Multi-scale optimization for process systems engineering

Computers and Chemical Engineering

Volumn 60, Issue , 2014, Pages 17-30

  Biegler, Lorenz T ^a   Lang, Yi dong ^a   Lin, Weijie ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

Model reduction; Nonlinear programming; Process optimization; Trust region

Indexed keywords

GRADIENT CALCULATIONS; INTEGRATED OPTIMIZATION; MODEL REDUCTION; MULTI-SCALE OPTIMIZATION; OPTIMIZATION PROBLEMS; OPTIMIZATION STRATEGY; PROCESS SYSTEMS ENGINEERING; TRUST REGION;

ALGORITHMS; MOLECULAR DYNAMICS; ODOR CONTROL; OPTIMIZATION; PROCESS CONTROL;

NONLINEAR PROGRAMMING;

EID: 84883610459     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2013.07.009     Document Type: Article

References (81)

1. Agarwal A., Biegler L.T. A trust-region framework for constrained optimization using reduced order modeling. Optimization and Engineering 2013, 14(1):3-36.
2. Agarwal A., Biegler L.T., Zitney S.E. Simulation and optimization of pressure swing adsorption systems using reduced-order modeling. Industrial and Engineering Chemistry Research 2009, 48(5):2327-2343.
3. Alexandrov N.M., Dennis J.E., Lewis R.M., Torczon V. A trust-region framework for managing the use of approximate models in optimization. Structural Optimization 1998, 15:16-23.
4. Alexandrov N.M., Lewis R.M., Gumbert C.R., Green L.L., Newman P.A. Approximation and model management in aerodynamic optimization with variable-fidelity models. Journal of Aircraft 2001, 38(6):1093-1101.
5. Antoulas A.C., Sorensen D.C. Approximation of large-scale dynamical systems: An overview. International Journal of Applied Mathematics and Computer Science 2001, 11(5):1093-1121.
6. Armaou A., Christofides P.D. Dynamic optimization of dissipative PDE systems using nonlinear order reduction. Chemical Engineering Science 2002, 7:5083-5114.
7. Astrid P., Weiland S., Willcox K., Backx T. Missing point estimation in models described by proper orthogonal decomposition. IEEE Transactions on Automatic Control 2008, 53(10):2237-2251.
8. Barrett A., Walsh J.J. Improved chemical process simulation using local thermodynamic approximations. Computers and Chemical Engineering 1979, 3:397-405.
9. Bendersky E., Christofides P.D. Optimization of transport-reaction processes using nonlinear model reduction. Chemical Engineering Science 2000, 55:4349-4366.
10. Bergmann M., Cordier L., Brancher J.-P. Optimal rotary control of the cylinder wake using proper orthogonal decomposition reduced-order model. Physics of Fluids 2005, 17:97-101.
11. Biegler L.T., Grossmann I.E. Part I: Retrospective on optimization. Computers & Chemical Engineering 2004, 28(8):1169-1192.
12. Biegler L., Grossmann I.E., Westerberg A.W. A note on approximation techniques used for process optimization. Computers & Chemical Engineering 1985, 9(2):201.
13. Biegler L.T., Lang Y.-D. Multi-scale optimization for advanced energy processes. International symposium on process systems engineering, volume 31 of computer aided chemical engineering 2012, 51-60.
14. Boston J.F., Britt H.I. A radically different formulation and solution of the single-stage flash problem. Computers & Chemical Engineering 1978, 2:109-125.
15. Brdys M., Roberts P.D. Convergence and optimality of modified two-step algorithm for integrated system optimization and parameter estimation. International Journal of Systems Science 1987, 18:1305-1322.
16. Brdys M., Tatjewski P. Iterative algorithms for multilayer optimizing control 2005, Imperial College Press, London, UK.
17. Bui-Thanh T., Damodaran M., Willcox K. Aerodynamic data reconstruction and inverse design using proper orthogonal decomposition. AIAA Journal 2004, 42(8):1505-1516.
