aspen plus & dynamic workshop (step by step)

Aspen Plus & Aspen Dynamic Workshop

Driven by Innovation

By: Dinie Muhammad

2 D. Muhammad & AspenTech, 2013

Presentation Outline

• Part 1: Introduction to Aspen Plus

• Introduction to AspenONE

• Introduction to Flowsheet simulation

• What is Aspen Plus?

• What Aspen Plus can do?

• Aspen Plus extension- Aspen Dynamic

• Steady state and Dynamic model dilemma

• How Aspen can help me with my research?

• Part 2: Before starting with Aspen Plus

• Process “know how”

• Process Analysis

• Property Method

Presentation Outline

• Part 3: Getting Started with Aspen Plus

• Distillation column design

• Aspen Analysis

Binary Analysis

Azeotrope Analysis

Design Specs

Sensitivity Analysis

Optimization

• Part 4: From Aspen Plus to Aspen Dynamic

• Part 5: Aspen Dynamic with Matlab

PART 1: INTRODUCTION TO ASPEN

Introduction to AspenONE

• Developed by AspenTech Inc.

• Integrated simulation software to implement best practices for:

Process design and modelling

Optimization engineering

Production management

Supply chain operation

Advanced process control

General Simulation Problem

What is the composition of stream PRODUCT?

To solve this problem, we need:

• Material balances

• Energy balances

REACTOR

RECYCLE

REAC-OUT

COOL-OUT SEP

PRODUCT

Flowsheet Simulation

What is flowsheet simulation?

Use of a computer program to quantitatively model the characteristic equations of a chemical process

Uses underlying physical relationships

• Mass and energy balance

• Equilibrium relationships

• Rate correlations (reaction and mass/heat transfer)

Predicts

• Stream flowrate, compositions, and properties

• Operating conditions

• Equipment sizes

Flowsheet simulation

Approaches to Flowsheet Simulation

Sequential Modular

• Each unit operation block is solved in a certain sequence

• Aspen Plus is a sequential modular simulation program

Equation Oriented

• All equations are solved simultaneously

• Aspen Custom Modeler (formerly SPEEDUP) is an equation oriented

simulation program

Combination

• Aspen Dynamics (formerly DynaPLUS) uses the Aspen Plus

sequential modular approach to initialize the steady state simulation

and the Aspen Custom Modeler (formerly SPEEDUP) equation

oriented approach to solve the dynamic simulation

Sequential-Modular

Approach

Equation Oriented

Approach

Advantage of Simulation

Reduces plant design time

• Allows designer to quickly test various plant configurations

Helps improve current process

• Answers “what if” questions

• Determines optimal process conditions within given constraints

• Assists in locating the constraining parts of a process (debottlenecking)

Good Flowsheeting Practice

• Build large flowsheets a few blocks at a time.

This facilitates troubleshooting if errors occur.

• Ensure flowsheet inputs are reasonable.

• Check that results are consistent and realistic.

What is Aspen Plus?

• Steady state computer-aided chemical process simulation tool

Aspen Plus Inputs

Aspen Plus Process

Simulation Model Inputs

Process Flowsheet

Design

Specify Chemical

Components

Choose Thermodynamic

Models

Specify Feed Conditions

Specify Operating Conditions

What Aspen Plus can do?

• Flowsheet (default): process simulation (SA and optimization)

• Data Regression: fitting data to existing models in Aspen

• Property Display: show properties of a components in Aspen Plus’s database

• Property Analysis: estimating physical and thermodynamic properties

• Assay Data Analysis: analyze assay data (petroleum application)

• Property Plus: prepare property package for Aspen Custom Modeler

Aspen Plus in Process Design & Development

Aspen Plus Extension: Aspen Dynamic

• Dynamic modeling tool for plant operations and process design

• Enables users to study and understand the dynamics of real plant operations

• Exported from Aspen Plus steady state model

Aspen Dynamic Overview

Adding Dynamic Data

Data is required to calculate the following:

• Vessel geometry (required for vessel volume)

• Vessel initial filling (used for starting liquid holdup)

• Process heat-transfer method

• Equipment heat transfer options

Equipment heat capacity

Environmental heat transfer

Steady state vs. Dynamic dilemma

Steady state

• All properties are steady (not changing over time).

