chapter 4d - chemical process optimization (classification and the approach)

8/18/2019 Chapter 4d - Chemical Process Optimization (Classification and the Approach)

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EP426Chemical Process Design and Optimization

Chapter 4


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Teaching plan (Wk8 to Wk14)

8 Chapter 4Chemical Process Optimization.

Optimization overview.22/02/2016

Chapter 4Chemical Process Optimization.

Optimization application on Chemical processes.24/02/2016

9 Chapter 4Chemical Process Optimization.

Optimization application on Chemical processes.29/02/2016


Optimization classification and the approach (Part I)02/03/2016

10Individual Assesement (5%)

Presentation based on the group assignment07/03/2016


Optimization classification and the approach (Part II) 09/03/2016

11 Chapter 5Heat & Energy Integration.

Overview of process integration and the applicaton14/03/2016

Chapter 5Heat & Energy Integration.

HENs analysis (Part I) - Composite Curves and Problem16/03/2016

12 Test 1 (10%) 21/03/2016

Chapter 5 Heat & Energy Integration.HENs analysis (Part II) - Area & Unit targeting

23/03/2016

13 Chapter 5Heat & Energy Integration.

HENs analysis (Part III) - Pinch design28/03/2016

Chapter 5Heat & Energy Integration.

HENs analysis (Part IV) - Maximum Recovery design.30/03/2016

14

Revision and Tutorial

Group Report Submission (10%)

04/04/2016

Due: 5:00 PM


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Student attainment

CLO4: Determine optimal solution for a chemicalprocess using Linear Programming.

Note:

Teaching method - Lecture & Group Project

Assessment - Test, Final Exam and report presentation.


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Chapter 4: Topics

1. Optimization overview.

2. Optimization application on Chemical processes.

3. Basic elements in the optimization; ObjectiveFunction, Parameters, and Constrains.

4. Optimization classification and the

approach ofLinear Programming method.


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EP426Chemical Process Design and Optimization

Chapter 4d - Chemical Process Optimization.

Optimization classification and the approach(Part I)


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The goal of optimisation

is to improve the process, it is essential that one startfrom a defined process, that is, a BASE CASE.

Example:

if one has already determined (through prior analysis) that

heat integration greatly improves the process,

Thus: the base case should include the heat integration.

Data Required for Base Case


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Optimization Limitation 1: Reality

Example: Using Continuous and Discrete Functions of Pipe Diameter

B

A

In reality, the cost

function depends

only on certain pipe

diameters and pump

sizes are standard.


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Both annualized capital costs and operating costs are included.

Although there is a

point of zero slope

(point A), the best

design (minimumannual cost) shown

is at point B.

The first derivatives of the

cost function are zero.

Optimization Limitation 2: Location


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Optimization Limitation 3: Limited data


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Topological Optimization

Deals with the topology or arrangement of processequipment.

The concern:

1. Can unwanted by-products be eliminated?

2. Can equipment be eliminated or rearranged?

3. Can alternative separation methods or reactorconfigurations be employed?

4. To what extent can heat integration be improved?

Rearrangement of Equipment


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Elimination of Unwanted Nonhazardous By

Products or Hazardous Waste Streams

• The objective to obtain 100% conversion of reactantswith a 100% selectivity to the desired product shouldbe clear.

• Although this goal is never reached in practice, it can beapproached through suitable choices of reactionmechanisms, reactor operation, and catalyst.

• A chemical engineer may not be directly involved in the

choice of reaction paths. However, one may be asked toevaluate and optimize designs for using alternativereactions in order to evaluate the optimum scheme.


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Elimination and Rearrangement of Equipment

• It is assumed that thePFD in which allprocess equipment

serves a valid function(the process does notcontain any redundantequipment).

• It is often the result of

a change in operatingconditions and the endlead to parametricchanges.


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Rearrangement of Equipment

•

There are certain guidelines that should befollowed when the sequence of equipment isconsidered.

• For example:

Should try to pump a liquid rather than compress a gasThus: Always be better to place a pump before a vaporizerrather than a compressor after it.

• Mostly, Equipment rearrangement are associatedwith the separation section of a process and theintegration of heat transfer equipment


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Parametric optimization

Concerned with the operating variables, such astemperature, pressure, and concentration of streams, for a given piece of equipment or process.

1. Single-Variable Optimization

The effect of minimum reflux ration on the Net Present value

2. Two-Variable Optimization

The Effect of Pressure and Reflux Ratio on the SeparationColumn

3. Three Variable Optimization


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Single Variable Optimization

The Effect of Pressure and Reflux Ratio on the Separation Column

R/Rmin = 1.2


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Two Variable Optimization

The Effect of Pressure and Reflux Ratio on the Separation Column

R/Rmin = 1.2

R/Rmin = 1.15

@ 9 bar


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Two Variable Optimization

R/Rmin = 1.15

@ 9 bar


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Parametric consideration

Potential decision variables:1. Operating conditions for the reactor

The temperature range may be restricted by catalyst properties

2. Single-pass conversion in the reactor.The selectivity will be determined by the conditions mentioned in (1) and

the single-pass conversion.3. Recovery of unused reactants.

4. Purge ratios for recycle streams containing inerts.

5. Purity of productsthis is often set by external market forces.

6. Reflux ratio and component recovery in columns, and flow ofmass separating agents to absorbers, strippers, extractors, andso on.

7. Operating pressure of separators.


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Approach

1. Analytical Techniques

Finding the location where gradients of the objective function arezero.

2. Reponse Surface Techniques

• Commonly known as “factorial designs”• At early phases of design.

• Scoping the optimization problem to determine an decisionvariables.

3. Pattern Search Techniques

• Iterative techniques

• Proceed from an initial guess toward the optimum, withoutevaluating derivatives or making assumptions about the shape of the objective function surface.


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EndNext Class (Optimisation Classification and the Approach -Part 2)

chapter 4d - chemical process optimization (classification and the approach)

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