18. Bui-Thanh T., Willcox K., Ghattas O., Bloemen Waanders B. Goal-oriented, model-constrained optimization for reduction of large-scale systems. Journal of Computational Physics 2007, 224(2):880-896.
19. Burnham A., Viveros R., MacGregor J. Frameworks for latent variable multivariate regression. Journal of Chemometrics 1996, 10:31-45.
20. Caballero J.A., Grossmann I.E. An algorithm for the use of surrogate models in modular flowsheet optimization. AIChE Journal 2008, 54(10):2633-2650.
21. Cao Y., Zhu J., Luo Z., Navon I.M. Reduced-order modeling of the upper tropical pacific ocean model using proper orthogonal decomposition. Computers & Mathematics with Applications 2006, 52:1373-1386.
22. Chatterjee A. An introduction to proper orthogonal decomposition. Current Science 2000, 78(7):808-817.
23. Chung P.S., Jhon M., Biegler L.T. The holistic strategy in multi-scale modeling. Advances in Chemical Engineering 2011, 40:59-118.
24. Conn A.R., Gould N.M., Toint P.L. Trust-region methods. MPS-SIAM series on optimization 2000, SIAM, Philadelphia, PA.
25. Conn A.R., Scheinberg K., Vicente L. Global convergence of general derivative-free trust-region algorithms to first- and second-order critical points. SIAM Journal on Optimization 2009, 20:387-415.
26. Conn A.R., Scheinberg K., Vicente L. Introduction to derivative free optimization 2009, SIAM, Philadelphia.
27. Couplet M., Basdevant C., Sagaut P. Calibrated reduced-order POD-galerkin system for fluid flow modelling. Journal of Computational Physics 2005, 207:192-220.
28. Cozad A., Sahinidis N.V. Derivative-free optimization enhanced-surrogate models for energy systems optimization. INFORMS annual meeting 2011, http://archimedes.cheme.cmu.edu/?q=alamo.
29. Davis E.F. Modeling and optimization of process engineering problems containing black-box systems and noise 2008, State University of New Jersey, (PhD thesis).
30. Dihlmann M.A., Haasdonk B. Certified PDE-constrained parameter optimization using reduced basis surrogate models for evolution problems. Technical Report 2013, Stuttgart Research Centre for Simulation Technology (SRC SimTech).
31. Dowling A.W., Vetukuri S.R.R., Biegler L.T. Large-scale optimization strategies for pressure swing adsorption cycle synthesis. AIChE Journal 2012, 58:3777-3791.
32. Eldred M.S., Giunta A.A., Collis S.S. Second-order corrections for surrogate-based optimization with model hierarchies. 10th AIAA/ISSMO multidisciplinary analysis and optimization conference 2004.
33. Fahl M., Sachs E.W. Reduced-order modelling approaches to pde-constrained optimization based on proper orthogonal decomposition. Large-scale PDE-constrained optimization 2003, 268-280.
34. Forbes J.F., Marlin T.E., MacGregor J.F. Model adequacy requirements for optimizing plant operations. Computers and Chemical Engineering 1994, 18(6):497-510.
35. Galletti B., Bruneau C.H., Zannetti L., Iollo A. Low-order modelling of laminar flow regimes past a confined square cylinder. Journal of Fluid Mechanics 2004, 503:161-170.
36. Gao W., Engell S. Iterative set-point optimization of batch chromatography. Computers & Chemical Engineering 2005, 29:1401-1409.
37. Giunta A.A., Eldred M.S. Implementation of a trust region model management strategy in the DAKOTA optimization toolkit. Proceedings of the 8th AIAA/USAF/NASA/ISSMO symposium on multidisciplinary analysis and optimization 2000.
38. Goel T., Haftka R., Shyy W. Comparing error estimation measures for polynomial and kriging approximation of noise-free functions. Structural and Multidisciplinary Optimization 2009, 38(5):429-442.
39. Gregory F., Srinivasan B., Bonvin D. Comparison of six implicit real-time optimization schemes. Journal Europeen des Systemes Automatises 2012, 46(2-3):291-305.