• Can be used to study different steady state conditions for a specific range of properties either at operating conditions or off-design conditions.

Dynamic

• Ability to model the time varying behaviour of a system (changing over time)

• Used to analyse the dynamic behaviour (response) of complex systems.

Advantages of Steady State Simulation

• Immediate answers to system condition variation

• Determine results at specific conditions

• Quick what if in design, sensitivity and optimization studies

Advantages of Dynamic Simulation

• Determine behaviour of plant/system over complete operating range: start up, shut down, accident scenarios, transition between different states and disturbances occurrence (what if –behaviour)

• Can identify in advance if the operating problems occurred

• Facilitate the design for control and optimization of process components to ensure optimum system behaviour, even during off design and transient behaviour

• Design and commission control systems using simulations and just fine tune during actual installations

• Dynamic integrated simulations can help to identify bottlenecks, inefficiencies and safety risks that are not identifiable with steady-state or segregated simulation

Application for SS and Dynamic Simulation

Mcmillan, G. K. (2006). Modeling and Simulation of Processes. In "Process Control And Optimization" (B. G. Lipták, ed.), Vol. 2. CRC Press, Boca Raton, FL.

How Aspen can help me with my research?

• Another option for first principle model (FPM)

• Simulation and validation of complex chemical process

•Sensitivity analysis and optimization study of process

• Study nonlinearity and multiplicity behavior in process

• Using Aspen Dynamic & Matlab Simulink for control scheme design

PART 2: BEFORE STARTING WITH

ASPEN PLUS

Process “know how”

• Aspen Plus is not a magic box

• All the process inputs (e.g. sizing and process condition) must based on facts or heuristic justification

• A preliminary study of process design in recommended

Process Analysis

• Used to generate simple property diagrams to validate physical property models and data

• Understand the behavior of the process

• Diagram Types:

Pure component, e.g. Vapor pressure vs. temperature

Binary, e.g. TXY, PXY

Ternary residue maps

• Select Analysis from the Tools menu to start Analysis

Aspen Property Method

• A collection of thermodynamic models and methods used to calculate physical properties.

• Choice of model types depends on degree of non-ideal behavior and operating conditions

• Users can modify existing Property Methods or create new ones

Case Study - Acetone Recovery

• Correct choice of physical property models and accurate physical property parameters are essential for obtaining accurate simulation results.

Ideal vs. Non-Ideal Behavior

What do we mean by ideal behavior?

• Ideal Gas law and Raoult’s law

Which systems behave as ideal?

• Non-polar components of similar size and shape

What controls degree of non-ideality?

• Molecular interactions e.g. Polarity, size and shape of the molecules

How can we study the degree of non-ideality of a system?

• Property plots (e.g. TXY & XY)

Comparison of EOS and Activity Models

Common Property Methods

Equation of State Property Methods

• PENG-ROB

• RK-SOAVE

Activity Coefficient Property Methods

• NRTL

• UNIFAC

• UNIQUAC

• WILSON

Choosing a Property Method - Review

References:

Aspen Plus User Guide, Chapter 7, Physical

Property Methods, gives similar, more detailed

guidelines for choosing a property Method.

PART 3: GETTING STARTED WITH

ASPEN PLUS

Run ID

Tool Bar

Title Bar

Menu Bar

Select Mode

button Model

Library

Model Menu

Tabs Process Flowsheet

Window

Next Button

Status Area

Aspen User Interface

Case Study

Design a distillation process to separate isobutane and propane so that the impurity target in distillate is 2 wt% and in bottom is 1 wt%

Propane (40%)

Isobutane (60%)

Flowrate: 100 kg/h

Temperature: 322 K (48.85’C)

Pressure: ?

Number of Stages = 32 (reboiler + sump)

Number of Trays = 30

Feed at Stage 16

Reflux ratio = 2

Overview of case study

C3 0.4 wt%

iC4 0.6 wt%

C3 0.98 wt%

iC4 0.02 wt%

C3 0.01 wt%

iC4 0.99 wt%

How to begin?

