Bayesian framework for building kinetic models of catalytic systems

Industrial and Engineering Chemistry Research

Volumn 48, Issue 10, 2009, Pages 4768-4790

  Hsu, Shuo Huan ^a   Stamatis, Stephen D ^a   Caruthers, James M ^a   Delgass, W Nicholas ^a   Venkatasubramanian, Venkat ^a   Blau, Gary E ^a   Lasinski, Mike ^a   Orcun, Seza ^a  

^a PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN APPROACHES; BAYESIAN FRAMEWORKS; BEST MODEL; CATALYTIC REACTIONS; CATALYTIC SYSTEM; COMPUTATIONAL RESOURCES; ESTIMATE MODEL; HIGH THROUGHPUT SCREENING; IMPROVED MODELS; KINETIC BEHAVIOR; KINETIC MODELS; LANGMUIR-HINSHELWOOD; MONTE CARLO; PARAMETER ESTIMATE; QUALITY MODELS; RATE EXPRESSION; STATISTICAL TOOLS; THREE MODELS;

BAYESIAN NETWORKS; CATALYSIS; KINETIC THEORY; LAW ENFORCEMENT; MONTE CARLO METHODS; PARAMETER ESTIMATION;

MODEL BUILDINGS;

EID: 67249145577     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie801651y     Document Type: Article

References (57)

