Tin học ứng dụng trong công nghệ hóa học C1 tin hoc trong cn hoa hoc tieng a nh

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Computer-Aided Chemical
Engineering
An Introduction to Process Simulation

C1. Computer Simulation
in Process Engineering

Computer Simulation in Process Engineering
1. Computer Simulation in Process Engineering
2. An Historical View
3. Approach of A Simulation Problem
3.1. Definition
3.2. Input
3.3. Execution
3.4. Results
3. 5. Analysis
4. Architecture of Flowsheeting Software
4.1 Computation Strategy
4.2 Sequential-Modular Approach
4.3 Equation-Oriented Approach
4.4 Simultaneous-Modular Approach
5. Integrated systems (Aspen Technology; Hyprotech; Simulation Sciences)
6. Selection of A Simulation Software (Functional Analysis; Computer
Science Analysis; Commercial Analysis)
7. Summary

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1. Computer Simulation in Process Engineering
Simulation is a fundamental activity in Process Engineering. The following
definition captures its essential features (Thomeù, 1993):
Simulation is a process of designing an operational model of a system and
conducting experiments with this model for the purpose either of
understanding the behaviour of the system or of evaluating alternative
strategies for the development or operation of the system. It has to be able
to reproduce selected aspects of the behaviour of the system modelled to an
accepted degree of accuracy.
Simulation implies modelling, as well as tuning of models on experimental
data. A simulation model serves to conduct 'virtual experiments'. Almost
invisible in most cases, being incorporated in the software technology,
modelling is the key feature in every simulation. It is important to keep in
mind that the simulation is only an approximate representation of the reality,
at a certain level of accuracy, and not the reality itself. That is why the user
must always be able to evaluate the reliability of the results delivered by a
simulator.
Simulation in Process Engineering requires specific scientific knowledge
among we may cite accurate description of physical properties of pure
components and complex mixtures, models for a large variety of reactors
and unit operations, as well as numerical techniques for solving large
systems of algebraic and differential equations.

1. Computer Simulation in Process Engineering
The main simulation activity in process engineering is flowsheeting. Following a
previous definition (Westerberg et al., 1979) flowsheeting is the use of

computer aids to perform steady state heat and mass balancing, sizing and

costing calculation for a chemical process.

Taking into account the evolution in the last decades, we may formulate a
more extended definition as:
Flowsheeting is a systemic description of material and energy streams in a
process plant by means of computer simulation with the scope of designing a
new plant or improving the performance of an existing plant. Flowsheeting
can be used as aid to implement a plantwide control strategy, as well as to
manage the plant operation.

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1. Computer Simulation in Process Engineering
Figure 1: The new paradigm of Process Engineering: Simulation as core
activity in Research & Development, Design and Operation

1. Computer Simulation in Process Engineering
Table 1: Process Simulation applications in Chemical Process Industries
Chemical Process Industries
Applications
Oil & Gas
Offshore exploration, Surface treatment,
Pipeline transport, Underground storage,
Gas processing
Refining
Gasoline and fuels
Petrochemicals

Hydrocarbon based chemicals, Methanol,
Monomers
Basic Organic Chemicals Intermediates, Solvents, Detergents, Dyes
Inorganic Chemicals
Ammonia, Sulphuric Acid, Fertilisers
Fine Chemicals
Pharmaceuticals, Cosmetics
Biotechnology
Food and bio products
Metallurgy
Steel, Aluminium, Copper, etc.
Polymers
Polyethylene, PVC, Polystyrene, fibres, etc.
Paper & Wood
Paper pulp
Energy
Power plants, Coal gasification
Nuclear industry
Waste treatment, Safety
Environment
Water cleaning, Biomass valorisation

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Figure 2: Applications of steady state and dynamic Plant Simulation Models

2. An Historical View

The story of process simulation began in 1966, when Simulation Science, a
small company located in Los Angeles/USA, had the idea to commercialise
a generic computer program for simulating distillation columns. This was
the heart of a flowsheeting package, PROCESS (precursor of PRO II,
Simulation Science), which might be considered the ancestor of process
simulators. Three years later ChemShare (Houston/USA) released
DESIGN (continued with DESIGN II and WINSIM), a capable flowsheeting
program for gas & oil applications. At that time, the expansion of the refining
and petrochemical industries motivated the advent of computer packages.
The first world oil crisis in 1973 has greatly stimulated the interest in
simulating processes with alternative raw materials, as coal and biomass. In
1976, US Dept. of Energy and MIT launched jointly the ASPEN project
(continued by ASPEN PLUS, ASPEN Tech). The advent of high-speed
computation systems boosted the business of small companies specialised
in modelling and simulation. More generally, the scientific computation
evolved from individual programs to large packages designed as industrial
products.