Develop the distillation column system

Specify the C3 and iC4 in component selection

Choose a suitable property method

Define feed condition

Specify a reasonable operating condition

Run and check the results

Columns - Shortcut

Columns - Rigorous

Develop the distillation column system

Pump (pressure

changer library)

Valve (pressure

changer library)

Distillation column –

RadFrac (separator library)

Connect all the blocks

Select material stream to insert

stream in the flowsheet

Connect all the red input and

output (primary stream)

A complete distillation system

Click the NEXT button

and this dialog menu

will appeared. Click OK

to proceed.

FEED DIST

Rename all

the blocks

and streams

Fill the specification menu

Select unit measurement Note:

You can also use your own set of unit

by using Unit-Sets option under the

Setup Menu

Edit Report Options

Specify the component

Use the Find

button to search

the components Click the NEXT button

Select the property method

Select Chao-Seader

property method

Define the FEED stream

How to calculate the pressure in FEED?

• Cooling water at condenser is expected to be at 305 K (31.85’C)

• Heuristic temperature different for heat transfer in condenser is 20 K

• Therefore, the reflux drum temperature is ~ 325 K

• Vapor pressure for C3 at 325 K is ~ 14 atm

• Assume the pressure drop in the V1 is 5 atm

• So, FEED stream pressure > 19 atm

• In this case, FEED pressure is selected at 20 atm

Distillation column setup (Configuration)

Distillation column setup (Stream)

Distillation column setup (Condenser)

Heuristic pressure

drop in column =

0.0068 atm

Pump 11 and Pump 12 Setup

Use pressure increase

6 atm for all pump Click the NEXT button

V1 Setup

Use outlet

pressure option

= 14.2 atm

Choose Liquid-Only

V12 and V13 Setup

Use Pressure

drop option

= 3 atm

Choose Liquid-Only

Run the simulation

Click OK to run the simulation

The simulation run complete

Result completed normally

Status Indicators

Check the results (Stream summary>>Streams)

The overall

result is still

not achieve

target

Adjust to

STREAMS

Select the

wanted

streams

Redesign: RR = 3

• Operating condition for RR is changed from 2 to 3

• Reinitialize the simulation and Run again

Reinitialize button

Check the results (Stream summary>>Streams)

Separation

target achieved

Analysis Using Aspen Plus

• Binary Analysis – This tool will examine and plot the binary interaction between components.

• Azeotrope Analysis – To determine whether the mixture is azeotrope mixture or not

• Design Spec - This tool will help the user to achieve the production target by varying the specified operating condition.

• Sensitivity Tool – This tool will help the user to analysis the effect of specified operating condition over a certain region towards the production target.

• Optimization – This tool will produce the optimized value for the operating condition in order to achieve the desired production target. This tool will automatically change the selected operating value to an optimized value after Run.

ANALYSIS: BINARY ANALYSIS

Find Binary Analysis Menu

Access the Binary Analysis

Menu under Tools Menu

Click OK to continue

Select basis

component

Binary Analysis Menu

Select type

of analysis

Select Unit

and list/range

for Pressure

variation

Property

Method

Click GO to

start analysis

Analysis Result

Txy Graph

results

Use Plot Wizard

to plot other type

of graphs e.g. xy

ANALYSIS: AZEOTROPE ANALYSIS

Azeotrope Analysis Menu

Select the menu

In this case, consider a feed of water and

isopropane mixture to be analyzed. Here,

the property method selected is SRK

Mixture Block

Click the desired

component

Finally, click the

Report option to

get the analysis

Select the

Pressure basis

Select Property

method and

mixture phase

Azeotrope Report

Azeotrope exist!