1. Caruthers, J. M.; Lauterbach, J. A.; Thomson, K. T.; Venkatasubramanian, V.; Snively, C. M.; Bhan, A.; Katare, S.; Oskarsdottir, G. Catalyst design: knowledge extraction from high-throughput experimentation. J. Catal. 2003, 216 (1-2), 98-109.
2. Dumesic, J. A.; Milligan, B. A.; Greppi, L. A.; Balse, V. R.; Sarnowski, K. T.; Beall, C. E.; Kataoka, T.; Rudd, D. F.; Trevino, A. A. A Kinetic Modeling Approach to the Design of Catalysts - Formulation of a Catalyst Design Advisory Program. Ind. Eng. Chem. Res. 1987, 26 (7), 1399-1407.
3. Banaresalcantara, R.; Westerberg, A. W.; Ko, E. I.; Rychener, M. D. DECADEsA Hybrid Expert System for Catalyst Selection. 1. Expert System Consideration. Comput. Chem. Eng. 1987, 11 (3), 265-277.
4. Banaresalcantara, R.; Ko, E. I.; Westerberg, A. W.; Rychener, M. D. DECADEsA Hybrid Expert System for Catalyst Selection. 2. Final Architecture and Results. Comput. Chem. Eng. 1988, 12 (9-10), 923-938.
5. Ammal, S. S. C.; Takami, S.; Kubo, M.; Miyamoto, A. Integrated computational chemistry system for catalysts design. Bull. Mater. Sci. 1999, 22 (5), 851-861.
6. Burello, E.; Rothenberg, G. In silico design in homogeneous catalysis using descriptor modelling. Int. J. Mol. Sci. 2006, 7 (9), 375-404.
7. Dumesic, J. A.; Rudd, D. F.; Aparicio, L. M.; Rekoske, J. E.; Trevino, A. A. The Microkinetics of Heterogeneous Catalysis; American Chemical Society: Washington, D.C., 1993; p 316.
8. Box, G. E. P.; Lucas, H. L. Design of Experiments in Non-Linear Situations. Biometrika 1959, 46 (1/2), 77-90.
9. Chernoff, H. Sequential design of experiments. Ann. Math. Statist. 1959, 30, 755-770.
10. Franckaerts, J.; Froment, G. F. Kinetic study of the dehydrogenation of ethanol. Chem. Eng. Sci. 1964, 19 (10), 807-818.
11. Box, G. E. P.; Draper, N. R. The Bayesian Estimation of Common Parameters from Several Responses. Biometrika 1965, 52 (3), 355-365.
12. Hunter, W., G.; Reiner, A. M. Designs for discriminating between two rival models. Technometrics 1965, 7 (3), 307-323.
13. Kittrel, J. R.; Hunter,W. G.; Watson, C. C. Nonlinear Least Squares Analysis of Catalytic Rate Models. AIChE J. 1965, 11 (6), 1051-1057.
14. Box, G. E. P.; Hill, W. J. Discrimination among mechanistic models. Technometrics 1967, 9 (1), 57-71.
15. Hunter, W. G.; Mezaki, R. An experimental design strategy for distinguishing among rival mechanistic models. An application to the catalytic hydrogenation of propylene. Can. J. Chem. Eng. 1967, 45, 247- 249.
16. Froment, G. F.; Mezaki, R. Sequential Discrimination and Estimation Procedures for Rate Modeling in Heterogeneous Catalysis. Chem. Eng. Sci. 1970, 25, 293-301.
17. Van Welsenaere, R. J.; Froment, G. F. Parametric Sensitivity and Runaway in Fixed Bed Catalytic Reactors. Chem. Eng. Sci. 1970, 25, 1503- 1516.
18. Reilly, P. M. Statistical methods in model discrimination. Can. J. Chem. Eng. 1970, 48, 168-173.
19. Bard, Y. Nonlinear parameter estimation; Academic Press: New York, 1974.
20. Reilly, P. M.; Blau, G. E. The Use of Statistical Methods to Build Mathematical Models of Chemical Reaction Systems. Can. J. Chem. Eng. 1974, 52, 289-299.
21. Reilly, P. M.; Bajramovic, R.; Blau, G. E.; Branson, D. R.; Sauerhoff, M. W. Guidelines for the optimal desing of experiments to estimate parameters in first order kinetic models. Can. J. Chem. Eng. 1977, 55, 614.
22. Stewart, W. E.; Sorensen, J. P. Bayesian Estimation of Common Parameters From Multiresponse Data With Missing Observations. Technometrics 1981, 23 (2), 131-141.
23. Rabitz, H.; Kramer, M.; Dacol, D. Sensitivity Analysis in Chemical Kinetics. Annu. Rev. Phys. Chem. 1983, 34, 419-461.
24. Froment, G. F. The kinetics of complex catalytic reactions. Chem. Eng. Sci. 1987, 42 (5), 1073-1087.
25. Stewart, W. E.; Caracotsios, M.; Sorensen, J. P. Parameter estimation from multiresponse data. AIChE J. 1992, 38 (5), 641-650.
26. Stewart, W. E.; Shon, Y.; Box, G. E. P. Discrimination and goodness of fit of multiresponse mechanistic models. AIChE J. 1998, 44 (6), 1404-1412.
27. Asprey, S. P.; Naka, Y. Mathematical Problems in Fitting Kinetic ModelssSome New Persopectives. J. Chem. Eng. Jpn. 1999, 32 (3), 328- 337.
28. Stewart, W. E.; Henson, T. L.; Box, G. E. P. Model discrimination and criticism with single-response data. AIChE J. 1996, 42 (11), 3055- 3062.
