Aspen Plus

(1)

Aspen Plus for Process

Design and Simulation

Resource Persons

Prof Dr Shahid Naveed Prof. Dr. Shahid Naveed Dr. –Ing. Naveed Ramzan

Associate Professor

Mr. Farhan Ahmad Mr. Farhan Ahmad

Lecturer

Ms Sana Yousaf

Course Organizing Officer Ms. Sana Yusuf

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Course Agenda

• Role of Simulation in Process Design

• AspenTech Products and Aspen Plus Features • Aspen Plus graphical User Interface

• Aspen Plus Basics

• Physical Properties Model and Properties Estimation • HEATX and Heat Exchanger Modelling

• RADFRAC and Distillation Column Modelling • Unit Operation ModelsUnit Operation Models

• Sensitivity Analysis • Final Workshop

• Final Workshop

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Course Agenda (Day – 1)

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Course Agenda (Day – 2)

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Course Agenda (Day – 3)

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Role of Simulation in

Process Design

Resource Persons

Prof. Dr. Shahid Naveed

6 Aspen Plus for Process Design and Simulation

(7)

Simulation

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Modelling and Simulation

1: What is Modeling

Description

of

any

complete

system

in

mathematical terms is called a mathematical

model

2: What is Simulation

Solving

the

modeling

equations

either

numerically or analytically

(9)

Simulation and Modelling Problem in

Process Engineering

Nano

Micro

Meso

Macro

Mega

Molecular Processes, Bubbles, Drops, Particles Reactors, Columns, Exchangers, Pumps Production Plants, Petrochemical Environment, Atmosphere Oceans

Active sites Particles, Eddies Pumps, Compressors, ... Petrochemical Complexes Oceans Soils

Lit.: Charpentier, J.-C.; Trambouze, P.: Process Engineering and problems encountered by chemical and related Industries in the near future Revolution or cointinuity?

9

by chemical and related Industries in the near future. Revolution or cointinuity? Chemical Enginering and Processing 37(1998) 559-565

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Why Process Simulation

The development of new industrial processes requires the solution of several unknown or expensive problems resulting from the scaling up, such as the impurities behaviour in a continuous run, the optimum such as the impurities behaviour in a continuous run, the optimum equipment design, the better fluid distribution, the pressure losses in different equipments, the operators training, etc. These problems shall be resolved with the high reliability and less costs as possible before the industrial plant installation.

To solve these problems it is necessary to run the process either in pilot plants or to construct prototypes, but this way is too expensive and normally very slow. Computer simulation applications can be used as a complementary development tool that in many cases lead to accurate solutions in shorter time and with much less consumption of resources solutions in shorter time and with much less consumption of resources. These computational tools are not used aiming to substitute traditional ones, but have demonstrated that can be a helpful complement in technological development and design engineering

11

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Process Simulation Tools

Simulations tools can help to resolve several of these

problems, with low cost, high reliability and normally in less

time. Otherwise these tools can help to the process engineer

to understand what happen, and what are the problematic

points in the whole process or in a particular equipment

points in the whole process, or in a particular equipment.

These tools can be classified in three groups depending on

the problem that are going to be resolved:

Æ

Process Simulation tools.

Æ

A computational fluid dynamics (CFD) tools.

Æ

Other particular simulation software

12

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Process Simulation Tools

Objectives of Process Simulation Tools:

Optimizing the design and performance of product assets

Opt

g t e des g a d pe o

a ce o p oduct assets

Increasing throughput and yield improving quality and

Increasing throughput and yield, improving quality, and

reducing energy costs

Responding more quickly to unexpected events or

changes in customer demand

g

Managing the profitability of operations in real time

13

(14)

Types of Process Simulation Tools

In process engineering two types of simulations tools are

used:

Æ

Steady-State Simulators:

Or Static simulators.

Typically used in process design, they simulate the

yp

y

p

g ,

y

process at steady state conditions, usually at the design

operating conditions. In this kind of tools Time is not a

variable

variable.

Æ

Dynamic models

: consider time as a variable and

simulate the process over a period of time A dynamic

simulate the process over a period of time. A dynamic

simulation can be used to estimate or illustrate the

response, over time, to a change in the process.