The xy graph

azeotrope point

xy graph of water and isopropane mixture (from Binary Analysis)

ANALYSIS: DESIGN-SPEC

Choose the Design-Spec Menu

Design Spec and

Vary (below) menu

in the explorer

Create new ID

Design Spec Tab Information

• Specification – define the target to be achieve in the simulation e.g. 99% composition in distillate stream

• Components – specify the target component

• Feed/Product Streams - specify the target component’s stream

Specify target

Specification Tab

Select type

of target

In this case, a mass purity target of 0.99% is desired

Components Tab

Select the target

component from

available

components

Propone is selected as the target component

Feed/Product Streams Tab

Specify the target

stream from the

available streams

Since the C3 product stream is at the top, thus

the distillate stream is selected

Vary Menu: To specify the varying variable for Design-Spec

Vary Menu

Create new ID

Specification Tab Select the varying variable

to be used. Must be a

variable from the specified

operating conditions

Select a reasonable

lower and upper

Run the simulation

Click OK to start the simulation

Check result in Vary Menu

Select the

Results Tab

The final value of RR to achieve

99%C3 purity is 2.87

ANALYSIS: SENSITIVITY STUDY

Select: Sensitivity Study

Select the Sensitivity

option from Model

Analysis Tool

Sensitivity Study Tab Information

• Define: The user need to define the variable to be used as the production/simulation target.

• Vary: Choose the a variable from the specified operating conditions to be varied over selected region.

• Tabulated: Choose how the data will be tabulated. Usually, varied operating conditions vs. target value responses

Insert new variable

Click New and enter a name

for the target variable

Select the target variable

In this case, we want

to specify the C3 mass

concentration in the

distillate stream as the

Target variable

Select the Vary Variable

In this case, the Reflux

ratio (RR) is selected to be

the Vary variable. The RR

variable can be selected by

specify C1 (the column)

under Block-Var (Block

variables).

Specify range: Lower and Upper boundary.

Specify the number of point to be plotted

Use search option

to find the RR

Tabulate the variables

Click Fill variables button

as Aspen will automatically

tabulated all the variables.

Click the NEXT

button and OK

Check result Choose Results. Make sure all the

result is completed and converged

(blue tick on the explorer)

Full results is

available here

under S-1 label

Results summary

for C3 composition

by varying RR

How to plot results in Aspen

Select the RR column

in results summary

Click Plot from menu bar.

Specify as X-axis.

Repeat the same procedure for C3 result. Finally,

click the Display Plot under the same Plot menu

The Sensitivity analysis results

The figure show the effects of varying

the RR towards C3 composition.

Based on the figure, the best RR value

to achieve the highest C3 purity would

be around RR=4

ANALYSIS: OPTIMIZATION

Select Optimization Menu

Optimization menu

Click New to

create a new ID

Define Tab

Click New to define a

New optimization value

Enter the target variable

name and Click OK

Define the Target variable

Specify the Target

variable

The optimization target variable is C3

mass purity in the distillate stream

Objective & Constraints Tab

Select max

or min

Specify the previously defined

variable name in the Define Tab

Constraint can also be

specified in the

Constraint Menu

C3 composition is optimized to find the max purity

Vary Tab

Specify number of

varying variable

Select and specify

the varying variable Specify lower and

upper boundary

RR is varied from 0.5 to 5 to find the max

mass purity for C3 distillate product

Run the simulation

Click OK to start the simulation

Check the results: Final C3 composition

Final value shows the max C3 distillate

product composition can be achieved

within the specified boundary

Check the results: New optimized RR value

The optimized RR value in

the C1 Results Summary

PART 4: FROM ASPEN PLUS TO ASPEN DYNAMIC

Steady State to Dynamic Simulation

Using the same example:

A commonly used heuristic is to set these holdups to allow for 5 min of liquid holdup when the vessel is 50% full, based on the total liquid entering or leaving the vessel (Luyben, 2006)

• 100% full = 10 minutes of volume flowrate

• From Hydraulic Tab:

Reflux drum volume = 0.00800586 m3/min (10min) = 0.0801 m3

Sump volume = 0.00216335 m3/min(10min) = 0.0216 m3

*Please refer to slide18 &19 for explanation on dynamic properties

Luyben, W. L. (2006). "Distillation Design and Control using Aspen Simulation," Wiley, New York.