40. Gunzburger M.D., Peterson J.S., Shadid J.N. Reduced-order modeling of time-dependent pdes with multiple parameters in the boundary data. Computer Methods in Applied Mechanics and Engineering 2007, 196:1030-1047.
41. Kitamori, Y. (1976). Process for producing polyethylene resin particles and foamable polyethylene resin particles. United States Patent 3959189.
42. Kleijnen J.P.C. Kriging metamodeling in simulation: A review. European Journal of Operational Research 2009, 192:707-716.
43. Kobayashi, S., Nakamura, M. (1985). Process for preparing modified polyolefin particles and foamed article made from the particles. US Patent 4525486.
44. Krallis A., Pladis P., Kiparissides C. Prediction of the bivariate molecular weight-long chain branching distribution in high-pressure low-density polyethylene autoclaves. Macromolecular Theory and Simulations 2007, 16(6):593-609.
45. Kumar S., Ramkrishna D. On the solution of population balance equations by discretization - III. Nucleation, growth and aggregation of particles. Chemical Engineering Science 1997, 52(24):4659-4679.
46. Kunisch K., Volkwein S. Control of the burgers equation by a reduced-order approach using proper orthogonal decomposition. Journal of Optimization Theory and Applications 1999, 102(2):345-371.
47. Kunisch K., Volkwein S. Galerkin proper orthogonal decomposition methods for parabolic problems. Numerical Mathematics 2001, 90:117-148.
48. Kunisch K., Volkwein S. Galerkin proper orthogonal decomposition methods for a general equation in fluid dynamics. SIAM Journal on Numerical Analysis 2002, 40(2):492-515.
49. Lang Y.-d., Malacina A., Biegler L.T., Munteanu S., Madsen J.I., Zitney S.E. Reduced order model based on principal component analysis for process simulation and optimization. Energy and Fuels 2009, 23(3):1695-1706.
50. Lang Y.-D., Zitney S.E., Biegler L.T. Optimization of IGCC processes with reduced order CFD models. Computers & Chemical Engineering 2011, 35:1705-1717.
51. Leesley M.E., Heyen G. The dynamic approximation method of handling vapor-liquid equilibrium data in computer calculations for chemical processes. Computers and Chemical Engineering 1977, 1:102-110.
52. LeGresley P.A., Alonso J.J. Airfoil design optimization using reduced order models based on proper orthogonal decomposition. Fluids 2000 conference and exhibit 2000.
53. Lin W. Modeling and optimization of a semi-interpenetrating polymer network process 2011, Carnegie Mellon University, (PhD thesis).
54. Lin W., Biegler L.T., Jacobson A.M. Modeling and optimization of seed polymerization process. Chemical Engineering Science 2010, 65:4350-4362.
55. Lin W., Biegler L.T., Jacobson A.M. Kinetic modeling of semi-interpenetrating polymer network (SIPN) process - a comprehensive study on the case of polyethylene/polystyrene semi-I IPN. Macromolecular Theory and Simulations 2011, 20(2):146-165.
56. Lophaven S.N., Nielsen H.B., Sondergaard J. DACE A Matlab kriging toolbox. Technical report 2002, Technical Report IMM-TR-2002-12, Technical University of Denmark.
57. Lumley J.L. Coherent structures in turbulence. Transition and turbulence 1981, 215-242. Academic Press, New York, NY. R.E. Meyer (Ed.).
58. Ly H.V., Tran H.T. Modeling and control of physical processes using proper orthogonal decomposition. Mathematical and Computer Modelling 2001, 33(1-3):223-236.
59. March A., Willcox K. A provably convergent multifidelity optimization algorithm not requiring high-fidelity derivatives. Technical report 2010, AIAA-2010-9198, AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference.
60. Marchetti A., Chachuat B., Bonvin D. Modifier adaptation methodology for real-time optimization. Industrial and Engineering Chemistry Research 2009, 48:6022-6033.