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Steady State Process Simulation Tools

The steady state simulation tool produce a

static simulation

,

which typically used in process design, to simulate the

yp

y

p

g ,

process at steady state conditions, usually

at the design

operating conditions

. This simulator don’t use Time as

variable

variable.

Th

i

l ti

t

l

ll

th

i

t

d

il

d

These simulation tools allow the engineer to do easily and

strictly

mass balance and energy balance

for a high variety of

chemical and petrochemical processes. Equipment and

p

q p

instrument design, plant design, capital costs, and technical

evaluations are all dependent on such calculations.

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Steady State Process Simulation Tools

All of this tools contains:

• A Physical and chemical properties Data Base for several elements and compounds and different methods to calculate the elements and compounds, and different methods to calculate the properties of mix.

• A Drawing tool, which can help to produce the Process Flow Di (PFD)

Diagrams (PFD).

• A Pre-modelled unit operation; like abortion columns, heaters, reactors, etc.

There are several different software for the steady state process simulation as:

- VMG Sim - Aspen plus

- Metsim - Chemcad

Others

16

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Dynamic Process Simulation Tools

Dynamic simulation tools consider

time as a variable

and

simulate the process over a period of time. A dynamic

simulation can be used to estimate or illustrate the response,

over time, to a change in the process.

This technology is commonly used for

design and revamp

studies, operator training, testing of DCS configurations

and

the development of operating procedures

the development of operating procedures.

Several of the steady state software tools have an especial

module to produce the dynamic simulation of the process. For

example

Aspen Dynamics

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Computational Fluid Dynamic (CFD) Tools

Computational Fluid Dynamic (CFD) simulation software has

been used for more than twenty years in the aerospace and

automobile industries but it is recently being applied to new

automobile industries, but it is recently being applied to new

industry fields where

heat transfer and fluids distribution

problems are present.

CFD is based on finite elements calculations. The simulation

software divides the 3D surface in discrete cells creating a

mesh. The software creates and calculates the

Navier–

Stokes equations

for every cell within the mesh starting from

defined

boundary

conditions

It

is

possible

to

define

defined

boundary

conditions.

It

is

possible

to

define

calculation objectives, for instance pressure, temperature,

and flow velocity, at selected sites of the simulated volume.

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Computational Fluid Dynamic (CFD) Tools

The following analyses can be performed:

•2D and 3D analysis of Newtonian fluids

•External and internal flows

•Steady-state and transient-state flows

C

ibl

d

ibl fl

•Compressible and non-compressible flows

•Laminar, turbulent and transitional flow regimes

•Flows with vortex

There are several different CFD

software as:

- Fluent

•Multicomponent flows

•Heat transference effects

•Gravitational effects

- Fluent

- Floworks

- Flow Science

•Gravitational effects.

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Required Competency

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Impact on Chemical Process Industry

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Problem

definition

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Problem definition

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AspenTech Products & Aspen Plus

Graphical User Interface

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Lesson Objectives

Aspen Tech Company Information

Simulation Targets

Li t f A

T

h P d

t

List of AspenTech Products

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AspenTech Company Information

• Advanced System for Process Engineering

(ASPEN)

• Project conducted at the Massachusetts Institute of

Technology (MIT) in Cambridge Massachusetts

Technology (MIT) in Cambridge Massachusetts,

from 1976 to 1981

• Over 2000 Employees world wide

• HQ in Cambridge, MA (Boston)

• Offices in 35 Countries

• Public held since 1994, NASDAQ

• www.aspentech.com

http://support aspentech com

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Process Simulation Targets

Process Simulation Debottlenecking R i Optimization,design etc. H t i t ti t Steady State Simulation _Revamping

Operation

Heat integration etc.

