Foz do Iguaçu August 24 th , 2005 Dynamic Simulation GIMSCOP Group of Integration, Modeling, Simulation, Control, and Optimization of Processes PASI 2005 Pan American Advanced Studies Institute Program on Process Systems Engineering Argimiro R. Secchi Chemical Engineering Department
58
Embed
Secchi seminar Pasi2005 - CEPACcepac.cheme.cmu.edu/pasilectures/secchi/Secchi_seminar_Pasi2005.… · gPROMS. UFRGS 26 CAPE OPENCAPE OPEN Another example of CAPE-OPEN: EMSO (Environment
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Foz do IguaçuAugust 24th, 2005
Dynamic Simulation
GIMSCOPGroup of Integration, Modeling, Simulation,
Control, and Optimization of Processes
PASI 2005Pan American Advanced Studies Institute Program on Process Systems Engineering
Argimiro R. SecchiChemical Engineering Department
UFRGS
2
LocationLocation
BRAZIL
Iguazu Falls Porto Alegre940 km
•
••Gramado (ADCHEM 2006)
UFRGS
3
OutlineOutline
• When I need?
• How I use?
• What are the difficulties?
• What are the challenges?
Dynamic Simulation:
UFRGS
4
When I need Dynamic SimulationWhen I need Dynamic Simulation
• Batch and semi-batch processes
• Dynamic real-time optimization (D-RTO)
• Process control
• Startups, shutdowns and transitions
• Process intensification
• Teaching and training
UFRGS
5
Batch and Semi-Batch ProcessesBatch and Semi-Batch Processes
(Semi-)batch (bio)reactors
1
productreflux
Batch distillation
UFRGS
6
Analysis (Davies et al., 2004)
Batch and Semi-Batch ProcessesBatch and Semi-Batch Processes
L = 0.9 m , g = 9.8 m/s2 ∴ I.C.: x(0) = 0.9 m and w(0) = 0
UFRGS
41
Dynamic Simulation ModelDynamic Simulation Model
UFRGS
42
ChallengesChallenges
Robust strategies for on-line updating of dynamic models
Dynamic data reconciliation Parameter estimation
Related topics:• Hybrid and rigorous modeling• Order reduction of nonlinear models• Fault diagnosis• NMPC tuning strategies
UFRGS
43
ChallengesChallenges
DAE solvers
High-index (>3) solvers
Automatic/guided selection of feasible set of variables
for initial condition
Index reduction with trajectory projection
onto hidden manifold
UFRGS
44
ChallengesChallenges
Integrated tool for D-RTO
Multi-level dynamic simulator
Simultaneous data reconciliation and
parameter estimation tool
Dynamic optimizer with adaptive grid
Self-tuned nonlinear model predictive controller
Specialist system
UFRGS
45
ChallengesChallenges
Systems Interoperability
Truly CAPE-OPEN Heterogeneity and multi-platform
Single communication
protocolMulti-processing
and
Shared-memory advantages
UFRGS
46
ChallengesChallenges
Complex systems
Process simulation + CFD
Multi-scale modeling + simulation tools
Bifurcation + control system design
Hybrid modeling
UFRGS
47
OptimizationOptimization,,
RTO, DRTORTO, DRTO
Design
Design
Adv
ance
d
Adv
ance
d
Con
trol
Con
trol
Training,
Training, SafetySafety
Decision
Decision
Making
Making
Data
Data
Reconciliation
Reconciliation
Inferences
Inferences
Hierarchical Modeling
Hierarchical Hierarchical ModelingModeling
OptimizationOptimization,,RTO, DRTORTO, DRTO
DesignDesign
Advanced
Advanced
Control
Control
Training, Training,
SafetySafety
Decisio
n
Decisio
n M
aking
Mak
ing
Dat
a D
ata
Rec
onci
liatio
nR
econ
cilia
tion
Inferences
Inferences
ProcessProcessProcess
VisionVisionIntegrated
Environment Dual Space
UFRGS
48
ReferencesReferences
• Al-Arfaj, M. and W.L. Luyben. Comparison of Alternative Control Structures for an Ideal Two-Product Reactive Distillation Column. Ind. Eng. Chem. Res., 39, 3298–3307 (2000).
