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

1/25/2014 Computer-Aided Chemical Engineering An Introduction to Process Simulation C1 Computer Simulation in Process Engineering Computer Simulation in Process Engineering Computer Simulation in Process Engineering An Historical View Approach of A Simulation Problem 3.1 Definition 3.2 Input 3.3 Execution 3.4 Results Analysis Architecture of Flowsheeting Software 4.1 Computation Strategy 4.2 Sequential-Modular Approach 4.3 Equation-Oriented Approach 4.4 Simultaneous-Modular Approach Integrated systems (Aspen Technology; Hyprotech; Simulation Sciences) Selection of A Simulation Software (Functional Analysis; Computer Science Analysis; Commercial Analysis) Summary 1/25/2014 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 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 1/25/2014 Computer Simulation in Process Engineering Figure 1: The new paradigm of Process Engineering: Simulation as core activity in Research & Development, Design and Operation 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 1/25/2014 Figure 2: Applications of steady state and dynamic Plant Simulation Models 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 1/25/2014 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 Approach of A Simulation Problem Figure 3: Methodological levels in steady-state simulation 1/25/2014 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 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 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 1/25/2014 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 Approach of A Simulation Problem 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 1/25/2014 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 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 1/25/2014 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 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 1/25/2014 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 Architecture of Flowsheeting Software Figure 4: General layout of unit operation model 10 1/25/2014 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 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 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) 11 1/25/2014 Architecture of Flowsheeting Software Figure 5: Software architecture of a Sequential-Modular simulator 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 %) 12 1/25/2014 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 Architecture of Flowsheeting Software The software architecture built with an EO approach is presented in Fig 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 13 1/25/2014 Architecture of Flowsheeting Software Figure 6: Software architecture of an Equation-Oriented simulator 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 14 1/25/2014 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 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) 15 1/25/2014 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 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 Selection of A Simulation Software 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 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 16 1/25/2014 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 presents a sample of the main commercial software at the end of 2001 Selection of A Simulation Software Table 2: Process Design & Simulation commercial software Supplier Aspen Tech Cambridge-MA/USA Chemstations Houston-USA Hyprotech Calgary-Canada Prosim Toulouse-France Simulation Science Los Angeles-USA WinSim Houston-USA Imperial College London-UK Bryan Research & Engineering 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 17 1/25/2014 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 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 18