Advanced pH Measurement and Control
Description
Advanced pH Measurement and Control: Digital Twin Synergy and Advances in Technology details system design, installation, maintenance and ongoing improvement, including a special focus on how digital twins and first-principles charge balance contribute to innovation, operability, productivity, reliability and maintainability. It offers insights into key principles and advances in electrode technology and diagnostics, including a simple and largely untapped method for computing titration curves that match laboratory curves, as well as guidance on selecting and implementing the best control valves and strategies.
The extraordinary sensitivity and rangeability of pH used for measuring and controlling hydrogen concentration introduce many challenges in managing the nonlinearity in the control loop and the precision needed for the control valve. This, combined with pH's critical role in maintaining cell health in biological processes, as well as in the production of clean water, food, pharmaceuticals and chemicals, makes the best pH control system particularly important and challenging. Despite these challenges, the outcomes can lead to significant reductions in equipment costs and, more importantly, substantial improvements in system reliability and performance.
Finally, the appendices cover fundamental principles and provide guidance on using new PID features to reduce project costs and maximize process efficiency, capacity and safety.
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Persons
Gregory K. McMillan, CAP, has more than 50 years of experience in industrial process automation, with an emphasis on the synergy of dynamic modeling and process control. He retired as a Senior Fellow from Solutia and a senior principal software engineer from Emerson Process Systems and Solutions. He was also an adjunct professor in the Washington University Saint Louis Chemical Engineering department from 2001 to 2004. McMillan is the author of numerous ISA books and columns on process control, and he has been the monthly Control Talk columnist for Control magazine since 2002. He started and guided the ISA Standards and Practices committee on ISA-TR5.9-2023, PID Algorithms and Performance Technical Report, and he wrote "Annex A - Valve Response and Control Loop Performance, Sources, Consequences, Fixes, and Specifications" in ISA-TR75.25.02-2000 (R2023), Control Valve Response Measurement from Step Inputs. McMillan's achievements include the ISA Kermit Fischer Environmental Award for pH control in 1991, appointment to ISA Fellow in 1991, the Control magazine Engineer of the Year Award for the Process Industry in 1994, induction into the Control magazine Process Automation Hall of Fame in 2001, selection as one of InTech magazine's 50 Most Influential Innovators in 2003, the ISA Life Achievement Award in 2010, and the ISA Mentoring Excellence award in 2020. He has a BS in engineering physics from Kansas University and an MS in control theory from Missouri University of Science and Technology, both with emphasis on industrial processes.
Christopher Stuart is a senior software engineer in the Process Simulation Development group at Emerson Process Systems and Solutions. He holds a bachelor of science degree in chemical engineering with a biochemical emphasis from Missouri University of Science and Technology. Stuart's research interests are in efficient algorithms for thermodynamic calculations and dynamic simulations.
Dean Cook is the Mimic product manager in the Process Simulation Development group at Emerson Process Systems and Solutions. He holds a bachelor of science degree in physics from Western Illinois University, has 30 years of experience developing dynamic simulation software, and continues to drive toward improving training and process optimization for a wide range of industries.
Zachary Sample is a digital enterprise consultant in Marketing/Business Development for Emerson Process Systems and Solutions. He has over 10 years of experience delivering cross-industry simulation solutions in various roles ranging from technical implementation and engineering to project management and consulting. In these roles, he has had a passion for helping process companies better leverage simulation to improve automation and operational performance. He has a bachelor of science degree in chemical engineering from Missouri University of Science and Technology and a master of science degree in chemical engineering from North Carolina State University.
Content
Acknowledgments vii
About the Authors xv
Preface xvii
Chapter 1 The Essentials 1
1.1 The Heart of the Matter 1
1.2 Stage Fright 9
1.3 Size Does Matter 14
1.4 One Is the Loneliest Number 17
1.5 Acceleration and Stagnation 22
1.6 Life Is a Batch 25
1.7 Industrial Importance 27
1.8 The Real Deal 27
1.9 Best Practices 28
Chapter 2 The Chemistry 33
2.1 ¿Nearly Normal 33
2.2 ¿Staying Active 38
2.3 ¿Free Dissociation 40
2.4 A Question of Balance 46
2.5 Best Practices 50
Chapter 3 Titration Curves 53
3.1 ¿Slippery Slopes 53
3.2 Laboratory Generation 59
3.3 Computer Generation 64
3.4 Field Generation 66
3.5 Buffering 68
3.6 Uses 70
3.7 Best Practices 70
Chapter 4 Electrodes 73
4.1 A Dose of Reality 73
4.2 Measurement Electrodes 92
4.3 Reference Electrodes 99
4.4 Great Expectations and Practical Limitations 102
4.5 Smart Transmitters 123
4.6 Failure Protection 125
4.7 Dynamic Response of Electrodes, Holders, and Sample Systems 126
4.8 Installation Practices 130
4.9 Calibration Procedures 136
4.10 Troubleshooting Logic 141
4.11 Best Practices 149
Chapter 5 Mixing Equipment 155
5.1 What Was Good Might Be Bad 155
5.2 Mixing Dynamics 157
5.3 Agitated Vessels 159
5.4 Static Mixers 169
5.5 Sumps, Ponds, and Lagoons 170
5.6 Best Practices 171
Chapter 6 Control Valves 173
6.1 A Moving Story 173
6.2 Resolution Requirements 178
6.3 Rangeability Requirement 181
6.4 Split-Ranging 184
6.5 Best Practices 186
Chapter 7 Reagent 191
7.1 Delivery Dilemmas 191
7.2 Dilution 194
7.3 Buffering 196
7.4 Dissolution 197
7.5 Special Strategies 200
7.6 Best Practices 203
Chapter 8 Control System 205
8.1 Feedback Control 205
8.2 Feedforward Control 207
8.3 Cascade Control 210
8.4 ¿Linear Reagent Demand Control 212
8.5 ¿Adaptive Control 216
8.6 Advanced Batch Control 219
8.7 Online Dynamic pH Estimators 224
8.8 Model Predictive Control 225
8.9 Real-Time Optimization 227
8.10 Dynamics and Performance 227
8.11 PID Tuning 258
8.12 ¿External Reset Feedback 272
8.13 ¿System Selection 278
8.14 ¿Best Practices 285
Chapter 9 Digital Twin 289
9.1 ¿Introduction 289
9.2 Key Features 293
9.3 ¿Spectrum of Uses 298
9.4 ¿Implementation 306
9.5 ¿Data-Driven Dynamics 308
9.6 ¿Titration Curve Modeling 310
9.7 ¿Instrumentation Modeling 313
9.8 ¿Speedup 321
9.9 ¿Performance Monitoring 322
9.10 ¿Generating and Fitting Profiles 323
9.11 ¿Best Practices 324
References 328
Appendix A: Automation System Performance Top 10 Concepts 329
Appendix B: Questions and Answers 345
Appendix C: Control Valve Positioners 357
Appendix D: Review of Algebra with Logarithms 369
Appendix E: Enhanced PID 371
Appendix F: First-Principle Process Relationships 377
Appendix G: Gas Pressure Dynamics 395
Appendix H: Charge Balance to Model pH 397
Appendix I: Interactive to Noninteractive Time Constant Conversion 407
Appendix J: Jacket and Coil Temperature Control 411
Appendix K: PID Forms and Conversion of Tuning Settings 417
Appendix L: Liquid Mixing Dynamics 425
Appendix M: Modeling pH Systems in Digital Twin 429
Index 437