• Arpornwichanop, A., P. Kittisupakorn and I.M. Mujtaba. On-line Dynamic Optimization and Control Strategy for Improving the Performance of Batch Reactors. Chemical Engineering and Processing, 44, 101–114 (2005).
• BenAmor, Z., F.J. Doyle III and R. McFarlane. Polymer Grade Transition Control using Advanced Real-Time Optimization Software. Journal of Process Control, 14, 349–364 (2004).
• Bhagwat, A., R. Srinivasan and P.R. Krishnaswamy. Fault Detection During Process Transitions: a Model-Based Approach. Chemical Engineering Science, 58, 309–325 (2003).
• Biagiola, S.I. and J.L. Figueroa. Application of State Estimation Based NMPC to an Unstable Nonlinear Process. Chemical Engineering Science, 59, 4601–4612 (2004).
• Biegler, L.T., A.M. Cervantes and A. Wächter. Advances in Simultaneous Strategies for Dynamic Process Optimization. Chemical Engineering Science, 57, 575–593 (2002).
• Charpentier, J.C. and T.F. McKenna. Managing Complex Systems: Some Trends for the Future of Chemical and Process Engineering. Chemical Engineering Science, 59, 1617–1640 (2004).
• Costa Jr., E.F., R.C. Vieira, A.R. Secchi and E.C. Biscaia Jr. Dynamic Simulation of High-Index Models of Batch Distillation Processes. Journal of Latin American Applied Research, 32 (2) 155–160 (2003).
UFRGS
49
ReferencesReferences
• Davies, M.L., I. Schreiber and S.K. Scott. Dynamical Behaviour of the Belousov–Zhabotinsky Reaction in a Fed-Batch Reactor. Chemical Engineering Science, 59, 139–148 (2004).
• Elgue, S., L. Prat, M. Cabassud, J.M. Le Lann and J. Cézerac. Dynamic Models for Start-up Operations of Batch Distillation Columns with Experimental Validation. Computers and Chemical Engineering, 28, 2735–2747 (2004).
• Ferreira, L.S., J.O. Trierweiler, A.R. Secchi and S.M. Marcon. Development of a Virtual Analyzer Software for Bioprocesses. AIChE Annual Meeting, San Francisco, CA, USA, p. #107ak (2003).
• Gao, W. and S. Engell. Iterative Set-point Optimization of Batch Chromatography. Computers and Chemical Engineering, 29, 1401–1409 (2005).
• Grünera, S. and A. Kienle. Equilibrium Theory and Nonlinear Waves for Reactive Distillation Columns and Chromatographic Reactors. Chemical Engineering Science, 59, 901–918 (2004).
• Hahn, J., T.F. Edgar and W. Marquardt. Controllability and Observability Covariance Matrices for the Analysis and Order Reduction of Stable Nonlinear Systems. Journal of Process Control, 13, 115–127 (2003).
• Henson, M.A. Dynamic Modeling and Control of Yeast Cell Populations in Continuous Biochemical Reactors. Computers and Chemical Engineering, 27, 1185–1199 (2003).
• Iliuta, I. and F. Larachi. Modeling Simultaneous Biological Clogging and Physical Plugging in Trickle-Bed Bioreactors for Wastewater Treatment. Chemical Engineering Science, 60, 1477–1489 (2005).
UFRGS
50
ReferencesReferences
• Jockenhövel, T., L.T. Biegler and A.Wächter. Dynamic Optimization of the Tennessee Eastman Process using the OptControlCentre. Computers and Chemical Engineering, 27, 1513–1531 (2003).
• Kulikov, V., H. Briesen, R. Grosch, A. Yang, L. vonWedel and W. Marquardt. Modular Dynamic Simulation for Integrated Particulate Processes by Means of Tool Integration. Chemical Engineering Science, 60, 2069–2083 (2005).