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2. An Historical View
Personal Computer arrived in 1982. Although the power of PC's was weak
for flowsheeting, the idea of a 'personal' tool was strong enough to incite
enthusiasts (development of ChemCAD, ChemStations and Hysys,
Hyprotech). The challenge of leaving the elitist environment of mainframes
was launched.
At the beginning of 1990's the domination of PC products was a fact. The

relative stabilisation in operating systems, dominated nowadays by UNIX
and Windows, enabled the development of new generation of simulation
software. The Graphical User Interface became a central part in the
software development. The power of the former super-computers was
available on desktops.

3. Approach of A Simulation Problem
Figure 3: Methodological levels in steady-state simulation

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3. Approach of A Simulation Problem
3.1. Definition
A real Process Flow Diagram (PFD) must be translated in a scheme
compatible with the software capabilities and with the simulation goals. The
flowsheet scheme built up for simulation purposes will be called Process
Simulation Diagram (PSD). PSD is in general different from PFD. For
example, some simple units, as for pressure or temperature change, may
be lumped in more complex units (from simulation viewpoint). Contrary,
complex units, as distillation columns or chemical reactors, may need to be
simulated as small flowsheets. Hence, a preliminary problem analysis is
necessary. The steps in defining a simulation problem are:
- Convert PFD in PSD. Split the flowsheet in several sub-flowsheets, if
necessary.
- Analyse the simulation model for each flowsheeting unit.
- Define chemical components, including user-defined or petroleum
fractions.

- Analyse the thermodynamic modelling issues regarding the global
flowsheet, subflowsheets and key units.
- Analyse the specification mode (degrees of freedom) of complex units.

3. Approach of A Simulation Problem
3.2. Input: The input of a flowsheeting problem depends on the software
technology. This activity is normally supported by a Graphical User Interface
(GUI). The steps are:

- Draw the flowsheet.
- Select the components, from standard database or user defined.
- Specify the input streams.
- Specify the units (degrees of freedom analysis).
- Select the thermodynamic models. Check model parameters.
- Determine the computational sequence.
- Initialise tear streams and difficult units. Note that correct specifications do not
always mean feasible specifications.

3.3. Execution: The simulation is successful when the convergence criteria
are fulfilled both at the flowsheet and units' level. The user should pay
particular attention to convergence history for troubles shootings. Here the
steps involved are:
- Check the convergence algorithms and parameters, and change them if
necessary.
- Check the convergence errors and the bounds of variables.
- Follow-up convergence history.

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3. Approach of A Simulation Problem
3.4. Results
A simulation delivers a large amount of results. The most important are:
- Stream report (material and heat balance), including flowsheet
convergence report.
- Unit report, including material and heat balance, as well as unit
convergence report.
- Rating performances of units.
- Tables and graphs of physical properties.
The graphical presentation of results may take various forms. Generally,
advanced software provides their own analysis tools, but the exchange of
data with all-purpose spreadsheets is usually available. Detailed results, as
internal flows or tables of properties, may be exported to specialised design
packages.

3. Approach of A Simulation Problem
3. 5. Analysis
Flowsheeting analysis tools enable to get more value from the simulation
results. The most used is the sensitivity analysis. This consists usually of
recording the variation of some 'sampled variables' as function of
'manipulated variables'. The interpretation of results can be exploited
directly, as trends, correlation or pre-optimisation. Case studies can be
employed to investigate combinations (scenarios) of several flowsheet
variables. Finally, the simulation work may be refined by multi-variable
optimisation.
A more advanced use of flowsheeting capabilities is the controllability
analysis of standalone units, or the study of a plantwide control strategy.

