• These tiers are intended to be completed in that
  particular order. In the first tier, students are
  quizzed at various points to measure their degree
  of understanding, before proceeding to the next
  two tiers.

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Purpose of Module 9

• What is the purpose of this module?
• It is the intent of this module to cover the
  basic aspects of Steady State Simulation. It is
  identified as a pre-requisite for other modules
  related to the learning of Steady State
  Simulation.
• This module is intended for students familiar
  with basic mass and energy balances and may have
  had some training with thermodynamics and
  transport processes.

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Tier IBackground Information
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• Statement of Intent
• Review basic chemical engineering concepts
  employed in steady state simulation
• Understand the purpose of steady-state simulation
• Learn how to develop models of processes in
  steady-state
• Discuss problem solving techniques

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• Steady State Process
• We can use steady-state processes to determine
  the optimum operation conditions for a process
  that can be limited by safety, equipment
  performance, and product quality constraints.
• Concentration does not change with respect to
• time
• Accumulation term in mass balance set to zero
• Input Generation Output Consumption 0

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• Three types of processes
• Batch
  Continuous
• Semi-batch

• A process where inputs and outputs flow
  continuously through duration of process.

• A process where a set amount of input enters a
  process, where it is removed from the process at
  a later time.

• Neither batch or continuous, may be combination
  of both.

In steady-state processes, we will be looking at
continuous processes.
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• Batch Example
• Ammonia is produced from nitrogen and hydrogen.
  At time t t0, nitrogen and hydrogen are added
  to the reactor. No ammonia leaves the reactor
  between t t0 and t tf. At tf, nf moles of
  ammonia are released.

H2 N2
NH3
t to
t tf
12

• Semibatch Example
• Helium is pressurized in large tanks for storage.
  When the tank valve is open, the gas diffuses out
  due to the difference in pressure.

13

• Continuous Example
• Pump a methanol/water mixture into a distillation
  column and withdraw the more volatile component
  (methanol) from the top of the column and the
  less volatile component (water) from the bottom
  of the column.

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Quiz 1

• Classify the following processes as batch,
  continuous, or semibatch.
• A balloon is filled with air at a steady rate of
  2 m3/min.
• Pump a mixture of liquids into a distillation
  column at a constant rate and steadily withdraw
  product streams from the top and bottom.
• Slowly blend several liquids in a tank from which
  nothing is being withdrawn.

15

• Block Diagrams
• When solving a problem, it is helpful to develop
  a block diagram, such as the one below, that
  defines what the process looks like as well as to
  indicate all information about the process such
  as flow rates and species compositions.

Process
Carbon (C) Air (79 N2, 21 O2)
Separator
Reactor
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Degree Of Freedom Analysis

• Analysis done to determine if there is enough
  information to solve a given problem.
• Draw and completely label a flowchart
• Count the unknown variables, then the independent
  equations relating them,
• Subtract the number of equations from the number
  of variables. This gives ndf, or the number of
  degrees of freedom in the process.

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Degree of Freedom Analysis

• If ndf 0 there are n independent equations in n
  unknowns and the problem can be solved
• If ndf gt0, there are more unknowns than
  independent equations relating them, and at least
  ndf additional variable values must be specified.
• If ndf lt0, there are more independent equations
  than unknowns. The flowchart is incompletely
  labeled or inconsistent and redundant relations
  exist.

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Mass (Material) Balance A mass (material)
balance is an essential calculation that accounts
for the mass that enters and leaves a particular
process.
Accumulation of mass Mass flow rate in Mass
flow rate out
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Mass (Material) Balance (continued) In the case
of a steady-state process we are able to set the
accumulation term to zero since it is a time
dependent term. Since steady-state does not
depend on time as it is constant, we are able to
eliminate this term Mass Flow Rate In Mass
Flow Rate Out Material Balance Procedure
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• First Law of Thermodynamics (Energy Balance) for
  a Steady State Open System

The net rate at which energy is transferred to
system as heat and/or shaft work equals the
difference between rates at which (enthalpy
kinetic energy potential energy) is transported
into and out of the system
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Quiz 2

1. Explain the Degree of Freedom analysis.
2. What term goes to zero in a steady-state process?
3. Is a continuous process closed or open? How about
   a batch process?

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• Heat Transfer
• Also classified as energy transfer
• Three types of heat transfer modes
• Conduction
• Convection
• Radiation

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• Conduction
• Accomplished in two ways
• Molecular interaction
• Free electrons
• Conduction equation called Fouriers Law
• qy heat transfer area in y direction (W)
• A area normal to direction flow (m2)
• dT/dy temperature gradient (oC/m)
• k thermal conductivity (W/moC)

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• Convection
• Accomplished in two ways
• Natural convection
• Forced convection
• Convection equation called Newtons Law
• qy rate of convective heat transfer (W)
• A area normal to direction flow (m2)
• ?T temperature gradient (oC)
• h convective heat transfer coefficient (W/m2 oC)

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Radiation (Thermal)

• Exhibits same optical properties as optical light
• May be absorbed, reflected, or transmitted