• Lakner, R., K.M. Hangos and I.T. Cameron. On Minimal Models of Process Systems. Chemical Engineering Science, 60, 1127–1142 (2005).
• Lee, S., I. Jeong and I. Moon. Development of Evaluation Algorithms for Operator Training System. Computers and Chemical Engineering, 24, 1517-1522 (2000).
• Logsdon, J.S. and Biegler, L.T. Accurate Determination of Optimal Reflux Polices for the Maximum Distillate Problem in Batch Distillation. Ind. Eng. Chem. Res., 32 (4) 692-700 (1993).
• Longhi, L.G.S., D.J. Luvizetto, L.S. Ferreira, R. Rech, M.A.Z. Ayub and A.R Secchi. A Kinetic Model for the Kluyveromycesmarxianus Growth using Cheese Whey as Substrate. Journal of Industrial Microbiology, 31 (1) 35–40 (2004).
• Marquardt, W. and M. Mönnigmann. Constructive Nonlinear Dynamics in Process Systems Engineering. Computers and Chemical Engineering, 29, 1265–1275 (2005).
• Martinson, W.S. and P.I. Barton. Distributed Models in Plantwide Dynamic Simulators. AIChE Journal, 47 (6) 1372–1386 (2001).
UFRGS
51
ReferencesReferences
• Molnár, A., M. Krajciová, J. Markos and L. Jelemensky. Use of Bifurcation Analysis for Identification of a Safe CSTR Operability. Journal of Loss Prevention in the Process Industries, 17, 489–498 (2004).
• Reepmeyer, F., J.U. Repke and G. Wozny. Time Optimal Start-up Strategies for Reactive Distillation Columns. Chemical Engineering Science, 59, 4339–4347 (2004).
• Skogestad, S. Control Structure Design for Complete Chemical Plants. Computers and Chemical Engineering, 28, 219–234 (2004).
• Soares, R.P. and A.R. Secchi. EMSO: A New Environment for Modeling, Simulation and Optimization. ESCAPE 13, Lappeenranta, Finlândia, 947 – 952 (2003).
• Soares, R.P. and A.R. Secchi. Modifications, Simplifications, and Efficiency Tests for the CAPE-OPEN Numerical Open Interfaces. Computers and Chemical Engineering, 28, 1611–1621 (2004).
• Soares, R.P. and A.R. Secchi, Direct Initialisation and Solution of High-Index DAE Systems, ESCAPE 15, Barcelona, Spain, 157–162 (2005).
• Srinivasan, R., P. Viswanathan, H. Vedam and A. Nochur. A Framework for Managing Transitions in Chemical Plants. Computers and Chemical Engineering, 29, 305–322 (2005).
• Toledo, E.C.V., R.F. Martini, M.R.W. Maciel and R. Maciel Filho. Process Intensification for High Operational Performance Target: Autorefrigerated CSTR Polymerization Reactor. Computers and Chemical Engineering, 29, 1447–1455 (2005).
UFRGS
52
ReferencesReferences
• Tosukhowong, T., J.M. Lee, J.H. Lee and J. Lu. An Introduction to a Dynamic Plant-Wide Optimization Strategy for an Integrated Plant. Computers and Chemical Engineering, 29, 199–208 (2004).
• Trierweiler, J.O. and L.A. Farina. RPN tuning strategy for model predictive control. Journal of Process Control, 13, 591–598 (2003).
• Wu, K.L., C.C. Yu, W.L. Luyben and S. Skogestad. Reactor/Separator Processes with Recycles-2. Design for Composition Control. Computers and Chemical Engineering, 27, 401–421 (2002).
• Yip, W.S. and T.E. Marlin. The Effect of Model Fidelity on Real-Time Optimization Performance. Computers and Chemical Engineering, 28, 267–280 (2004).
• Zhang, J. and R. Smith. Design and Optimisation of Batch and Semi-Batch Reactors. Chemical Engineering Science, 59, 459–478 (2004).