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4. Architecture of Flowsheeting Software
4.1 Computation strategy
The architecture of a flowsheeting software is determined by the strategy of
computation. Three basic approaches have been developed over the years:
- Sequential-Modular;
- Equation-Oriented;
- Simultaneous-Modular.
A. In Sequential-Modular (SM) architecture, the computation takes place
unit-by-unit following a calculation sequence. A process with recycles must
be decomposed in one or several calculation sequences. Each of these
begins at a certain place, where the incoming streams have to be known
either as inputs, or initialised as tear streams. The computation sequence of
units involved in a recycle defines a convergence loop. When tear streams
are present, the final steady state solution is obtained by iterative
calculations. Tear streams are modified (accelerated) after successive
iterations by applying an appropriate convergence algorithm. The
computation stops when both the units and the tear streams satisfy some
convergence criteria, usually the closure of the material and heat balance.
The SM architecture was the first used in flowsheeting, but still dominates
the technology of steady state simulation.

4. Architecture of Flowsheeting Software
Among the advantages of the SM architecture we may cite:
- Modular development of capabilities.
- Easy programming and maintenance.

- Easy control of convergence, both at the units and flowsheet level.
There are also disadvantages, as for example:
- Need for topological analysis and systematic initialisation of tear streams.
- Difficulty to treat more complex computation sequences, as nested loops
or simultaneous flowsheet and design specification loops.
- Difficulty to treat specifications regarding internal unit (block) variables.
- Rigid direction of computation, normally 'outputs from inputs'.
- Not well suited for dynamic simulation of systems with recycles.
Some modifications have been proposed to improve the flow of information
and avoid redundant computations. Among these we may mention the bidirectional transmission of information implemented in HysysTM.

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4. Architecture of Flowsheeting Software
B. In Equation-Oriented (EO) approach all the modelling equations are
assembled in a large sparse system producing Non-linear Algebraic
Equations (NAE) in steady state simulation, and stiff Differential Algebraic
Equations (DAE) in dynamic simulation. Thus, the solution is obtained by
solving simultaneously all the modelling equations.
Among the advantages of the equation-solving architecture we may
mention:
- Flexible environment for specifications, which may be inputs, outputs, or
internal unit (block) variables.
- Better treatment of recycles, and no need for tear streams.
- Note that an object oriented modelling approach is well suited for the EO
architecture.
However, there are also substantial drawbacks, as:

- More programming effort.
- Need of substantial computing resources, but this is less and less a
problem.
- Difficulties in handling large DAE systems.
- Difficult convergence follow-up and debugging.

4. Architecture of Flowsheeting Software
C. In Simultaneous-Modular approach the solution strategy is a combination
of Sequential-Modular and Equation-Oriented approaches. Rigorous
models are used at units' level, which are solved sequentially, while linear
models are used at flowsheet level, solved globally. The linear models are
updated based on results obtained with rigorous models. This architecture
has been experimented in some academic products.
It may be concluded that Sequential-Modular approach keeps a dominant
position in steady state simulation. The Equation-Oriented approach has
proved its potential in dynamic simulation, and real time optimisation. The
solution for the future generations of flowsheeting software seems to be a
fusion of these strategies. The release 11.1 of Aspen Plus (2002)
incorporates for the first time EO features in the environment of a SM
simulator.

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4. Architecture of Flowsheeting Software
4.2 Sequential-Modular approach
Sequential-Modular approach is mostly used in steady state flowsheeting,
among we may cite as major products Aspen Plus, ChemCad, Hysys, ProII,

Prosim, and Winsim (see Table 2.2 for information). However, there are
some dynamic simulators built on this architecture, the most popular being
Hysys.
The basic element in a modular simulator is the unit operation model. A
simulation model is obtained by means of conservation equations for mass,
energy and momentum. These lead finally to a system of non-linear
algebraic equations as:
f(u,x,d,p)=0
(1)
Here the notations signify:
- u, connectivity variables formally classified in input and output variables;
- x, internal (state) variables, as temperatures, pressures, concentrations;
- d, variables defining the geometry, as volume, heat exchange area, etc;
- p, variables defining physical properties, as specific enthalpies, K-factors,
etc.