Total radiation for unit area of opaque body of
area A1, emissivity e1, and absolute temperature
T1, and a universal constant s
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Radiation Between Surfaces

• Simplest type occurs where each surface can see
  only the other and where both surfaces are black
• Energy emitted by first plane is sT14 the
  second plane emits sT24
• if T1 gt T2, then net loss energy per unit area
  by first plane and net gain by second are sT14-
  sT24, or s(T14-T24)

Cold surface
Note this is only in ideal cases no surface is
exactly black, and emissivities must be considered
Hot surface
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• Mass Transfer
• The transport of one constituent from a region of
  higher concentration to a region of lower
  concentration
• Molecular mass transfer
• Random molecular motion in quiescent fluid
• Convective mass transfer
• From a surface into a moving fluid or vice-versa

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• Flux
• - (overall density)(diffusion
  coefficient)(concentration gradient)
• Fick rate equation (restricted to
  isothermal/isobaric systems)
• de Groot equation is more general

Units JA mol A/m2s CA- mol A/m3 DAB- m2/s
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• Molar flux of species A in binary system (A B)

c concentration DAB diffusivity of species A
in B change of molar species in y with
respect to a specified direction NA, NB molar
fluxes of components
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Quiz 3

1. What are two ways in which conduction occurs?
2. Define natural and forced convection.
3. What is the restriction to the use of Ficks Law?

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• Modeling
• What is Modeling?
• Steady-State vs. Dynamic Modeling
• Empirical vs. Mechanistic Modeling
• Derivation of a Steady State Model
• Modeling and Process Design Implications

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What is a Model?

• A model is an depiction of a process operation
• used to design, change, improve or control a
  process.
• Uses of Model
• Equipment Design, Size and Selection
• Comparison of Different Process Configurations
• Evaluation of Process Performance Against
  Limitations
• Optimization

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• Models vary by
• Phenomena represented
• Energy, phase changes
• Level of details
• Assumptions (perfect mixing, heat loss)
• Inputs required
• Functions performed (satisfaction of constraints,
  optimization)
• Outputs generated

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• Requirements of a good model
• Accuracy the model should be close to the target
  description.
• Validity model must have a solid foundation and
  ability to be easily justified.
• Complexity the level of the model should be
  considered and easy to understand.
• Computational efficiency models should be
  calculable using reasonable amounts of time and
  computing resources.

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Time-based Modeling
Steady State
Dynamic
Model
Empirical
Mechanistic
Hybrid
Level of Knowledge-based Modeling
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Steady State
Dynamic

Balance at equilibrium condition Time dependent results
Equilibrium results for all unit operations Equilibrium conditions not assumed for all units
Equipment sizes not needed Equipment sizes needed
Amount of information required small to medium Amount of information required medium to large
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Steady State Example
Continuous Stirred Tank Reactor (CSTR)
Concentration profile at one point in reactor
does not change with time
Ca
t
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Dynamic Example
Batch Reactor
Concentration profile at one point in reactor
does change with time
ca
t
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• Empirical Modeling
• Definition
• a model that is based on data whether it has been
  collected from a process or some other source.
• Key Notes
• Derived from observation
• Often simple
• May or may not have theoretical foundation
• Valid only within range of observation

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• Procedure Empirical Modeling
• Obtain data from process you wish to model.
• Temperature, pressure, flow, etc
• Perform appropriate statistical analysis and
  develop accurate correlations from data.
• Develop mathematical equations to accurately
  represent the data and the correlations found in
  step 2, and determine which equations are useful
  in the development of the model.
• Check for correctness in your analysis and
  equations, and determine if the model is
  satisfactory.
• Statistical Analysis with Excel

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• Example
• The figure below depicts a heat exchanger. Heat
  exchangers function as a medium to transfer
  energy (in the form of heat) from a hotter stream
  to a cooler stream. Lets say we have a hot
  stream of fluid coming into the exchanger at Th1,
  leaves at Th2 and a cool stream coming in at Tc1
  and leaving at Tc2. If the physical properties of
  the fluids are the same, then the temperature
  difference describes the amount of energy
  transferred.

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• We do not know Tc2, but we can take various
  measurements of Th1, Th2 and Tc1 to find Tc2 .
  Using certain statistical procedures, it can be
  determined that Tc2 is related to the other three
  temperatures by this equation
• Tc2 Tc1 a(Th2-Th1)
• We have empirically determined a value for a, but
  only for the specific fluids and conditions
  tested.

• If we knew, say, the mass flow rates and heat
  capacities of the two fluids, we can use them to
  determine the mechanistic model that relates the
  four temperatures for any combination of two
  fluids.

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• Mechanistic Modeling
• Definition
• a model that is derived from fundamental physical
  laws or basic principles
• Key Notes
• Model construction time-consuming and costly
• Most reliable, but often not enough data available

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• Procedure Mechanistic Modeling
• Know physical and chemical properties of the
  process.
• Determine the appropriate process model using
  mass and/or heat balance.
• Determine appropriate model run conditions and
  parameters
• Complete runs and use output data to compare
  against the predicted model results
• Develop an acceptable conclusion for the model.
  Should the conclusion not be acceptable,
  re-examine the assumptions, process and the
  physical and chemical properties made in Step 1.
  Make appropriate modifications and repeat Steps
  2-4.