Sensitivity, maintenance Steady State Simulation

Process Control Real time optimization

Operation Dynamic Simulation

Start up, Shut down, safety

Operator Training

Operational failures _{Safety examinations, design} Disturbance Simulation

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Products

• Process Engineering

» Process simulation Chemicals (10 products : AspenPlus) » Process simulation Oil&Gas (8 products : AspenHYSYS)( p p ) » Process simulation Refining (11 products : Aspenadsim+)

» Process simulation Batch/Pharma (8 products :Aspenproperties) » Model Deployment (3 products : AspenModelrunner)

» Equipment modeling (8 products :AspenAcol+) » Basic Engineering (2 products :AspenKbase)

» Economic Evaluation (3 products : Aspn Icarus Project Manager) • Advance Process Control (14 products : Aspen Apollo, Aspen IQ) • Planning & Scheduling (10 products : Aspen Advisor Aspen MBO) • Planning & Scheduling (10 products : Aspen Advisor, Aspen MBO) • Supply & Distribution (3 products : Aspen Retail)

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Products

• Aspen Plus

Aspen Plus is the most popular product (accounted 48%

of sales in 1995)

a steady state modeling system built around the core

technology

• Properties PLUS

It is a database of chemicals properties underlying its

other products popular with customers ~ developed in

other products, popular with customers ~ developed

in-house modeling software

Oth

d l

• Other modules

» offers to the customers ~ license separately

» use with its other products to model subsystems used

i hi hl

i li

d h

i

l

i

li

i

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Starting with Aspen Plus

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Exercise-I

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Basic Input to Run Aspen Plus

Simulation

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Exercise-II

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Property Packages

&

Property Estimation

Resource Person

FARHAN AHMAD

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Types of properties

Th th t f ti

There are three types of properties:

» Thermodynamic properties » Transport properties

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Why are physical properties important ?

• A key requirement of process design is the need to • A key requirement of process design is the need to accurately reproduce the various physical properties that describes chemical species.

• Accurate representation of physical properties is essential key to meaningful simulation result.

• Aspen Plus also allow you to predict properties of mixtures ranging from well defined light hydrocarbon systems to omple oil mi t es and highl non ideal (non ele t ol te) complex oil mixtures and highly non-ideal (non-electrolyte) chemical systems.

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Can we believe simulation results?

Reasons: Reasons:

• Improperly selected thermodynamic models.

• Inadequate model parameters.

• Incorrect hypothetical components generation • Incorrect hypothetical components generation.

(87)

Property Package

• Property package is a collection of models that simulation tool (Aspen Plus) uses to compute thermodynamic tool (Aspen Plus) uses to compute thermodynamic, transport and other properties.

P t k d fi d b l l ti th ( t )

• Property packages are defined by calculation paths (routes) and physical property equations (models), which determine how properties are calculated.

• Aspen Plus includes a large number of built-in property packages that are sufficient for most applications.

» Modification of existing package » Develop a new package

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Available Property Packages

• Property methods ca be categorized into 4 groups: • Property methods ca be categorized into 4 groups:

» Ideal

» Equation-of-state

» Activity coefficient » Special

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Ideal Property Method

Ideal Property method uses the following calculation methods and models:

• Most basic property methods and models:

• Most basic property methods based on ideal behavior of system.

• Mixture properties are based on mole fraction averages of pure components properties pure components properties.

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Equation-of-state Property Packages

EOS property method uses the following calculation methods and models:

• It accounts the Departure from ideality.

• In EOS property methods, vapor and liquid properties are all calculated by the same

d l model.

• Extrapolates reasonably well with temperature and pressure.

• Inability to accurately predictab ty to accu ate y p ed ct highly non-ideal liquid mixtures.

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Activity coefficient Property Methods

Activity coefficient property methods use the following calculation methods and models for pure component

• Vapor and liquid properties l l d b diff

properties:

are calculated by different models.

• Ability to represent highly non-ideal liquid mixtures.

• Inconsistent in the critical region.

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Special Property packages

• Additional property packages use special correlations and are available for special applications:

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Selection

of

Property Packages

p

y

g

How to choose the best property prediction method for simulation ?

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Importance of Selecting the Appropriate

property package

p p

y p

g

• Correct predictions of the physical properties of the mixtureCorrect predictions of the physical properties of the mixture

as a function of temperature and pressure.

• Each method is suitable only for particular types of • Each method is suitable only for particular types of

components and limited to certain operating conditions.