4. Architecture of Flowsheeting Software
Figure 4: General layout of unit operation model

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4. Architecture of Flowsheeting Software
Note that the system (1) has a strong non-linear character, particularly due
to the interdependence between physical properties and state variables. It
is important to keep in mind that physical properties may consume up to
90% from the computation time. The above system should be seen as
completed with equations for constraints.

The difference between the total number of non-redundant variables in the
system (1) and the number of independent algebraic equations gives the
degrees of freedom. These are usually specifications that a user must
supply to run a simulation.
In SM approach each simulation unit (block) is treated by the rule:
output variables = function {input variables, unit variables, unit parameters}
The functional relation is specific for each unit, as flash, pump, reactor,
distillation column, etc. Because of a large variety of physical situations, it is
rational to incorporate a part of the algorithm in the routine that solves the
unit. From programming point of view it is said that the approach is
procedural.

4. Architecture of Flowsheeting Software
The architecture of software is a matter of computer science. However, as
with every complex system, the user should be aware about the main
elements. Figure 5 presents a generic architecture of a Sequential-Modular
simulator. The heart of the system is the Executive Program. Its function is
to manage both computation and data exchange tasks, as for example
calculation sequence, retrieval of parameters for physical properties,
routines for unit operations, convergence follow-up, and management of the
data file system. Other essential components are:
- Databases with physical parameters for pure components and mixtures.
- Librarian for computing physical properties of components and mixtures.
- Librarian for physical and chemical equilibrium calculations.
- Librarian for unit operations and reactors.
- Librarian with mathematical Solvers.
- Graphical User Interface (GUI).

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4. Architecture of Flowsheeting Software
Figure 5: Software architecture of a Sequential-Modular simulator

4. Architecture of Flowsheeting Software
From the above description, we may conclude that
flowsheeting software is a very sophisticated computer-based
system, and not a collection of algorithms for solving different
unit operations. A process simulator must be designed with
computer science development and management tools. It is
interesting to note that in the total cost the software
maintenance (typically more than 70 %) is by far more
important than the cost of programming (typically under 10 %).

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4. Architecture of Flowsheeting Software
4.3 Equation-Oriented approach
In Equation-Oriented (EO) approach the software architecture is close to a
solver of equations. EO is more suited for dynamic simulation since this can
be modelled by a system of differential-algebraic equations (DAE) of the
form:
dx
--- = f (u,x,d,p) (2)
dt

The steady state solution is obtained by setting the derivatives to zero. The
overall DAE system (2) is sparse and stiff, its size varying between 103 and
105 equations.
Dynamic simulation is more demanding as its steady state counterpart.
Firstly, it needs much more sizing elements. Then, the pressure variation
cannot be neglected or lumped in the specification of simulation unit.
However, in general the specification of variables is more flexible. Any
flowsheet variable could be set as input or output streams, or internal unit
variables.

4. Architecture of Flowsheeting Software
The software architecture built with an EO approach is presented in Fig. 6.
The input of the simulation problem can be formulated by means of a metalanguage, or be supported by an intelligent GUI. In Aspen Dynamics, the
problem definition starts at steady state in Aspen Plus in an SM
environment. Adding accumulation terms to the equations of units
generates the DAE system.
In an EO simulator the algorithmic treatment includes not only the
mathematical solution, but also problem debugging, compilation/linking, as
well as correction and addition of equations. An important feature is the
post-processing of results, as timerecordings and plots of different
variables.

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4. Architecture of Flowsheeting Software
Figure 6: Software architecture of an Equation-Oriented simulator

5. Integrated Systems
Three major integrated simulation systems will be shortly presented.
Update information may be found by consulting the respective web sites.
5.1 Aspen Technology
The integrated system includes both all-purpose flowsheeting system, and
specialised packages. Different packages communicate via specific files,
but share the same physical property methods and data. Here we mention
only the major components.
- Aspen Plus: steady state simulation environment with comprehensive database
and thermodynamic modelling; feasibility studies of new designs, analysis of
complex plants with recycles, optimisation.
- Aspen Dynamics: dynamic flowsheeting interfaced with Aspen Plus.
- Aspen Custom Modeller: modelling environment for user add-on units and
programming in dynamic simulation.
- Aspen Pinch: Pinch analysis, optimal design of heat exchanger networks.
- Aspen Split: synthesis and design of non-ideal separation systems.
- Polymer Plus: simulation of polymerisation processes.
- Aspen Properties: physical property system including regression capabilities and
estimation methods.
- Aspen OLI: simulation of aqueous electrolyte systems.
- Batch Plus: recipe-oriented batch process modeling.
- Batchfrac: batch reactions and separation processes.
- RTO: real time plant optimisation based on rigorous models.
- Aspen Zyqad: database environment for engineering projects.