From Hydraulic Tab: Stage 1 => Reflux drum volume i.e. sum of Reflux and distillate flowrate

From Hydraulic Tab: Stage 32 => sump level i.e. liquid entering reboiler from bottom tray

Calculate the vessel geometry

Reflux drum: L = 0.9718m; D = 0.3239 m

Sump: L = 0.6279 m; D = 0.2093 m

L=length; D=diameter

Vessel Geometry

Entering the dynamic properties

Click this button to enter

the dynamic properties

Enter the dynamic properties in the column configuration: Reflux drum and Sump Sizing

Enter the calculated

Length and Diameter for

Reflux Drum and Sump

Entering the properties for Hydraulic calculation inside the column

Choose Rigorous

Tray Calculation

Additional Info

• Simple Tray: Using simple tray hydraulics equation relates the liquid flow rate from a tray to the amount of liquid on the tray. Here, the Francis weir equation for a single pass tray is used.

• Rigorous: The pressure drop across the tray is calculated by the same rigorous methods used for the steady-state simulation. The Francis weir equation is used to model the hydraulics based on the number of passes and tray geometry specified in the steady-state simulation.

Tray Rating

Since we are using Rigorous Tray

Calculation, we need to specify the Tray

Rating (so that Aspen Plus can perform the

pressure drop calculation along the trays)

Specify Tray Rating

Select Tray Rating

menu under the C1

Click New and enter

any ID number

Specify Tray Rating

Enter the starting stage = 2

and End stage = 31

(In Aspen Plus; Stage1 =

Condenser and Stage 32 =

Reboiler)

Enter the tray diameter, Tray type,

Tray spacing and weir heights

Note: Default value for

Tray spacing = 0.6069 m

weir heights = 0.05 m

Pressure Drop profile

In order for the Aspen Plus to

calculate and update the Pressure

Drop profile inside the column, this

box must be tick

Click the NEXT button and RUN the simulation

Export to Dynamic (Flow Driven)

Click this icon for export our model

into dynamic state (flow driven).

A menu will pop up to rename and

save the model. Just click OK.

Additional Note:

Aspen provide two type of dynamic simulation i.e. flow driven and pressure driven. The icon for pressure driven simulation is just next to the flow driven in the menu. In the author experience, flow driven simulation is much simpler to develop compared to the pressure driven. Once the simulation is completed with no error, the simulation is ready to be export to the dynamic states in flow driven.

However, for pressure driven, all the pressure inside the streams in steady state model must be control by using pump or valve and its pressure must appropriate. There are also problem (depends) with irregular pressure drop inside the column and inconsistence pressure in feed and recycle stream. Use the Pressure checker icon to check the pressure within the SS model. Refer Process Simulation and Control Using Aspen by AK Jana.

Pressure Checker

Find the saved file .dyn file

Click the saved file from previous

menu. Generally, the file is saved

in the same folder as the SS

simulation file

Entering Aspen Dynamic (or Custom Modeler)

If all goes right, you should get

this figure. Notice that in Aspen

Dynamic, the basic controller is

already implemented. These

control loops are important to

operate the column properly.

Click this set of

icons to

run/pause/rewind

(or restart) the

simulation

Choose the state

of simulation:

Dynamic or

Steady-state. Run

Initialization at

before starting

dynamic

simulation

Additional Info:

• For distillation system, there are 3 major control loop that are essential to operate the column:-

1. Top / Condenser Pressure control loop –control energy balance

2. Reflux drum Level control loop –control mass balance (top)

3. Sump Level control loop –control mass balance (bottom)

See simulation result

Run the simulation.

Right click top product

stream. Select Forms

and click TPFmPlot

During running

the simulation,

this panel will

show the latest

calculation step

Results in real time form This panel

display the

mass flowrate,

pressure and

temperature for

the top product

stream in real

time. Use Zoom

Full option for

clearer plot.

Although the graph is

not steady, notice that

the difference (in each

parameter) is very small.

#1 Select Tool in

the top menu.

Click New Form

#2 Name form

and choose Plot

option

Specify custom parameter (e.g. Propane purity in top product stream)

#3 The plot

figure with no Y

axis value

Specify specific parameter

#4 Right click top stream and

choose Results in the Forms option

#5 From Results Table, drag the

highlighted row (Propane purity) into

the Y axis of the plot. The final figure

should be like the one on the left. Run

the simulation in dynamic mode.