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• Let us go back to the heat exchanger. Now we know
  that the empiricism a that we determined earlier
  is related to the mass flow and heat capacity of
  the two fluids. This knowledge allows us to model
  a heat exchanger for any two fluids. The model is
  determined to be

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Steady state model derivation

• 1. Define Goals.
• a) Specific design decisions.
• b) Numerical values.
• c) Functional relationships.
• d) Required accuracy.

2. Prepare information. a) Sketch
process. b) Identify variables of
interest. c) State assumptions and data.
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Steady state model derivation
3. Formulate model a) Conservation
balances. b) Constitutive equations. c) Rationaliz
e (combine equations and collect terms). d) Check
degrees of freedom.

• 4. Determine solution
• a) Analytical
• b) Numerical

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Steady state model derivation

• 5. Analyze results
• a) Check results for correctness
• Accuracy of numerical/analytical methods
• Plot solution
• Relate results to data and assumptions
• Answer what if questions
• Compare with experimental results

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Process insights resulting from modeling

1. Identification If we know the input (I) and
   output (O) parameters, we can determine the
   structure (R) of the model.

I
O
R?
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Process insights resulting from modeling
2. Simulation If we know the structure of the
model, we can simulate what the output of the
process will be for a given input.
I
O?
R
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Process insights resulting from modeling
3. Control/Optimization If we know the desired
output (O) and the structure (R) of the model, we
can determine what the input (I) should be to
optimize the process.
I?
O
R
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Quiz 4

1. What are some uses of modeling?
2. Name and explain three requirements of a good
   model.
3. What distinguishes a steady-state model and a
   dynamic model?
4. Review the procedures for developing a
   mechanistic and empirical model. What are some
   differences between the two procedures?
5. Discuss the control/optimization insight of
   modeling.

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• Solving Problems
• Analytical Methods
• Process Design
• Methods
• Spreadsheets
• Simulation Software
• Solution Determination

54

• Curve fitting
• Try to find the best fit of a curve through the
  data such that the distribution of the data
  points on either side of the line is equal
• Possible errors
• Measurement error
• Precision error
• Systematic error
• Calculation error
• Error propagation
• Curve Fitting Example

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• Least Squares
• The best curve through the data is the one that
  minimizes the sum of the squares of the residuals
  (differences between predicted and experimental
  values)
• Least Squares Method

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Process Design
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Process design

• The design of chemical products begins with the
  identification and creation of potential
  opportunities to satisfy societal needs and to
  generate profit. The scope of chemical product is
  extremely broad. They can be roughly classified
  as
• Basic chemical products.
• Industrial products.
• Consumer products.

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Process design
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Motivation for Process Design

1. Desires of customers for chemicals with improved
   properties for many applications.
2. Discovery of a new inexpensive source of a raw
   material with comparable physical and chemical
   properties to the old source.
3. New markets are discovered.

60
Steps in a Process Design

• Process Design Questions to Answer
• Is the chemical structure known?
• Is a process required to produce the chemicals?
• Is the gross profit favorable?
• Is the process still promising after further
  elaboration?
• Is the process and/or product feasible?

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Steps in a Process Design

1. Process Design Steps

• Develop objective(s).
• Find inputs that have the desired properties and
  performance.
• Create process.
• Develop a base case for which to conduct initial
  testing on process.
• (does it stay stable at steady state?)
• Improve/maintain process

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Stability of the process

• When a process is disturbed from an initial
  steady state, it will generally respond in one of
  3 ways.
• Proceed to a steady state and remain there.

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Stability of the process

1. Fail to attain to a steady state condition
   because its output grows indefinitely. The system
   is unstable.

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Stability of the process

1. Fail to attain a steady state condition because
   the output of the process oscillates indefinitely
   with a constant amplitude. The system is at the
   limit of stability.

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Quiz 5

1. What are some errors that may arise when
   attempting to fit a curve?
2. What are the three products developed from
   process design? Provide an example of each
   product.
3. What happens to an unstable system over time?

66

• Spreadsheet
• A computer program (Microsoft Excel) used to
  store and calculate information in a structured
  array of data cells. By defining relationships
  between information in cells, a user can see the
  effects of certain data changes on other data in
  other parts of the spreadsheet.
• Provides an easy, efficient method for solving
  sets of equations and other forms of data that
  are not too numerous but complex enough that it
  would be difficult to solve by hand.

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• Columns are designated by letters, rows by numbers

http//www.instrunet.com/images/Direct20To20Exce
l20Spreadsheet.png
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Goalseek

• Under Tools Menu
• want to know input value formula needs to
  determine result
• Excel varies value in cell specified until
  dependent formula returns value you want

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• Spreadsheet Drawbacks
• Entering the equations yourself could lead to
  false answers as you can make a mistake. Mistakes
  can become unmanageable very quickly causing
  debugging to be difficult.
• Excel can handle large amounts of data but there
  is a point where Excel may have difficulty in
  solving a system of equations.

