Design, Simulation and Optimization of Adsorptive and Chromatographic Separations: A Hands-On Approach

A comprehensive resource to the construction, use, and modification of the wide variety of adsorptive and chromatographic separations Design, Simulation and Optimization of Adsorptive and Chromatographic Separations offers the information needed to effectively design, simulate, and optimize adsorptive and chromatographic separations for a wide range of industrial applications. The authors?noted experts in the field?cover the fundamental principles, the applications, and a range of modeling techniques for the processes. The text presents a unified approach that includes the ideal and intermediate equations and offers a wealth of hands-on case studies that employ the rigorous simulation packages Aspen Adsorption and Aspen Chromatography. The text reviews the effective design strategies, details design considerations, and the assumptions which the modelers are allowed to make. The authors also cover shortcut design methods as well as mathematical tools that help to determine optimal operating conditions. This important text: -Covers everything from the underlying pheonmena to model optimization and the customization of model code -Includes practical tutorials that allow for independent review and study -Offers a comprehensive review of the construction, use, and modification of the wide variety of adsorptive and chromatographic separations -Contains contributions from three noted experts in the field Written for chromatographers, process engineers, ehemists, and other professionals, Design, Simulation and Optimization of Adsorptive and Chromatographic Separations offers a comprehensive review of the construction, use, and modification of adsorptive and chromatographic separations.

Table of Contents:
Foreword by George E. Keller, II xi Preface xiii Software Selection and Copyright Notice xvii Acknowledgments xix About the Authors xxi List of Computer Files xxiii 1 Simulation of Adsorption Processes 1 1.1 Introduction to Gas-phase Adsorption Technologies 1 1.2 Core Concepts in Gas Adsorption 2 1.2.1 The Adsorption Process 2 1.2.2 How the Driving Forces Achieve Separation 3 1.3 Isotherms 4 1.3.1 The Langmuir Isotherm (1918) 5 1.3.2 The Linear Isotherm 5 1.3.3 The Brunauer–Emmett–Teller (BET) Isotherm (1938) 5 1.3.4 The Freundlich Isotherm (1906) 6 1.3.5 The Sips (Langmuir–Freundlich) Isotherm (1948) 6 1.3.6 The Toth Isotherm (1971) 6 1.3.7 Summary 6 1.4 The Properties of Packed Beds 6 1.4.1 Void Fractions 7 1.4.2 External Voids 8 1.4.3 Internal Voids 8 1.4.4 Densities 8 1.4.4.1 Bulk Density 8 1.4.4.2 Skeletal or Solid Density 9 1.4.4.3 Envelope or Particle Density 10 1.4.4.4 Caveats 10 1.4.5 Relationships 10 1.4.6 Gas-phase Behavior 10 1.4.6.1 Pressure Drop 10 1.4.6.2 Compressibility 11 1.5 PSA and TSA Implementation Details 12 1.5.1 Common Adsorbent Characteristics 12 1.5.2 Common Process Configurations 12 1.6 Introduction to Aspen Adsorption 13 1.7 PSAWorkshop: Aspen Adsorption Modeling for Air Separation 15 1.7.1 Adding Components to an Aspen Adsorption Simulation 17 1.7.2 Creating a Flowsheet in Aspen Adsorption 22 1.7.3 Specifying Operating Conditions: Tables and Forms 33 1.7.4 Scheduling Events with the Cycle Organizer 42 1.7.5 Running an Aspen Simulation 51 1.7.6 Viewing and Exporting Simulation Results 51 1.8 PSAWorkshop: Hydrogen Separation in Aspen Adsorption 57 1.8.1 Define the Components and Property Model 58 1.8.2 Creating a Flowsheet in Aspen Adsorption 63 1.8.3 Run a Breakthrough Simulation 65 1.8.4 Create the PSA Flowsheet 77 1.9 PSAWorkshop: Modeling