Incremental identification of complex reaction systems:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Düsseldorf
VDI-Verl.
2006
|
| Ausgabe: | Als Ms. gedr. |
| Schriftenreihe: | Fortschritt-Berichte VDI
Reihe 3, Verfahrenstechnik ; 864 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Zugl.: Aachen, Techn. Hochsch., Diss. |
| Beschreibung: | XX, 217 S. Ill., graph. Darst. |
| ISBN: | 3183864037 |
Internformat
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| 100 | 1 | |a Brendel, Marc Levin |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Incremental identification of complex reaction systems |c Marc Levin Brendel |
| 250 | |a Als Ms. gedr. | ||
| 264 | 1 | |a Düsseldorf |b VDI-Verl. |c 2006 | |
| 300 | |a XX, 217 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Fortschritt-Berichte VDI : Reihe 3, Verfahrenstechnik |v 864 | |
| 490 | 0 | |a Berichte aus dem Lehrstuhl für Prozesstechnik RWTH Aachen | |
| 500 | |a Zugl.: Aachen, Techn. Hochsch., Diss. | ||
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Datensatz im Suchindex
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| adam_text | Notation IX
Kurzfassung XVIII
1 Introduction 1
2 Identification of reaction Systems 4
2.1 Fundamentals of chemical kinetics 5
2.2 Conventional identification approaches 8
2.3 A motivating example: Acetoacetylation of pyrrole 14
2.3.1 Reaction System and experimental conditions 15
2.3.2 Conventional identification 18
2.4 The incremental identification concept 21
2.4.1 Reactor modeling 22
2.4.2 Reactor model identification 23
2.5 Summary 26
3 Incremental identification Steps 28
3.1 Incremental identification The base case 28
3.1.1 Reaction flux estimation 29
3.1.1.1 Problem formulation 29
3.1.1.2 Calculation of regularized flux estimates 30
3.1.1.3 Reduction of measurement noise 31
3.1.2 Identification of a stoichiometric model 32
3.1.3 Reaction rate estimation 34
3.1.4 Identification of kinetic laws 36
3.1.4.1 Regression problem 36
3.1.4.2 Dependent reactions 37
3.1.4.3 Reversible reactions 38
V
3.2 Incremental identification Extensions 39
3.2.1 Incremental identification for incomplete measurements .... 40
3.2.2 Identifiability and estimation of reaction rates 41
3.2.2.1 All reaction rates identifiable 41
3.2.2.2 Subset of reaction rates identifiable 41
3.2.3 Concentration estimation 43
3.2.3.1 Reconstruction of reaction fluxes 43
3.2.3.2 Calculation of concentration estimates 45
3.2.4 Unmeasured species in dependent reaction Systems 46
3.3 Incremental identification of the acetoacetylation System 47
3.3.1 Problem setting 48
3.3.2 Identification procedure 48
3.4 Conclusions 53
4 Extensions of the incremental concept 56
4.1 Identification of temperature dependencies 56
4.1.1 Incremental and combined estimation of temperature laws . . 57
4.1.1.1 Incremental estimation 57
4.1.1.2 Combined estimation 59
4.1.2 Application example: Acetoacetylation System 60
4.2 Multiple phases 64
4.2.1 Rate estimation in multi phase Systems 64
4.2.2 Application example: Two phase reactive System 68
4.2.2.1 The reactor model 68
4.2.2.2 Identification procedure 70
4.3 Distributed parameter Systems 72
4.3.1 Rate estimation in distributed Systems 73
4.3.2 Application example: Bncapsulated enzyme bead 75
4.3.2.1 Problem setting 75
4.3.2.2 Identification procedure 77
4.4 Conclusions and perspectives 81
5 Incremental identification of unstructured kinetic modeis 83
5.1 A function estimation algorithm based on hierarchically refined
sparse grids 85
5.1.1 Function approximation with sparse grids 87
5.1.1.1 The approximation concept 87
5.1.1.2 Conventional finite element discretization 88
VI
5.1.1.3 Sparse grids with uniform discretization 90
5.1.1.4 Sparse grids with variable discretization 91
5.1.2 The function estimation approach 93
5.1.2.1 Stepwise grid refinement algorithm 0 96
5.1.2.2 Selection of discretization and Tikhonov regularization 100
5.1.3 Case studies 103
5.1.3.1 Best estimates 104
5.1.3.2 Bivariate function examples 105
5.1.3.3 Trivariate and quadrivariate function examples . . . 112
5.1.3.4 Analysis of sensitivity calculation 114
5.1.3.5 Comparison of grid combination approaches 115
5.1.3.6 Discussion 116
5.1.3.7 Comparison to neural networks 117
5.1.4 Summary 119