#6 We can now know the

Propane composition in

Distillate Stream in real time

PART 5: ASPEN DYNAMIC WITH MATLAB SIMULINK

Getting Started with Aspen-Matlab

• Basically, AspenTech had made a collaboration with Mathworks to develop the AMS simulation system to connect Aspen Dynamic with Matlab Simulink

• However, there might be some compatibility issues regarding Aspen and Matlab version. Please refer to Aspen Help. Based on the author experiences:

Aspen V7.2 compatible with Matlab 2009

Aspen V7.3 compatible with Matlab 2010

Use Aspen Dynamic Examples

• As an example, we are using the Simulink file in the Aspen Dynamic Examples

• Find the Aspen Dynamic instillation folder. Inside the folder, find the Examples folder. Inside the example folder, click the Simulink folder;

C:\Program Files\AspenTech\Aspen Plus Dynamics V7.2\Examples

Click the MCH file (Simulink) as shown below:

Note: MCH is a simulation

of extractive distillation of

methylcyclohexane and

toluene using phenol as

an entrainer.

The MCH simulation in Simulink

Notice that there are 4 control loops

that are controlling the MCH column.

Now, input s form the Aspen Dynamic

(via AMS Block) is supplied to the

controller block. Then, the controller

action is computed in Simulink and

returned back to the Aspen Dynamic

for further action.

AM-Simulation

A step input

block act as the

disturbance

Configure AMSimulation Block

Click the AM-

Simulation Block

to open this menu

Use Browse to

find the .dynf

(Aspen Dynamic)

Input & Output represent the variables

that being used in the AMS Block. Input

refer to the input that is supplied to the

Aspen Dynamic model (e.g. MV or DV).

Output refer to the process variable (i.e.

PV) that is produced from the model.

Click Connect

to link with Aspen

Dynamic

MCH Model in

Aspen Dynamic

AMSimulation file

Before begin the Aspen-Matlab

simulation, it is advised that we

copy the AMSimulation file (m-

file format) into the current

working folder (in Matlab) . The

file is generally located inside

the AMSystem folder in the

Aspen installation folder.

Follow the link

Running the simulation

Click RUN button in the Simulink to run the

simulation

Simulink

Dynamic

How they work?

AM-Simulation

Aspen Dynamic

Matlab Simulink

Provide simulation

data and result

(present the PV)

Compute and provide

controller action

(decide the MV)

What happen?

• Based on the previous figure (after running the simulation), Matlab Simulink had provided the initial Input (SS or initial value) for the Aspen Dynamic Model. Then, the input is processed (or calculated) by Aspen Dynamic to provide the current process variable (PV) values. The process variables is send back to Simulink environment via AMS Output.

• Based on the output that we had selected (in the AMS box), the output will provide the latest PV for Simulink Matlab to calculate its next MV. The new MV is then supplied back to the Aspen Dynamic via AMS Input and so on.

• One of the ways to set the initial value for the Aspen Dynamic is by using the unit delay box in Matlab Simulink.

Simulation Time

• In the author opinion, it is important to synchronize the Aspen Dynamic and Matlab Simulink simulation time.

• This can be done via RUN (in the menu bar) >> Run Option or select F9.

Adjust the time

units to match

both simulation

Simulation model vs. predictive model

u(k) Simulation Model (Aspen Dynamic) y(k)

u(k) Predictive

Model y(k+1)

Special Thanks

• Assoc. Prof Dr. Norashid Bin Aziz (USM)

• Assoc. Prof Dr. Zainal Bin Ahmad (USM)

• Imam Mujahidin Iqbal, Msc (USM)

• Process Control Research Group (PCRG) USM

E: annursi@gmail.com

END OF PRESENTATION

aspen plus & dynamic workshop (step by step)

muhammad aspentech

inputs aspen

aspen dynamic workshop

dynamic simulation

certain sequence aspen

aspen custom modeler

dinie muhammad

process design

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