70

• Simulation
• Predicts behavior of a process by solving
  mathematical relationships that describe the
  behavior of the process components.
• Involves performance of experiments with a
  process model

71

• Simulation Software Why use it?
• economical way for engineers to construct or
  modify a process before doing a test in reality.
• Can determine optimum operating conditions
• Quantify equipment, raw materials required with
  accuracy
• Can discover process problems
• Make accurate changes in process without
  sacrificing money or safety
• Determine composition of streams and simplify
  complex unit operations

72

• Simulation Software What does it allow?
• Manipulation and comparison of previous data as
  well as for research
• Manipulation of a process until a desired target
  is reached
• Allows complex processes to be easily calculated
• Can easily change conditions and see how the
  output is changed and the equipment behaves

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• Simulation Issues and Considerations
• Built-in assumptions in programs must be taken
  into account and validated
• Can make mistakes in calculations do mass
  balances over process as a check over
• Number of variables involved
• Physical properties of streams
• Size of process being simulated

74
Process Flowsheet (Block Diagram)

• A process flowsheet is a collection of icons to
  represent process units and arrows to represent
  the flow of materials to and from the units.

Fresh feed
steam
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Calculation Order

• In most process simulators, the units are
  computed one at a time. The calculation order is
  automatically computed to be consistent with the
  flow of information in the simulation flowsheet,
  where the information flow depends on the
  specifications for the chemical process.

1
2
3
4
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Recycle Flows

• A simulation flowsheet usually contains
  information recycle loops. That is, there are
  variables that are not known which prevent the
  equations in the process model from being solved
  completely. These variables are recycled back to
  the initial calculation point.

1
2
3
4
For these processes, a solution technique is
needed to solve the equations for all the units
in the recycle loop.
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• Iteration
• Initial guess is taken at the input and a
  solution is determined for the system
• Second, a more educated guess is made and the
  system is solved based on initial solution
• Iterations continue until solution converges to
  one value

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Convergence

• Is the process to compare the guessed value with
  the computed value until a value is found within
  the tolerance range.

Guessed value
Yes
No
Guessed value calculated value lt Tolerance
Convergence
When the criterion is achieved, the solution is
found and no more iteration needs to be done.
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Process synthesis methodologies

• Total account of an explicit process is the most
  obvious. Here we generate and evaluate every
  alternative design. We locate the better
  alternative by directly comparing the
  evaluations.
• Evolution of design follow from the generation
  of a good base case design. Designers can then
  make many small changes, a few at a time, to
  improve the design incrementally.
• Structured Decision Making following a plan that
  contains all the alternatives.
• Design to target we design and specify unit
  operations to operate according to the desired
  target operation of the process.

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• Solution Determination
• Sequential Solution
• Work backwards from one point in a sequential
  order solving one equation at a time
• Iterative Method
• Simultaneous Solution
• Have to solve multiple equations with multiple
  variables all at same time
• Generally requires simulation software

81
Some advice when running a simulation

• 1. Talk with trained professionals (chemists,
  vendors, other engineers in the field).
• 2. Beware of using estimated parameters and
  interaction parameters when screening process
  alternatives.
• 3. Go see the plant. Plant personnel are usually
  helpful. Their insight and your knowledge of
  modeling can help solve problems efficiently.

82
With a simulator, one day of process operation
can be simulated in just seconds, and make as
many changes as you want.
Change in Reactor Properties
Change composition in feed
Change in Column Properties
83
Commercial Simulation Software Packages

• There are many of them, some of them are
• Excel (spreadsheet) Excel Tutorial
• Matlab MATLAB homepage
• Fortran and C (programming languages)
• Aspen AspenTech
• HYSYS HYSYS
• WinGEMS WinGEMS
• SuperPro Designer SuperPro Designer
• IDEAS (Simons)

84
Final Quiz

1. What is a drawback of using spreadsheets?
2. What are two functions that simulation allows
   for?
3. How are units calculated within a simulation
   process?
4. Explain how iteration works and why you should
   use it.
5. You are an engineer who has been tabbed to design
   a new chemical process for a company. What are
   some steps you can take to help you in your
   design?

85
Tier IIWorked Examples
86

• Statement of Intent
• Review basic chemical engineering concepts
  employed in steady state simulation through
  examples
• Understand how to develop a steady-state
  simulation problem in Excel

87
First Example A Single Effect Evaporator (to be
done in Excel)
88
Evaporation
Function is to concentrate solution

• What affects evaporation?
• Rate at which heat is transferred to the liquid
• Quantity of heat required to evaporate mass of
  water
• Maximum allowable temperature of liquid
• Pressure which evaporation takes place

89
Single Effect Vertical Evaporator

• Three functional sections
• Heat exchanger
• Evaporation section
• liquid boils and evaporates
• Separator
• vapor leaves liquid and passes off to other
  equipment

Three sections contained in a vertical cylinder
90

• In the heat exchanger section (calandria), steam
  condenses in the outer jacket
• Liquid being evaporated boils on inside of the
  tubes and in the space above the upper tube stack
• As evaporation proceeds, the remaining liquors
  become more concentrated