29. Park, T.-Y.; Froment, G. F. A Hybrid Genetic Algorithm for the Estimation of Paramters in Detailed Kinetic Models. Comput. Chem. Eng. 1998, 22 (Suppl.), S103-S110.
30. Petzold, L.; Zhu, W. Model reduction for chemical kinetics: an optimization approach. AIChE J. 1999, 45 (4), 869-886.
31. Ross, J.; Vlad, M. O. Nonlinear Kinetics and New Approaches to Complex Reaction Mechanisms. Annu. Rev. Phys. Chem. 1999, 50, 51-78.
32. Atkinson, A. C. Non-constant variance and the design of experiments for chemical kinetic models. In Dynamic model developmentsmethods, theory and applications; Asprey, S. P., Macchietto, S., Eds.; Elsevier: Amsterdam, 2000; pp 141-158.
33. Cortright, R. D.; Dumesic, J. A. Kinetics of Heterogeneous Catalytic Reactions: Analysis of Reaction Schemes. Adv. Catal. 2001, 46, 161-264.
34. Song, J.; Stephanopoulos, G.; Green, W. H. Valid Parameter Range Analyses for Chemical Reaction Kinetic Models. Chem. Eng. Sci. 2002, 57, 4475-4491.
35. Sirdeshpande, A. R.; Ierapetritou, M. G.; Androulakis, I. P. Design of Flexible Reduced Kinetic Mechanisms. AIChE J. 2001, 47 (11), 2461- 2473.
36. Katare, S.; Bhan, A.; Caruthers, J. M.; Delgass, W. N.; Venkatasubramanian, V. A hybrid genetic algorithm for efficient parameter estimation of large kinetic models. Comput. Chem. Eng. 2004, 28 (12), 2569-2581.
37. Bhan, A.; Hsu, S.-H.; Blau, G.; Caruthers, J. M.; Venkatasubramanian, V.; Delgass, W. N. Microkinetic Modeling of Propane Aromatization over HZSM-5. J. Catal. 2005, 235 (1), 35-51.
38. Bogacha, B.; Wright, F. Non-linear design problem in a chemical kinetic model with non-constant error variance. J. Stat. Plan. Inference 2005, 128, 633-648.
39. Ucinski, D.; Bogacha, B. T-optimum design for discrimination between two multiresponse dynamic models. J. R. Stat. Soc. Ser. B: Stat. Method. 2005, 67, 3-18.
40. Englezos, P. J.; Kalogerakis, N. Applied Parameter Estimation for Chemical Engineers; Marcel-Decker, Inc.: New York, 2001.
41. Blau, G. E.; Lasinski, M.; Orcun, S.; Hsu, S.-H.; Caruthers, J. M.; Delgass, W. N.; Venkatasubramanian, V. High Fidelity Mathematical Model Building with Experimental Data: A Bayesian Approach. Comput. Chem. Eng. 2008, 32 (4-5), 971-989.
42. Draper, N. R.; Hunter, W. G. Design of experiments for parameter estimation in multiresponse situations. Biometrika 1966, 53 (3/4), 525- 533.
43. Draper, D. Bayesian Hierarchical Modeling; Springer-Verlag: New York, 2000.
44. Nocedal, J.; Wright, S. J. Numerical optimization; Springer: New York, 1999; p 636.
45. Froment, G. F. Model discrimination and parameter estimation in heterogeneous catalysis. AIChE J. 1975, 21 (6), 1041-1057.
46. Metropolis, N.; Rosenbluth, A. W.; Rosenbluth, M. N.; Teller, A. H.; Teller, E. Equations of State Calculations by Fast Computing Machines. J. Chem. Phys. 1953, 21, 1087-1092.
47. Gilks, W. R.; Richardson, S.; Spiegelhalter, D. J. MarkoV Chain Monte Carlo in Practice; Chapman & Hall/CRC: New York, 1996.
48. Atkinson, A. C.; Cox, D. R. Planning Experiments for Discriminating between Models. J. R. Stat. Soc. Ser. B: Stat. Method. 1974, 36 (3), 321-348.
49. Atkinson, A. C.; Fedorov, V. V. Optimal design: Experiments for discriminating between several models. Biometrika 1975, 62 (2), 289-303.
50. Fedorov, V. V.; Pazman, A. Design of physical experiments. Fortschr. Phys. 1968, 16, 325-355.
51. Hsiang, T.; Reilly, P. M. A practical method for discriminating among mechanistic models. Can. J. Chem. Eng. 1971, 49, 865-871.
52. Montgomary, D. C.; Runger, G. C. Applied Statistics and Probability for Engineers, 3rd ed.; Wiley: Hoboken, NJ, 2002; p 720.
53. Prasad, V.; Vlachos, D. G. Multiscale Model and Informatics Based Optimal Design of Experiments: Application to the Catalytic Decomposition of Ammonia on Ruthenium. Ind. Eng. Chem. Res. 2008, 47, 6555-6567.
54. Hsu, S.-H. Bayesian Model Building Strategy and Chemistry Knowledge Compilation for Kinetic Behaviors of Catalytic Systems. Ph.D. Thesis, Purdue University, West Lafayette, IN, 2006.
55. Bates, D. M.; Watts, D. G. Nonlinear Regression Analysis and its Applications; Wiley and Sons: New York, 1988.
56. Fishman, G. S. A First Course in Monte Carlo; Thomson Brooks/Cole: Belmont, CA, 2005.
57. Hastings, W. K. Monte Carlo Sampling Methods Using Markov Chains and Their Applications. Biometrika 1970, 57, 97-109.