Choosing the wrong method may lead to incorrect

• Choosing the wrong method may lead to incorrect

simulation results.

l l f l bl d

• Particularly important for reliable computations associated

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Principle Steps in Selecting the Appropriate

Property Package

p

y

g

1. Choosing the most suitable model.g

2. Comparing the obtained predictions with data from the literature.

3. Adding estimates for components that not available in the chosen package.

4. Generation of lab data if necessary to check the property model.

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Criteria of choosing suitable property package

• The choice of which the property package to use should be based on

based on

» Composition

» Temperature and pressure » Temperature and pressure » Availability of parameters

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Issues in Selection of the Appropriate

property Package

p p

y

g

• Nature of mixture

(e.g., hydrocarbon, polar, electrolyte, etc.)

• Pressure and temperature range

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Sources of Information

• Publications and professional literature that deal with the process in question or with the components in the process.

• Simulator reference manual (HELP).

• Databanks

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Recommendations for the Selection of the

Appropriate Property Package

• Eric Carlson, “Don’t gamble with physical properties for simulations,” Chem. Eng. Prog. October 1996, 35-46

• Prof J.D. (Bob) Seader, University of Utah

• Hyprotech Recommendations • Hyprotech Recommendations

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Example

• Find the best thermodynamic package for 1-Propanol • Find the best thermodynamic package for 1-Propanol ,

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1-Propanol ,H₂O mixture Non-electrolyte See Figure 2 Figure 1

E?

Polar Polarity R? Real or pseudocomponents P? Pressure E? _Electrolytes

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LL?

Yes

ij?

LL?

P < 10 bar _No WILSON, NRTL, UNIQUAC and their variances Figure 2

P?

j

No their variances

P?

UNIFAC and its Polar Non-electrolytes

LL?

No No extensions LL? _{Liquid/Liquid} P? Pressure ij?

ij? _{Interaction Parameters} Available

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HC? Hydrocarbons LG? Light gases Figure 3

LG?

Yes PC? Organic Polar Compound Yes _{See Figure 4}

HC?

No

PC?

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Figure 4 Yes NRTL, UNIQUAC

PPS?

Available

BIP?

PC with HC Binary Interaction UNIFAC Not Available PPS? Possible Phase Splitting

BIP? Binary Interaction Parameters

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1-Propanol, H

₂

O

98

100 TXY diagram for 1-Propanol, H2O Perry NRTL 94 96 98 NRTL PRSV UNIQUAC Van-Laar (Built-in Van-Laar(Perry) 90 92 94 T [ o C] 86 88 90 T 0 0 1 0 2 0 3 0 4 0 0 6 0 0 8 0 9 1 82 84 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

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RADFRAC & Distillation Column

Modeling

Resource Person

Dr. –Ing. Naveed Ramzan

Associate Professor

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Mathematical Model Behind RADFRAC

Qc

V

₂ Stage f-1

D

Q

L

2 Stage2 vik V H Stage k-1 l_ik-1 L h v_if V_fH_f l_if-1 L_if-1h_{f- 1} V_if+V_if V_iF

D

L

₁ Stagef

F

S

Stagep v_ik+1 V_k=1H_K+ V_kH_K l_ik L_kh_K Stage k L₁k-1 h K-v_if+1 l_if l_if-1+l_iF l_iF Stage f

B

StageN

S

Stagep

Overall Column Model

1

Simple Stage Model

V_f+1H_f+1 L_jh_f

Feed Stage Model

+l l 0 l L F l 0

Overall Column Model

F_i+S_i-D_i-B_i=0 F+S-D-B=0 v_ik+1+l_ik-1-v_ik-l_ik=0 V_k+1+L_k-1-V_k-L_k=0 v_if+1+l_if-1+L_iF-v_if-l_if=0 V_f+1+L_f-1+F_f–V_f– L_f=0

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Mathematical Model Behind RADFRAC

The Equilibrium Equation The Summation Equation

y_{ik =} K_ikx_{ik OR}v_ik/ V_{k =}K_ikl_ik/ L_k K_{ik =}K_ik( T_k,P_k, x_ik y_ik )

For Liquid Phase ∑c

i xik –1 = 0

or ∑c _{l / L} _{1 = 0}

For Vapor Phase ∑c i yik –1 = 0 or ∑c _{v / V} _{1 = 0} ik = ik( k, k, ik , yik ) or ∑c i lik/ Lk –1 = 0 or ∑c i yik/ Kik –1 = 0 or ∑c i vik/ Vk –1 = 0 or ∑c i Xik Kik –1 = 0