91
Diagram of Single Effect Evaporator
Vapor V
Tv, yv, Hv, ?V
Tf, xf, hf, ?f
U J/m2 s oC
Feed F
P kPa
Ts, Hs, ?s
A ? m2
Condensate S
Ts, hs, ?s
Steam S
Concentrated liquid L
TL, xL, hL, ?L
92
Material and Heat Balances
q UA?T ?T Ts TL Heat given off by
vapor ? Hs hs ?FhF ?sHs ?LhL ?VHV
?shs ?FhF ?s? ?LhL ?VHV q ?s(Hs-hs)
?s? ?s? ideal heat transferred in evaporator
?F ?L ?V ?FxF ?LxL ?VyV
93
Finding the Latent Heat of Evaporation of
Solution and the Enthalpies

• Using the temperature of the boiling solution TL,
  the latent heat of evaporation can be found
• The heat capacities of the liquid feed (CpF) and
  product (CpL) are used to calculate the
  enthalpies of the solution.

94
Property Effects on the Evaporator

• Feed Temperature
• Large effect
• Preheating can reduce heat transfer area
  requirements
• Pressure
• Reduction
• Reduction in boiling point of solution
• Increased temperature gradient
• Lower heating surface area requirements
• Effect of Steam Pressure
• Increased temperature gradient when higher
  pressure steam is used.

95
Boiling-Point Rise of Solutions

• Increase in boiling point over that of water is
  known as the boiling point elevation (BPE) of
  solution
• BPE is found using Duhrings Rule
• Boiling point of a given solution is a linear
  function of the boiling point of pure water at
  the same pressure

96
Duhring lines (sodium chloride)
http//www.nzifst.org.nz/unitoperations/evaporatio
n4.htm
97
Problem Statement (McCabe 16.1 modified)
A single-effect evaporator is used to concentrate
9070 kg/h of a 5 solution of sodium chloride to
20 solids. The gauge pressure of the steam is
1.37 atm the absolute pressure in the vapor
space is 100 mm Hg. The overall heat transfer
coefficient is estimated to be 1400 W/m2 oC. The
feed temperature is 0oC. Calculate the amount of
steam consumed, the economy, and required heating
surface.
First Example Excel Spreadsheet
98
1. Draw Diagram and Label Streams
Vapor V
9070 kg/h feed, 0oC, 5 solids, hF
Tv, 0 solids, Hv, ?v
U 1400 W/m2 oC
Feed F
P 100 mm Hg
Ts, Hs, 1.37 atm gauge, ?s
q?
Condensate S
Ts, hs, ?s
A?
Steam S
TL, 20 solids, hL, ?L
Liquor L
99
2. Perform Mass Balances

• ?F ?L ?V
• 9070 kg/h ?L kg/h ?V kg/h
• ?FxF ?LxL ?VyV (note that yv is zero
  because only vapor is present, no solids)
• 0.05 9070 kg/h 0.2 ?L kg/h 0
• Can solve for ?v and ?L
• ?V 6802.5 kg/h, ?L 2267.5 kg/h

100
3. Perform Heat Balances to find the Economy
The economy is defined as the mass of water
evaporated per mass of steam supplied.
?FhF ?SHS ?LhL ?VHV ?ShS ?FhF ?S?
?LhL ?VHV q ?S(HS- hS) ?S?
101
Needed Data

• Boiling point of water at 100 mm Hg 51oC (from
  steam tables)
• www.nzifst.org.nz/unitoperations/appendix8.htm
• Boiling point of solution 88oC (from Duhring
  lines)
• http//www.nzifst.org.nz/unitoperations/evaporatio
  n4.htm
• Boiling point elevation 88 51 37oC
• Enthalpy of vapor leaving evaporator (enthalpy
  of superheated vapor at 88oC and 100 mm Hg .133
  bar) 2664 kJ/kg (FR, p.650) also called the
  latent heat of evaporation
• Heat of vaporization of steam (Hs-hs ? ) at
  1.37 atm gauge 20 lbf/in2 939 Btu/lb 2182
  kJ/kg (McCabe, App.7, p.1073)

102
Finding the enthalpy of the feed
yNaCl0.05 ywater0.95 Cp,water4.18 kJ/kgoC
Cp,NaCl0.85 kJ/kgoC

• Find the heat capacity of the liquid feed
• feed is 5 sodium chloride, 95 water

(Cp)F .050.85 .954.18 4.01 kJ/kgoC
2. Calculate Enthalpy (neglecting heats of
dilution)
hF 4.01 kJ/kgoC (0 - 0 oC) 0 kJ/kg
103
Finding the enthalpy of the liquor
yNaCl0.20 ywater0.80 Cp,water4.18
kJ/kgoC Cp,NaCl0.85 kJ/kgoC