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5. Integrated Systems
5.2 Hyprotech
The special feature of the flowsheeting system proposed by Hyprotech is
that steady state and dynamic simulation are available in the graphical
environment. Other products have been developed as stand-alone
applications for engineering or operation purposes. The system is designed
for complete customisation. The main components are:
- Hysys.Concept: conceptual design package for design and retrofit applications,
with two components:
 DISTIL: distillation column sequences,
 HX: heat integration projects by Pinch analysis.
- Hysys.Process: steady state flowsheeting for optimal new designs and modelling
of existing plants, evaluate retrofits and improve the process.
- Hysys.Plant: steady state and dynamic simulation to evaluate designs of existing
plants, and analyse safety and control problems.
- Hysys.Operator Training: start-up, shutdown or emergency conditions, consisting
of an instructor station with DCS (Distributed Control System) interface, and
combined with Hysys.Plant as calculation engine.
- Hysys.RTO+: real-time multivariable optimisation; on-line models may be used
offline to aid maintenance, scheduling and operations decision-making.
- Hysys.Refinery: rigorously modelling of complete refining processes, integrating
crude oil database and a set of rigorous refinery reactor models.
- Hysys.Ammonia: full plant modelling and optimisation of ammonia plants.

5. Integrated Systems
5.3 Simulation Sciences
The integrated system proposed by Simsci is built around a database
environment (PROVISION), and can be in principle interfaced with thirdparty components. The system is oriented to applications in oil & gas
industries, as described below.
Process Engineering: tools for process engineering design and operational

analysis.
- Pro/II: general-purpose process flowsheeting and optimisation.
- Hextran: Pinch analysis and design of heat-transfer equipment.
- Datacon: plant gross error detection and data reconciliation.
- Inplant: multiphase, fluid flow simulation for plant piping networks.
- Visual Flow: design and modelling of safety systems and pressure relief networks.

Upstream Optimisation: decision-support tools designed for oil and gas
production.
- Pipephase: multiphase fluid flow simulator for pipelines and networks.
- Tacite: multiphase simulator for complex transient flow phenomena.
- Netopt: optimisation of oil and gas production operations.

On-line Performance: Advanced Process Control (APC) and on-line
optimisation.

- ROMeo: on-line plant modelling and optimisation, off-line analysis tool.
- Connoisseur: APC multivariable controls several via the plant's DCS (Distributed
Control System).

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6. Selection of A Simulation Software
The selection of a simulation system is a strategic decision for an
organisation. It implies a medium/long term co-ordination policy, both in
hardware platforms and in scientific software, as well as in the training of
personnel, compatibility with third parties environment, etc. The procedure

described below may be applied for a low-risk choice of any scientific
software. The evaluation procedure takes the form of a questionnaire, as
given hereafter.
1. Functional Analysis

- Typical applications.
- Capabilities and options.
- User interface.
- Algorithms and numerical methods.
- Complementary products.
- Databases" size, applications, quality of data.
- Post-treatment of results.
- Typical benchmarks and library of examples.
- User manual

6. Selection of A Simulation Software
2. Computer Science Analysis

- Hardware: platforms and operating systems.
- Resources: hard disk space, typical user space, memory.
- Software analysis: architecture, file structure, programming languages.
- Graphical User Interface: functions, portability.
- Use of standards: graphics, communication, portability.
- Software development tools and quality control.
- Interface with known scientific or all-purpose software.
- Customisation.

3. Commercial Analysis

- Social reason, shareholders, financial report.

- Commercial politics: market, clients, prices.
- Training and user support.
- Maintenance and updates.
- Communication politics: users group meetings, newsletter
- Academic and scientific contacts, publications.