5.2 Application example: Acetoacetylation System 120
5.2.1 Problem setting 120
5.2.2 Identification results 121
5.2.3 Reduced modeis 125
5.2.4 Mixed structured and unstructured kinetic modeis 126
5.3 Conclusions 127
6 The iterative identification methodology 129
6.1 Structured kinetic modeis 130
6.1.1 Work process for structured modeis 130
6.1.1.1 Parameter re adjustment and model validation . . . 131
6.1.1.2 Experimental design 132
6.1.2 Application example: Acetoacetylation system 133
6.2 Unstructured kinetic modeis 137
6.2.1 A heuristic coverage design for data driven approximators . . 140
6.2.1.1 Single input space coverage 140
6.2.1.2 Multiple input space coverage 142
6.2.2 Application example: Acetoacetylation system 145
6.3 Conclusions 151
7 Conclusions and perspectives 153
A Input estimation based on multi scale methods 160
A.l Theory 160
A.2 Example 162
VII
A.3 Conclusions 167
B Some investigations on derivative estimation using a filter approach 168
B.l Forward backward filtering 169
B.2 Choosing endpoint constraints 173
B.3 Combining the search for regularization parameter and endpoint
constraints 176
B.4 Validation on test functions 178
B.5 Conclusions 182
C Identifiability of two film mass transfer modeis 183
C.l The mass transfer model 184
C.2 Physical properties and experimental settings 186
C.3 Analysis of identifiability 188
C.4 Conclusions 191
D Derivation of the sparse grid sensitivity vector 192
E Sparse grid test functions 196
F Data scaling to unity domain 197
G Experimental design settings 199
Bibliography 201
VIII
|
| adam_txt |
Notation IX
Kurzfassung XVIII
1 Introduction 1
2 Identification of reaction Systems 4
2.1 Fundamentals of chemical kinetics 5
2.2 Conventional identification approaches 8
2.3 A motivating example: Acetoacetylation of pyrrole 14
2.3.1 Reaction System and experimental conditions 15
2.3.2 Conventional identification 18
2.4 The incremental identification concept 21
2.4.1 Reactor modeling 22
2.4.2 Reactor model identification 23
2.5 Summary 26
3 Incremental identification Steps 28
3.1 Incremental identification The base case 28
3.1.1 Reaction flux estimation 29
3.1.1.1 Problem formulation 29
3.1.1.2 Calculation of regularized flux estimates 30
3.1.1.3 Reduction of measurement noise 31
3.1.2 Identification of a stoichiometric model 32
3.1.3 Reaction rate estimation 34
3.1.4 Identification of kinetic laws 36
3.1.4.1 Regression problem 36
3.1.4.2 Dependent reactions 37
3.1.4.3 Reversible reactions 38
V
3.2 Incremental identification Extensions 39
3.2.1 Incremental identification for incomplete measurements . 40
3.2.2 Identifiability and estimation of reaction rates 41
3.2.2.1 All reaction rates identifiable 41
3.2.2.2 Subset of reaction rates identifiable 41
3.2.3 Concentration estimation 43
3.2.3.1 Reconstruction of reaction fluxes 43
3.2.3.2 Calculation of concentration estimates 45
3.2.4 Unmeasured species in dependent reaction Systems 46
3.3 Incremental identification of the acetoacetylation System 47
3.3.1 Problem setting 48
3.3.2 Identification procedure 48
3.4 Conclusions 53
4 Extensions of the incremental concept 56
4.1 Identification of temperature dependencies 56
4.1.1 Incremental and combined estimation of temperature laws . . 57
4.1.1.1 Incremental estimation 57
4.1.1.2 Combined estimation 59
4.1.2 Application example: Acetoacetylation System 60
4.2 Multiple phases 64
4.2.1 Rate estimation in multi phase Systems 64
4.2.2 Application example: Two phase reactive System 68
4.2.2.1 The reactor model 68
4.2.2.2 Identification procedure 70
4.3 Distributed parameter Systems 72
4.3.1 Rate estimation in distributed Systems 73
4.3.2 Application example: Bncapsulated enzyme bead 75
4.3.2.1 Problem setting 75
4.3.2.2 Identification procedure 77
4.4 Conclusions and perspectives 81
5 Incremental identification of unstructured kinetic modeis 83
5.1 A function estimation algorithm based on hierarchically refined
sparse grids 85
5.1.1 Function approximation with sparse grids 87
5.1.1.1 The approximation concept 87
5.1.1.2 Conventional finite element discretization 88
VI
5.1.1.3 Sparse grids with uniform discretization 90
5.1.1.4 Sparse grids with variable discretization 91
5.1.2 The function estimation approach 93
5.1.2.1 Stepwise grid refinement algorithm 0 96