Hydrogen Separation using gCSS 87 1.9.1 Define the Components and Property Models 91 1.9.2 Working with Model Libraries: Advanced Flowsheet Options 95 1.9.3 Introduction to Scripting: Set Repeated Values and Initialize Blocks 108 1.9.4 Inspecting Blocks: Advanced Operating Conditions 112 1.9.5 Defining the Cycle Organizer 119 1.9.6 Viewing Results 127 1.10 TSAWorkshop: Temperature Swing Adsorption for Air Drying 128 1.11 Conclusions 140 1.12 Practice Problems 143 1.12.1 Introducing a gas_interaction Unit intoWorkshop 1 143 1.12.2 Naphtha Upgrading Using Adsorption 145 1.13 Nomenclature 149 Bibliography 150 2 Simulation of SMB Chromatographic Processes 155 2.1 Introduction to Chromatography 155 2.1.1 Mathematical Differences from Gas Adsorption 155 2.1.1.1 The Trace Liquid Assumption 155 2.1.1.2 Concentration Versus Partial Pressure 156 2.1.2 Thermodynamic Differences from Gas Adsorption 156 2.1.2.1 Isotherms 156 2.1.2.2 Physical Property Models 156 2.2 Introduction to SMB Chromatography 156 2.3 SMB Implementation Details 157 2.3.1 Common Process Configurations 157 2.3.2 M-Values 160 2.3.3 Scale-Up Concerns 161 2.3.4 Pressure Drop Limitations 162 2.3.5 Introduction to OperationalModes 163 2.4 SMBWorkshop: Simulate a Four-Zone SMB in Aspen Chromatography for the Separation of Tröger’s Base Enantiomers 163 2.4.1 Creating a Flowsheet in Aspen Chromatography 163 2.4.2 Adding Components to an Aspen Chromatography Simulation 164 2.4.3 The Chrom_CCC_separator2 Block 165 2.4.4 Viewing Results 188 2.5 Tandem SMBWorkshop: Simulate a Separation with Dual SMB Columns 192 2.6 Practice Problems 194 2.6.1 RunWorkshop 2.4 as a Steady-State Simulation 194 2.6.2 Simulation of an Industrial-Scale Xylene Separation Using Literature Data 200 2.6.3 Simulate a Five-Zone SMB System for Separating Phenylalanine, Tryptophan, and Methionine 202 Bibliography 206 3 Shortcut Design of SMB Systems 213 3.1 General Concepts 213 3.1.1 Mass Balances 215 3.1.2 Differential Equations 217 3.1.3 The Method of Characteristics 218 3.2 TriangleTheory 219 3.2.1 Notations 219 3.2.2 Introduction 219 3.2.3 Constraints on the System 222 3.3 TriangleTheoryWorkshop: Design of a System for the Separation of Amino Acids 224 3.4 Exercise 1: Calculating Transitions in a Fixed Bed Using Mathematica 230 3.4.1 Differential Equations – Analysis 232 3.4.2 Constructing the Solution from Eigenvectors and Eigenvalues 238 3.4.3 Use the Steady-State Information to Constrain Operating 3.4.4 Calculate the Curves Defined by the Eigenvectors 241 3.4.5 Calculate the Eigenvalues along the Transition 244 3.4.6 Calculate the Concentrations in Time and Space 246 3.4.7 Account for ShockWaves 246 3.5 Exercise 2: Constructing the Constraints on the TMB System in Mathematica 249 3.6 StandingWave Design 253 3.6.1 StandingWave Design in a Nonlinear Ideal System 254 3.6.2 StandingWave Design in a System with Nonlinear Isotherm and Significant Mass Transfer Effects 261 3.7 StandingWave DesignWorkshop: Calculating the Operating Conditions for an Ideal and a Nonideal System 265 3.8 Conclusions 271 3.9 Practice Problems 272 3.9.1 Use the TriangleTheory Tool and the StandingWave Design Tool to Create an Aspen Simulation of the Separation of 1-phenol-1-propanol on Tribenzoate 272 Bibliography 274 4 Operational Modes of SMB Processes 283 4.1 Overview 283 4.2 Selection of OperationalModes 284 4.3 Varicol 284 4.3.1 Design Heuristics and Examples 286 4.3.2 Workshop 1: Apply Varicol to the 4-Zone SMB Model 287 4.4 PowerFeed 293 4.4.1 Design Heuristics and Examples 294 4.4.2 Workshop 2: Apply PowerFeed to the Four-Zone SMB Model 297 4.5 ModiCon 309 