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6. Selection of A Simulation Software
Each question is quoted by a mark and weighted by a factor. Consequently,
this procedure will produce a list of two or three good candidates. The final
choice will imply a finer assessment of the above aspects. More information
may be asked by experts, as benchmarks, customised demonstrations,
programming samples, quality assurance documents, etc. In this respect it
is important to test the product on problems close to the user application
area.
Despite similar functionalities among generalist suppliers, every system has
capabilities where it performs better than others. This could have historical
reasons, or could come from the profile of clients. The reliability of physical
properties and of parameters in thermodynamic models is an essential
feature in design. That is why the quality of thermodynamics is a peculiar
feature in selecting a simulation system for process design purposes. Other
important features are customisation of units, programming capabilities,
transmission of information and control structures, as well as debugging
convergence problems with recycles. A system in which the user has the
control on all the aspects of the modelling background should be preferred.
As mentioned, the process simulation market has known severe

transformations in the 1985-1995 decade. Relatively few systems have
survived. Table 2 presents a sample of the main commercial software at the
end of 2001.

6. Selection of A Simulation Software
Table 2: Process Design & Simulation commercial software
Supplier
1 Aspen Tech
Cambridge-MA/USA

2 Chemstations
Houston-USA
3 Hyprotech
Calgary-Canada
4 Prosim
Toulouse-France
5 Simulation Science
Los Angeles-USA

6 WinSim
Houston-USA
7 Imperial College
London-UK
8 Bryan Research &
Engineering
9 KBC/Linnhoff March
10 Intelligen, Scotch Plains,
NJ-USA

Software

Aspen Plus
Aspen Dynamics
Advent
Split
Bijac
Polymer Plus
Batchfrac
ChemCad
CC-ReACS
Hysys
Concept
Hyprop
ProSim

Applications
Flowsheeting, sizing, costing
Dynamic Simulation, Real time systems
Energy Integration
Non-ideal Distillation Systems
Heat exchanger design
Polymer processes
Batch and semi-continuous processes
Flowsheeting, sizing, costing
Batch reactor simulator
Combined steady state and dynamic simulation
Non-ideal Distillation Systems
Thermodynamics
Flowsheeting

Pro II

Provision
Hextran
Datacon
ROMeo
Design II

Flowsheeting, sizing
Graphical environment
Energy Integration
Data reconciliation
Rigorous on-line modelling
Flowsheeting, sizing

g_PROMS

Dynamic Simulation

Prosim
Tsweet
Supertarget
BatchPro Designer

Flowsheeting
Gas purification
Energy integration
Scheduling and Design of batch processes

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7. Summary

Process Simulation is a key activity in Process Engineering covering the
whole life cycle of a process, from Research & Development to Conceptual
Design and Plant Operation. In this context, flowsheeting is a systemic
description of material and energy streams in a process plant by means of
computer simulation with the scope of designing the plant or understanding
its operation.
Steady state flowsheeting is an everyday tool of the chemical engineer. The
generalisation of the dynamic simulation in the design practice is the next
challenge. By means of a capable commercial flowsheeting system, it is
possible to produce a comprehensive computer image of a running
process, a Plant Simulation Model, which can combine both steady state
and dynamic simulation. This tool is particularly valuable in understanding
the operation of a complex plant, and on this basis can serve for continuous
improving the process design, or for developing new processes.
Process simulation is based on models. A model should mirror the reality at
the degree of accuracy required by application. Having a good knowledge
of the modelling background is compulsory for getting reliable results and
using the software effectively. The difference between successful and failed
computer-aided project should be attributed more to an insufficient capacity
of the user to take advantage from the modelling environment than to
inadequate performance of the simulator. That is why a problem simulation
must be carefully prepared.

7. Summary
Flowsheeting is still dominated by the Sequential-Modular architecture, but
incorporates increasingly features of the Equation-Oriented solution mode.

A limited number of systems can offer both steady state and dynamic
flowsheeting simulators.
The integration of simulation tools is necessary to cope with the variety of
needs in process engineering. It is desirable to open the access to
simulation technology to a larger number of model suppliers. This can be
realised by a cooperative approach between the community of users and of
software producers. The availability of simulation systems on Internet can
boost the use of simulation technology in a global environment.

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