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Mathematical Model Behind RADFRAC

Overall Energy Balance for Column

FH_F-DH_D-Bh_B+SH_S-Q_C=0

For Condenser

V₂H₂+L₁h₁-DH₁-Q_c = 0

For Simple Stage

V_k+1H_k+1+L_k-1h_k-1-L_kh_k-V_kH_k=0

2 2 1 1 1 Qc

H_{k =}H_k( T_k,P_{k ,}y_ik)

For Feed Stage

FH +V H +L h -L h -V H =0

h_{k =}h_k( T_k,P_{k ,}x_ik)

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Exercise

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Exercise

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Aspen Plus for Process

Design and Simulation

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Course Agenda

• Aspen Tech Products and Aspen Plus BasicsAspen Tech Products and Aspen Plus Basics

• HEATX and Heat Exchanger Modelling

• RADFRAC and Distillation Column Modelling

Unit Operation Models

• Unit Operation Models • Sensitivity Analysis

i l k h

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Course Agenda (Day –3)

• Aspen Tech Products and Aspen Plus BasicsAspen Tech Products and Aspen Plus Basics

• Physical Properties Model and Properties Estimation

• HEATX and Heat Exchanger Modelling • HEATX and Heat Exchanger Modelling

• RADFRAC and Distillation Column Modelling

Unit Operation Models

• Unit Operation Models • Sensitivity Analysis

i l k h

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Sensitivity Analysis using

Resource Person

Dr. Naveed Ramzan

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Steps for Sensitivity Analysis

P it Purity (mole fraction) of cumene in Product Stream Stream

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Steps for Sensitivity Analysis

P it Purity (mole fraction) of cumene in Product Stream Stream

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Steps for Sensitivity Analysis

COOL COOL

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Steps for Sensitivity Analysis

COOL COOL

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Exercise

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Exercise

Thermodynamic Model

What would be the effect of flow rate of phenol on

MCH distillate purity, Condenser duty, reboiler duty

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Aspen Plus for Process Design and

Simulation

Final Workshop

Resource Persons

Prof. Dr. Shahid Naveed Dr. –Ing. Naveed Ramzan Mr. Farhan Ahmad

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Aspen Plus - Module I

Aspen Plus for Process

Design and Simulation

Design and Simulation

Resource Persons

Course Agenda

Course Agenda (Day – 1)

Course Agenda (Day – 2)

Course Agenda (Day – 3)

Role of Simulation in

Process Design

Process Design

Resource Persons

Simulation

Modelling and Simulation

1: What is Modeling

Description

of

any

complete

system

in

mathematical terms is called a mathematical

model

model

2: What is Simulation

2: What is Simulation

Solving

the

modeling

equations

either

numerically or analytically

Simulation and Modelling Problem in

Process Engineering

Nano

Micro

Meso

Macro

Mega

Why Process Simulation

Process Simulation Tools

Simulations tools can help to resolve several of these

problems, with low cost, high reliability and normally in less

problems, with low cost, high reliability and normally in less

time. Otherwise these tools can help to the process engineer

to understand what happen, and what are the problematic

points in the whole process or in a particular equipment

points in the whole process, or in a particular equipment.

These tools can be classified in three groups depending on

the problem that are going to be resolved:

Æ

Process Simulation tools.

Æ

A computational fluid dynamics (CFD) tools.

Æ

Other particular simulation software

Process Simulation Tools

Objectives of Process Simulation Tools:

Optimizing the design and performance of product assets

Opt

g t e des g a d pe o

a ce o p oduct assets

 Increasing throughput and yield improving quality and

 Increasing throughput and yield, improving quality, and

reducing energy costs

 Responding more quickly to unexpected events or

changes in customer demand

g

 Managing the profitability of operations in real time

Types of Process Simulation Tools

In process engineering two types of simulations tools are

used:

used:

Æ

Steady-State Simulators:

Or Static simulators.

Typically used in process design, they simulate the

yp

y

Optimizing the design and performance of product assets

Increasing throughput and yield improving quality and

Increasing throughput and yield, improving quality, and

Responding more quickly to unexpected events or

Managing the profitability of operations in real time