61. Marquardt, W. (2002). Nonlinear model reduction for optimization based control of transient chemical processes. In: Rawlings, J. B., Ogunnaike, B. A., & Eaton, J. W. (Eds.), Chemical process control VI, Tuscon, Arizona, 326, 12-42.
62. Moehlis J., Smith T.R., Holmes P., Faisst H. Models for turbulent plane couette flow using the proper orthogonal decomposition. Physics of Fluids 2002, 14(7):2493-2507.
63. Morris A., Montague G., Willis M. Artificial neural networks: Studies in process modeling and control. Transactions of the Institution of Chemical Engineers 1994, 72:3-19.
64. Navia D., Marti R., Sarabia D., Gutirrez G., de Prada C. Handling infeasibilities in dual modifier-adaptation methodology for real-time optimization. 8th IFAC symposium on advanced control of chemical processes 2012, 537-542.
65. Park H.M., Cho D.H. The use of the Karhunen-Loéve decomposition for the modeling of distributed parameter systems. Chemical Engineering Science 1996, 51(1):81-98.
66. Peter J., Marcelet M. Comparison of surrogate models for turbomachinery design. WSEAS Transactions on Fluid Mechanics 2008, 3:10-17.
67. Romijn R., Marquardt W. A projection approach for optimization of distributed parameter systems without gradients. 19th European symposium on computer aided process engineering, volume 27 of computer aided chemical engineering 2009, 531-536.
68. Romijn R., Özkan L., Weiland S., Ludlage J., Marquardt W. A grey-box modeling approach for the reduction of nonlinear systems. Journal of Process Control 2008, 18(9):906-914.
69. Sakata S., Ashida F., Zako M. Structural optimization using Kriging approximation. Computer Methods in Applied Mechanics and Engineering 2003, 192:923-939.
70. Schlegel M., Berg J.v.d., Marquardt W., Bosgra O. Projection based model reduction for dynamic optimization. AIChE annual meeting 2002 2002.
71. Shvartsman S.Y., Theodoropoulos C., Rico-Martinez R., Kevrekidis I.G., Titi E.S., Mountziaris T.J. Order Reduction for nonlinear dynamic models of distributed reacting systems. Journal of Process Control 2000, 10:177-184.
72. Simpson T., Peplinsky J., Koch P., Allen J. Metamodels for computer-based engineering: Survey and recommendation. Research in Engineering Design 2001, 17:129-150.
73. Sirovich L. Turbulence and the dynamics of coherent structures. Quarterly of Applied Mathematics 1987, 45(3):561-571.
74. Srinivasan B., Biegler L.T., Bonvin D. Tracking the necessary conditions of optimality with changing set of active constraints using a barrier-penalty function. Computers and Chemical Engineering 2008, 32(3):572-579.
75. Thekale A. Trust-region methods for simulation based nonlinear optimization 2010, Friedrich-Alexander-Universität Erlangen-Nürnberg, (PhD thesis).
76. Theodoropoulou A., Adomaitis R.A., Zafiriou E. Model reduction for optimization of rapid thermal chemical vapor deposition systems. IEEE Transactions on Semiconductor Manufacturing 1998, 11(1):85-98.
77. van den Berg J. Model reduction for dynamic real-time optimization of chemical processes 2005, Technische Universiteit Delft, (PhD thesis).
78. Wächter A., Biegler L. On the implementation of a primal-dual interior point filter line search algorithm for large-scale nonlinear programming. Mathematical Programming 2006, 106(1):25-57.
79. Wild S.M., Regis R.G., Shoemaker C.A. ORBIT: Optimization by radial basis function interpolation in trust-regions. SIAM Journal on Scientific Computing 2008, 30:3197-3219.
80. Willcox K., Peraire J. Balanced model reduction via the proper orthogonal decomposition. AIAA Journal 2002, 40(11):2323-2330.
81. Yuan T., Cizmas P.G., O'Brien T. A reduced-order model for a bubbling fluidized bed based on proper orthogonal decomposition. Computers and Chemical Engineering 2005, 30:243-259.