• Find the heat capacity of the liquor
• feed is 20 sodium chloride, 80 water

Cp,L .200.85 .804.18 3.51 kJ/kgoC
2. Calculate Enthalpy (neglecting heats of
dilution)
hL 3.51 kJ/kgoC (88-0 oC) 309 kJ/kg
104
Heat Balances
?LhL ?VHV - ?FhF ?SHS - ?ShS ?S(HS- hS)
?S? ? (HS-hS) 2182 kJ/kg (2267.5 kg/h
309.23 kJ/kg) (6802.5 kg/h 2664 kJ/kg) (0)
?S (HS-hS) q ?S (2182 kJ/kg)
?s8626.5 kg/h
q 8626.5 kg/h2182 kJ/kg 1.88x107 kJ/h
5228621 W 5.23 MW
105
Find the Economy
?V/?S
106
4. Calculate Required Heating Surface
Condensing temperature of steam (1.37 atm gauge
126.1oC
q UA?T A q/U?T
107
Click on the Hyperlink and click on the Final
Solution tab to see the final answer for the
system.
First Example Final Solution
108
Second Example Simulation of Cyclic Process
(Felder and Rousseau, Example 10.2-3, pp.
516-519) (to be done in Excel)
109
Problem Statement
The gas-phase dehydrogenation of isobutane (A)
to isobutene (B) is carried out in a continuous
reactor. A stream of pure isobutane (the fresh
feed to the process) is mixed adiabatically with
a recycle stream containing 90 mole isobutane
and the balance isobutene, and the combined
stream goes to a catalytic reactor. The effluent
from this process goes through a multistage
separation process one product stream containing
all the hydrogen (C) and 10 of the isobutane
leaving the reactor as well as some isobutene is
sent to another part of the plant for additional
processing, and the other product stream is the
recycle to the reactor. The conversion of
isobutane in the reactor is 35. Assume a fresh
feed of 100 mol isobutane. Simulate the process
using a spreadsheet to find the desired process
variables.
110
Diagram of Process
Second Example Cyclic Process
111
Notes

• A will denote isobutane, B denotes isobutene, C
  denotes hydrogen
• All streams are gases, is the required rate
  of heat transfer to the reactor and is the
  net rate of heat transfer to the separation
  process
• Specific enthalpies are for the gaseous species
  at the stream temperatures relative to 25oC
• - Heats of formation are taken from Table B.1,
  and heat capacity formulas are taken from Table
  B.2 in Felder and Rousseau

112
1. Perform Degree of Freedom Analysis
113
Review Degrees of Freedom

1. Draw and completely label a flowchart
2. Count the unknown variables, then the independent
   equations relating them,
3. Subtract the number of equations from the number
   of variables. This gives ndf, or the number of
   degrees of freedom in the process.

114
Degree of Freedom Analysis

• If ndf 0 there are n independent equations in n
  unknowns and the problem can be solved
• If ndf gt0, there are more unknowns than
  independent equations relating them, and at least
  ndf additional variable values must be specified.
• If ndf lt0, there are more independent equations
  than unknowns. The flowchart is incompletely
  labeled or inconsistent and redundant relations
  exist.

115
Degree of Freedom Analysis Mixing Point
4 unknowns (?A1, ?B1, ?4,T1) - 3 balances (2
material balances, 1 energy balance) 1 local
degree of freedom
116
Degree of Freedom Analysis Reactor

• 7 unknowns (?A1, ?B1, ?A2, ?B2, ?C2, T1, )
• 4 balances (3 molecular species balances, 1
  energy balance)
• 1 additional relation (35 conversion of
  isobutane)
• 1 independent chemical reaction
• 3 local degrees of freedom

117
Degree of Freedom Analysis Separator

• 8 unknowns (?A2, ?B2, ?C2, ?A3, ?B3, ?C3, ?4,
  )
• 4 balances (3 material balances, 1 energy
  balance)
• - 1 additional relation (isobutane split)
• 3 local degrees of freedom

118
Net Degree of Freedom Analysis Overall Process
7 local degrees of freedoms (133) - 7 ties
(?A1, ?B1, ?A2, ?B2, ?C2, ?4, and T1 were counted
twice) 0 net degrees of freedom
The problem can be solved for all labeled
variables.
119
2. Equation Based Solution Process
120
Tearing the Cycle

• Cant solve system in a unit-to-unit manner
  without trial and error
• tear between two units
• Purpose is to have the least number of variables
  that have to be determined by trial and error
• We tear between separation process and mixing
  unit
• - Only have to determine ?4 by trial and error.

121
Solution Process

• Assume value of recycle flow rate (?4A 100
  mol/s)
• Assume mixing point outlet temperature (T1
  50oC)
• Vary ?4A until calculated recycle flow rate
  (?4C) equals assumed value in ?4A
• - Will be done by driving (?4A - ?4C) using
  Goalseek
• Mixing point temperature (T1) will be varied to
  determine the value that drives ??mix to zero
  (remember, the mixer is adiabatic)