5.1.2.2 Selection of discretization and Tikhonov regularization 100
5.1.3 Case studies 103
5.1.3.1 Best estimates 104
5.1.3.2 Bivariate function examples 105
5.1.3.3 Trivariate and quadrivariate function examples . . . 112
5.1.3.4 Analysis of sensitivity calculation 114
5.1.3.5 Comparison of grid combination approaches 115
5.1.3.6 Discussion 116
5.1.3.7 Comparison to neural networks 117
5.1.4 Summary 119
5.2 Application example: Acetoacetylation System 120
5.2.1 Problem setting 120
5.2.2 Identification results 121
5.2.3 Reduced modeis 125
5.2.4 Mixed structured and unstructured kinetic modeis 126
5.3 Conclusions 127
6 The iterative identification methodology 129
6.1 Structured kinetic modeis 130
6.1.1 Work process for structured modeis 130
6.1.1.1 Parameter re adjustment and model validation . . . 131
6.1.1.2 Experimental design 132
6.1.2 Application example: Acetoacetylation system 133
6.2 Unstructured kinetic modeis 137
6.2.1 A heuristic coverage design for data driven approximators . . 140
6.2.1.1 Single input space coverage 140
6.2.1.2 Multiple input space coverage 142
6.2.2 Application example: Acetoacetylation system 145
6.3 Conclusions 151
7 Conclusions and perspectives 153
A Input estimation based on multi scale methods 160
A.l Theory 160
A.2 Example 162
VII
A.3 Conclusions 167
B Some investigations on derivative estimation using a filter approach 168
B.l Forward backward filtering 169
B.2 Choosing endpoint constraints 173
B.3 Combining the search for regularization parameter and endpoint
constraints 176
B.4 Validation on test functions 178
B.5 Conclusions 182
C Identifiability of two film mass transfer modeis 183
C.l The mass transfer model 184
C.2 Physical properties and experimental settings 186
C.3 Analysis of identifiability 188
C.4 Conclusions 191
D Derivation of the sparse grid sensitivity vector 192
E Sparse grid test functions 196
F Data scaling to unity domain 197
G Experimental design settings 199
Bibliography 201
VIII |
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| genre_facet | Hochschulschrift |
| id | DE-604.BV021797412 |
| illustrated | Illustrated |
| index_date | 2024-07-02T15:46:41Z |
| indexdate | 2024-08-01T11:15:24Z |
| institution | BVB |
| isbn | 3183864037 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015009980 |
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| physical | XX, 217 S. Ill., graph. Darst. |
| publishDate | 2006 |
| publishDateSearch | 2006 |
| publishDateSort | 2006 |
| publisher | VDI-Verl. |
| record_format | marc |
| series | Fortschritt-Berichte VDI |
| series2 | Fortschritt-Berichte VDI : Reihe 3, Verfahrenstechnik Berichte aus dem Lehrstuhl für Prozesstechnik RWTH Aachen |
| spellingShingle | Brendel, Marc Levin Incremental identification of complex reaction systems Fortschritt-Berichte VDI Reaktionskinetik (DE-588)4048655-2 gnd Reaktionssystem (DE-588)4177124-2 gnd Mathematisches Modell (DE-588)4114528-8 gnd |
| subject_GND | (DE-588)4048655-2 (DE-588)4177124-2 (DE-588)4114528-8 (DE-588)4113937-9 |
| title | Incremental identification of complex reaction systems |
| title_auth | Incremental identification of complex reaction systems |
| title_exact_search | Incremental identification of complex reaction systems |
| title_exact_search_txtP | Incremental identification of complex reaction systems |
| title_full | Incremental identification of complex reaction systems Marc Levin Brendel |
| title_fullStr | Incremental identification of complex reaction systems Marc Levin Brendel |
| title_full_unstemmed | Incremental identification of complex reaction systems Marc Levin Brendel |
| title_short | Incremental identification of complex reaction systems |
| title_sort | incremental identification of complex reaction systems |
| topic | Reaktionskinetik (DE-588)4048655-2 gnd Reaktionssystem (DE-588)4177124-2 gnd Mathematisches Modell (DE-588)4114528-8 gnd |
| topic_facet | Reaktionskinetik Reaktionssystem Mathematisches Modell Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015009980&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV001897067 |
| work_keys_str_mv | AT brendelmarclevin incrementalidentificationofcomplexreactionsystems |
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