DAE Solvers:DASSL or DASSLC: Petzold, l.R. (1989) or Secchi, A.R. and F.A. Pereira (1997), http://www.enq.ufrgs.br/enqlib/numeric/numeric.htmlMEBDFI: Abdulla, T.J. and J.R. Cash (1999), http://www.netlib.org/ode/mebdfi.f
PSIDE: Lioen, W.M., J.J.B. de Swart, and W.A. van der Veen (1997), http://www.cwi.nl/cwi/projects/PSIDE/SUNDIALS: R. Serban et al. (2004), http://www.llnl.gov/CASC/sundials/description/description.html
UFRGS
53
International Symposium on Advanced Control of Chemical Processes
April 2-5, 2006http://www.adchem.org
Workshop of Solving Industrial Control and Optimization Problems
April 6-7, 2006http://www.enq.ufrgs.br/sicop2006/
ADCHEM 2006 and SICOP 2006ADCHEM 2006 and SICOP 2006
UFRGS
54
Argimiro Resende Secchi, D.Sc.Jorge Otávio Trierweiler, D.Sc.Marla Azário Lansarin, D.Sc.Nilo Sérgio Medeiros Cardozo, D.Sc.André Bello de Oliveira, M.Sc.André Rodrigues Muniz, M.Sc.Andrey Copat, Eng.Adriano Giraldi Fisch, M.Sc.Ariel Kempf, M.Sc.Christiano Daniel Wetzel Guerra, I.C.Cristiano Sá Brito Cardoso, Eng.Débora Jung Luvizetto, Eng.Edson Cordeiro do Valle, M.ScEduardo Fontoura Birnfeld, Eng.Eduardo Guimarães de Magalhães, Eng.Euclides Almeida Neto, M.Sc.Fábio Brião de Oliveira, Eng.
Marcus Darci Rutsatz, Eng.Maurício Carvalho Maciel, I.C.Nina Paula Gonçalves Salau, M.Sc.Paula Betio Staudt, Eng.Rafael de Pelegrini Soares, M.Sc.Rafael Spohr, Eng.Ricardo Guilherme Duraiski, M.Sc.Rodolfo Rodrigues, Eng.Rodrigo Paliga da Rosa, I.C.Samuel Facchin, Eng.Tanise Mori Flores, Eng.Tiago da Silva Osório, I.C.Tiago Fiorenzano Finkler, M.Sc.Tito Lívio Domingues, M.Sc.Vanessa Conz, M.Sc.Vinícius Cunha Machado, M.Sc.Wagner Bertuol Casagrande, I.C.
UFRGS
55
Process Simulation LabProcess Simulation Lab•• Chair: Prof. Dr. Chair: Prof. Dr. ArgimiroArgimiro ResendeResende SecchiSecchi•• Phone: +55Phone: +55--5151--33163316--35283528•• EE--mail: mail: [email protected]@enq.ufrgs.br•• http://http://www.enq.ufrgs.br/labs/lasim.htmlwww.enq.ufrgs.br/labs/lasim.html
Process Integration and Control LabProcess Integration and Control Lab•• Chair: Prof. Dr. Jorge Chair: Prof. Dr. Jorge OtOtááviovio TrierweilerTrierweiler•• Phone: +55Phone: +55--5151--33163316--40724072•• EE--mail: mail: [email protected]@enq.ufrgs.br•• http://http://www.enq.ufrgs.br/labs/lacip.htmlwww.enq.ufrgs.br/labs/lacip.html
... thank you for your attention!
PASI 2005Pan American Advanced Studies Institute Program on Process Systems Engineering
UFRGS
56
Extra slidesExtra slides
UFRGS
57
Maximum cardinality matchingMaximum cardinality matching
breadth-first search, E: equations set, V: variables set, L: lines setThere is a line Ei – Vj if the equation Ei contains the variable Vj
UFRGS
58
Index analysis and reductionIndex analysis and reduction