122
Known Values
XA 0.35 (fractional conversion of A) 100 mol/s
(basis of calculation) Feed temperature
20oC Reactor Effluent Temperature 90oC Product
Stream Temperature 30oC Guess for recycle
stream flow rate (?A4) 100 mol/s Mole fraction
of A in recycle stream 0.9 Mole fraction of B
in recycle stream 0.1 Temperature of recycle
stream 85oC Initial guess for combined stream
temperature 50oC
123
Mass Balances (based on initial guesses)
?A1 100 mol/s feed (100 mol/s recycle 0.9
mol fraction 190 mol/s) ?B1 100 mol/s recycle
0.1 mol fraction 10 mol/s ?A2 ?A1 (1-XA)
123.5 mol/s ?B2 ?B1 (?A1XA) 76.5 mol/s ?C2
?A1 XA 66.5 mol/s ?A3 0.01 ?A2 1.24
mol/s ?C4 (?A2- ?A3)/0.9 mol fraction 135.85
mol/s ?B3 ?B2 (0.1 mol fraction ?C4 ) 62.9
mol/s ?C3 ?C2 66.5 mol/s
124
Calculation of Specific Enthalpies (Tables B.1
and B.2, Felder and Rousseau)
- (heats of formation) are located in Table B.1
of FR
A (isobutane g) -134.5 kJ/mol B (isobutene
g) 1.17 kJ/mol C (hydrogen g) 0 kJ/mol
125
Calculation of Specific Enthalpies (Tables B.1
and B.2, Felder and Rousseau)
- heat capacity of component i (kJ/moloC)
a bT cT-2 dT-3 , where T is temperature in
oC
Chemicals A 103 B 105 C 108 D 1012
isobutane 89.46 30.13 -18.91 49.87
isobutene 82.88 25.64 -17.27 50.50
hydrogen 28.84 0.00765 0.3288 -0.8698
126
Heat Balances (based on initial guesses)
??mix ?A1HA1 ?B1HB1 100 mol/sHA0 -
(?A40.9 mol A/mol HA4) - (?A40.1 mol
fractionHB4) -78.64 kJ/mol
?A2HA2 ?B2HB2 ?C2HC2 - ?A1HA1
?B1HB1 9980.4 kJ/s
?A3HA3 ?B3HB3 ?C3HC3(?A40.900 mol
fractionHA4)(?B40.100 mol fractionHB4)
?A2HA2 - ?B2HB2 - ?C2HC2 -568.4 kJ/s
127
Click on the Hyperlink and click on the Final
Solution tab to see the final answer for the
system.
Second Example Final Solution
128
Tier IIIOpen-ended problem

• Approach to open-ended problem
• Case Study.

129

• Statement of Intent
• Learn how to approach open-ended design problems
• Solve a problem on your own

130
How to approach openended problems

• State the problem clearly, including goals,
  constraints, and data requirements.
• Define the trade-offs necessary.
• Define the criteria for a valid solution.
• Develop a set of cases to simulate possible
  solutions.
• Perform the simulation and evaluate results
  against solution criteria.
• Evaluate solutions against environmental, safety
  and financial considerations.

131
The Use of Limestone Slurry Scrubbing to Remove
Sulfur Dioxide from Power Plant Flue Gases
Prepared by Ronald W. Rousseau and Jack Winnick,
Georgia Tech Department of Chemical Engineering,
and Norman Kaplan, National Risk Management
Research Laboratory, United States EPA
132
About Coal

• Protection of environment through process
  development is an important responsibility for
  chemical engineers
• Coal is an abundant source of energy and source
  of raw materials in production
• Predominately carbon, but contains other
  elements and hydrocarbon volatile matter

133

• burned in many of worlds power plants to
  produce electricity
• can produce a lot of pollution if gases not
  treated, like soot and ash
• sulfur dioxide emissions regulated in the U.S.
  by the Environmental Protection Agency
• current regulations are no more than 520 ng SO2
  per joule of heating value of the fuel fed to the
  furnace
• plants must remove 90 of SO2 released when
  coal-burning

134
About Commercial Processing

• SO2 removal is classified as regenerative or
  throwaway
• throwaway processing can be modified to produce
  gypsum
• throwaway processing uses separating agent to
  remove SO2 from stack gases followed by disposal
  of SO2 innocuously (CaSO3 ½ H2O) and a slurried
  separating agent of calcium carbonate

135
Process Description
136

• want to produce 500 MWe (megawatts of
  electricity)
• properties of coal given in table on next slide
• coal fed at 25oC to furnace, burned with 15
  excess air
• sulfur reacts to form SO2 and negligible SO3
• carbon, hydrogen oxidized completely to CO2 and
  water
• nitrogen in coal leaves furnace as N2
• ash in coal leaves furnace in two streams
• 80 leaves as fly ash in furnace flue gas
• remainder as bottom ash at 900oC

137
Component Dry Weight
Carbon 75.2
Hydrogen 5.0
Nitrogen 1.6
Sulfur 3.5
Oxygen 7.5
Ash 7.2
Moisture 4.8 kg/100 kg dry coal
HHV 30780 KJ/kg dry coal
Cp dry coal 1.046 kJ/(kgoC)
Cp ash 0.921 KJ/(kgoC)
138

• combustion air brought into process at 25oC, 50
  RH
• air sent to heat exchanger, temperature
  increased to 315oC
• air then fed to boiler, reacts with coal
• flue gas leaves furnace at 330oC, goes to
  electrostatic precipitator
• 99.9 of particulate material removed
• goes to air preheater, exchanges heat with
  combustion air
• leaves air preheater and split into two equal
  streams
• each stream is feed to one of two identical
  scrubber trains
• trains sized to process 60 of flue gas

