programa doutoral em engenharia da refinação, petroquímica...

25-02-2011

teste 1

Programa doutoral em Engenharia da Refinação, Petroquímica e Química

Engenharia de Processos e Sistemas

Process Simulators

Fernando G. Martins

Departamento de Engenharia Química

Faculdade de Engenharia da Universidade de Porto

Programa EngIQ - EPS

FGM (FEUP) - February 2011 Slide #1

Module objective and module contents

Module contents

• Overview of process simulation;

• Comparison between hand and computer calculation;

• Types of chemical process problems;

• Solution of problems in steady-state mode;

• Systematic methodology in process simulation;

• Process simulators – examples.

Module objective

To present the potentialities of software tools to solve problems related with design and

revamping of chemical processes.


FGM (FEUP) – February 2011 Slide #2

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teste 2

Process simulation - I

• Simulation is the tool that chemical engineers use:

– To analyse process flowsheets;

– To locate process malfunctions;

– To predict the performance of the processes.

• Mathematical models are the basis for simulation which correspond a collection

of equations that relate the process variables, such as stream temperature,

pressure, flow rate, and composition, to surface area, valve settings geometrical

configuration , and so on.



Process simulation - II

• Simulation models can be composed by different levels of complexity involving

material balances, material and energy balances, equipment sizing and

profitability analysis;

• Additional equations are added at each level. New variables are introduced and

the equation-solving algorithms become more complicated;

• Most chemical process involve conventional process equipment:

– Heat exchangers;

– Pumps;

– Distillation columns;

– and so on.



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teste 3

Process simulation - III

• For the process units referred in the previous slide:

– The equations do not differ among chemical processes;

– The physical and thermodynamic properties and chemical kinetic constants

differ, but not the equations.

• It is possible to develop one or more equation-solving algorithms for each

process unit to solve the material and energy balances and to compute

equipment sizes and costs. These algorithms are the heart of process simulators.

These algorithms are often referred as procedures, modules or blocks.



The importance of the process simulation

•• Conception/DesignConception/Design: Analysis of different process conditions and calculation of

operational variables;

•• StartStart--upup: Prediction of operational conditions through the plants start-up;

•• OperationOperation: Studies of the limit operation conditions and changes in project

specifications;

•• OptimizationOptimization: : Changing of the operation parameters to process optimization

attending to economic, energy, time and environment objectives.



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teste 4

Main steps in process simulation

Analysis of

the results

Problem Problem

definitiondefinition

Process model

development

Additional data

collection

Solving model

equations



Problem definition – which can be selected from simulator?

• Components;

• Unit operations;

• Process flowsheet;

• Libraries

– Unit operation models;

– Models to estimate termophysical properties;

– Equation solving methods.



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teste 5

Problem definition – required information

• Components;

• Unit operations;

• Process flowsheet;

• Thermophysical properties estimation;

• Data that must be knowing:

– Data for input streams;

– Equipment data;

– Operation data.



Types of process simulation problems

• Flowsheeting;

• Specification;

• Optimization;

• Synthesis.



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teste 6

Flowsheeting problem

FlowsheetFlowsheet

Inputs Outputs

Operational conditions

Equipment

parameters

Calculation of all output information and some internal variables using all

information from the inputs.



Specification problem - performance

Flowsheet

Inputs Outputs

Operational conditions Equipment

parameters

Some data from the outputs are specified. The other variables are predicted from models.

Some data from inputs needn't be specified.



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teste 7

Optimization problem

Data::

- Feed composition

- Feed flowrate

Select::

-Target product composition

-Column trays, feed composition

Minimize

Objective=f(yield, energy, capital costs, ...)



Synthesis problem

?

Inputs Outputs

Inputs and outputs are known but the flowsheet, the equipment

parameters and the operational conditions are unknown.



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teste 8

Example of a synthesis problem

Technology ?

Design ?

Inputs Outputs

Separation technology – distillation, flash, extraction, separation

based on membranes.

How many unit operations are needed?

How is the equipment design performed?

Ethanol

WaterEthanol

Water



Solution of problems in steady-state mode - summary

Sequential-modular approximation Equation-oriented approximation

Each unit operation is simulated at once All unit operations are simulated at once

The flowsheet is decomposed The equations are sorted

Iterative procedures using tear-streams All variables are updated at once

Less flexible but more robust More flexible but less robust

The initialization is important The initialization is much important

Memory requirements not very high Memory requirements may be very high



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teste 9

Systematic methodology in process simulation

• Data collection and reconciliation;

• Perform additional measures if necessary;

• Creation/adaptation of models of the equipments involved;

• Model validation;

• Model optimization.



Modular process simulator - I

Databases (Termophysical properties, model parameters, etc)

Interfaces to introduce information and to see results

Simulator

core

Numerical

methods

Model

libraries

Cost models

Properties

estimation



25-02-2011

teste 10

Modular process simulators - II

• Computer-aided process design programs, often referred as process or simulators,

flowsheet simulators or flowsheeting packages, are widely used in process design;

• These packages are comprised of the data banks, physical properties models, and

equipment operation and sizing models;

• The extensive data banks contain data on the thermophysical and transport property

constants for hundreds of chemicals, equipment sizing, capital and operating costs and

profitability measures;

• The simulators contain many models of the reactors and unit operation, so-called

simulation models that can be used to calculate material and energy balances.



Modular process simulators - III

• Simulators sometimes give wrong results, even though no error messages appear. Therefore,

simulation results need to be checked carefully before being used as a basis for process and

equipment design;

• It is particularly important to verify the heat and mass balances for any simulation.

Otherwise, you might develop an incorrect design;

• The checks that must be done:

– Input data – are units and numerical values correct;

– Model scope – Is the simulator model scope sufficient to define the problem and thus

obtain meaningful results;

– Thermophysical property models – Is the vapor/liquid equilibrium model used

appropriate for the mixture being modelled and for the range of temperatures,

pressures and compositions simulated;



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teste 11

Modular process simulators - IV

• The checks that must be done (cont.):

– Thermophysical properties computed – Are calculated values of operating conditions

and stream properties reasonable for all streams;

– Specifications – Did the simulator converge on all specifications;

– Process equipment – Are the parameters and variables used for sizing and specifying

such equipment reasonable? Are the equipment sizes reasonable?

• In conclusion – If a process simulator is used properly and well, the results can be very

beneficial; if not use careful and wisely, the consequences may be dire.



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