4.5.1 Design Heuristics and Examples 309 4.5.2 Workshop 3: Apply ModiCon to the 4-Zone SMB Model 315 4.6 Combined Modes 323 4.6.1 Workshop 4: Extend Previously Created Flowsheets 323 4.7 Parallel Two Zones 330 4.7.1 Introduction to Parallel Two Zones 330 4.7.2 Specification Analysis 334 4.7.3 Importing Flowsheets 337 4.8 Conclusions 345 4.9 Practice Problems 345 4.9.1 Simulation of a Five-Zone SMB Unit Using the ModiCon Operational Mode 345 4.9.2 Compare Parallel Two-Zone Results with SMB Results 345 Bibliography 347 5 Parameter Estimation, Regression, and Sensitivity of Adsorptive and Chromatographic Processes 349 5.1 Empirical Correlations for Physical Properties 349 5.1.1 Axial Dispersion Coefficient 349 5.1.2 Mass Transfer Coefficient 350 5.1.3 Caveats 351 5.2 ParameterWorkshop: Regressing against Steady-State Experiments 351 5.2.1 Introduction to "Experiments" In Aspen Software 351 5.2.2 Experimental Data 352 5.2.3 Parameter Regression in Excel 352 5.2.4 Parameter Regression in Aspen Chromatography 363 5.2.4.1 Defining an Estimation Flowsheet 363 5.2.4.2 Entering Experimental Data 364 5.2.4.3 Estimation Settings 368 5.2.4.4 Running an Estimation 370 5.2.5 Parameter Regression In Mathematica 370 5.2.5.1 Defining the Functions 371 5.2.5.2 Entering the Data 372 5.2.5.3 Regression 375 5.3 ParameterWorkshop: Regressing Against Dynamic Experiments 376 5.3.1 Problem Description 376 5.3.2 Dynamic Estimation Settings 376 5.3.3 Performance Concerns 380 5.4 Xylene Parameter Regression 380 5.5 Conclusions 386 5.6 Practice Problems 387 5.6.1 Perform Dynamic Parameter Estimation in Aspen Adsorption 387 5.6.2 Sensitivity Analysis Using Scripts in Aspen Adsorption 389 Bibliography 393 Literature Cited in the Text 395 Index 399

About the Author :
Y.A. Liu, the Alumni Distinguised Professor and the Frank C. Vilbrandt Endowed Professor of Chemical Engineering at Virginia Tech, received his B.S. (1967), M.S. (1970), and Ph.D. (1974) degrees from National Taiwan University, Tufts University and Princeton University, respectively. Professor Liu devoted his school breaks helping petrochemical industries in developing countries and chemical industries in Virginia with technology development and engineering training. He has taught intensive training courses on computer-aided design, advanced process control, energy and water savings, and refinery and polymerization process modeling to over 7,000 practicing engineers in China, Taiwan and United States. Kevin Wood received his Ph.D. in the Department of Chemical Engineering at Virginia Polytechnic Institute and State University (?Virginia Tech?) in June, 2016. He received his B.S. in chemical engineering from Purdue University in 2010. He completed his doctoral dissertation on the development of computational tools for the design of SMB systems, and design of software to enable Aspen simulations to be run in parallel. The tools he developed, and simulations he ran using them, form the basis of this textbook. He has worked on industrial modeling projects, including biodiesel, CO2 capture, and xylene separation. These projects were collaborative efforts between Virginia Tech, Aspen Technology, and industrial partners. Yueying Yu received her Ph.D. in the Department of Chemical Engineering at Virginia Tech in December, 2015. She received her B.S. in chemical engineering from Dalian University of Technology in China in 2009. She completed her doctoral dissertation on the simulation and comparison of operational modes in simulated moving bed (SMB) chromatography and gas-phase adsorptive separation. This is a part of the basis of this book.