139

• divided gas stream fed to scrubber, contacts
  aqueous slurry of limestone, undergoes adiabatic
  cooling to 53oC.
• sulfur dioxide absorbed in the slurry and reacts
  with the limestone
• CaCO3 SO2 ½ H2O CaSO3 ½ H2O
  CO2
• solid/liquid slurry enters scrubber at 50oC
• liquid slurry flows at 15.2 kg liquid/kg inlet
  gas
• solid to liquid ratio in the slurry is 19 by
  weight
• liquid saturated with CaCO3 and CaSO3
• cleaned flue gas
• meets EPA SO2 requirements
• leaves scrubber with saturated water at 53oC

140

• cleaned flue gas contains CO2 generated in
  scrubbing but no fly ash
• cleaned flue gas reheated to 80oC, blended with
  clean flue gas stream from other train, and
  sent to be released to atmosphere
• solids in spent aqueous slurry
• unreacted CaCO3, flyash from flue gas, inert
  materials, CaSO3
• liquid portion of slurry saturated with CaCO3,
  CaSO3
• specific gravity of 0.988
• spent slurry split in two
• one stream sent to a blending tank, mixed with
  freshly ground limestone, makeup water, and
  recycle stream
• fresh slurry stream from blending tank fed to
  top of scrubber

141

• second stream sent to filter where wet solids
  containing fly ash, inert materials, CaSO3 and
  CaCO3 are separated from filtrate
• filtrate saturated with CaSO3, CaCO3, and is the
  recycle stream fed to the blending tank
• wet solids contain 50.2 liquid that has similar
  composition to filtrate
• fresh ground limestone fed to blending tank at
  rate of 5.2 excess of that is required to react
  with SO2 absorbed from flue gas
• limestone 92.1 CaCO3 and rest is insoluble
  inert material

142

• Boiler generates steam at supercritical
  conditions
• 540oC and 24.1 MPa absolute
• mechanical work derived by expanding steam
  through a power- generating system of turbines
• low pressure steam extracted from power system
  contains 27.5 liquid water at 6.55 kPa absolute
• heat removed from wet low pressure steam in a
  condenser by cooling water
• cooling water enters condenser at 25oC and
  leaves at 28oC
• saturated condensate at 38oC is produced by
  condenser and pumped back to boiler

143

• Assume a basis of 100 kg dry coal/min fed to the
  furnace.
• Construct a flowchart of the process and
  completely label the streams. Show the details of
  only one train in the scrubber operation. Do this
  in Excel.
• Estimate the molar flow rate (kmol/min) of each
  element in the coal (other than those in the
  ash).
• Determine the feed rate (kmol/min) of O2 required
  for complete combustion of the coal.

144

• If 15 excess oxygen is fed to combustion
  furnace, estimate the following
• The oxygen and nitrogen feed rates (kmol/min)
• The mole fraction of water in the wet air, the
  average molecular weight, and the molar flow rate
  of water in the air stream (kmol/min)
• The air feed rate (kmol/min, m3/min)
• Estimate flow rate (kmol/min, kg/min) of each
  component and composition (mole frac) of furnace
  flue gas (ignore fly ash). At what rate (kg/min)
  is fly ash removed from flue gas by the
  electrostatic precipitator?

145
6. If system is assumed to meet standard 90 SO2
removal released upon combustion a. Determine
flow rate (kg/min and kmol/min) of each
component in the flue gas leaving scrubber b.
Determine flow rate (kg/min) of slurry entering
scrubber c. Estimate solid-to-liquid mass
ratio in slurry leaving scrubber. d.
Estimate feed rate (kg/min) of fresh ground
limestone to the blending tank.
146
6. (continued) e. What are flow rates (kg/min)
of inerts, CaSO3, CaCO3, fly ash, and water, in
the wet solids removed from the filter? f.
Estimate rate (kg/min, L/min) at which filtrate
is recycled to blending tank. At what rate
(kg/min, L/min) is makeup water added to
blending tank? 7. At what rate is heat removed
from the furnace? Estimate the rate of steam
generation in the power cycle, assuming all the
heat removed from the furnace is used to make
steam.
147
References

• Felder, R.F. and Rousseau, R.W. Elementary
  Principles of Chemical Processes, Third Edition.
  New York, John Wiley and Sons, 2000.
• Smith, J.C. and Harriott, Peter. Unit Operations
  of Chemical Engineering, Sixth Edition. Boston,
  McGraw Hill, 2001.
• Earle, R.L. Unit Operations in Food Processing,
  Second Edition. http//www.nzifst.org.nz/unitopera
  tions/index.htm
• Thibault, Jules. Notes, CHE 4311 Unit
  Operations. University of Ottawa, August 2002.
• Genzer, Jan. Notes, CHE 225 Chemical Process
  Systems. North Carolina State University, August
  2002.

148

• Source on pictures for slides 13, 41,