Computer Aided Process and Product Engineering (CAPE)

Computer aided process engineering (CAPE) tools have been very successfully used in process design and product engineering for a long time. In particular, simulation and modelling tools have enabled engineers to analyse and understand the behaviour of selected processes prior to building actual plants. The aim of design or retrofit of chemical processes is to produce profitably products that satisfy the societal needs, ensuring safe and reliable operation of each process, as well as minimising any effects on the environment. This involves the conceptual design or retrofit of plants and processes, novel manufacturing approaches, process/control system design interactions and operability, manufacturability, environmental and safety issues. Backed by current studies, the book gives a comprehensive survey of the various approaches and latest developments on the use of CAPE in the process industry. An invaluable reference to the scientific and industrial community in the field of computer aided process and product engineering.

Table of Contents:
Preface. Foreword. List of Contributors. Volume 1. 1 Introduction. Section 1 Computer-aided Modeling and Simulation. 1 Large-Scale Algebraic Systems (Guido Buzzi Ferraris and Davide Manca). 1.1 Introduction. 1.2 Convergence Tests. 1.3 Substitution Methods. 1.4 Gradient Method (Steepest Descent). 1.5 Newton's Method. 1.6 Modified Newton's Methods. 1.7 Quasi-Newton Methods. 1.8 Large and Sparse Systems. 1.9 Stop Criteria. 1.10 Bounds, Constraints, and Discontinuities. 1.11 Continuation Methods. 2 Distributed Dynamic Models and Computational Fluid Dynamics (Young-il Lim and Sten Bay Jorgensen). 2.1 Introduction. 2.2 Partial Differential Equations. 2.3 Method of Lines. 2.4 Fully Discretized Method. 2.5 Advanced Numerical Methods. 2.6 Applications. 2.7 Process Model and Computational Fluid Dynamics. 2.8 Discussion and Conclusion. 3 Molecular Modeling for Physical Property Prediction (Vincent Gerbaud and Xavier Joulia). 3.1 Introduction. 3.2 What is Molecular Modeling? 3.3 Statistical Thermodynamic Background. 3.4 Numerical Sampling Techniques. 3.5 Interaction Energy. 3.6 Running the Simulations. 3.7 Applications. 3.8 Conclusions. 4 Modeling Frameworks of Complex Separation Systems (Michael C. Georgiadis, Eustathios S. Kikkinides, and Margaritis Kostoglou). 4.1 Introduction. 4.2 A Modeling Framework for Adsorption-Diffusion-based Gas Separation Processes. 4.3 Modeling of PSA Processes in gPROMS. 4.4 Efficient Modeling of Crystallization Processes. 4.5 Modeling of Grinding Processes. 4.6 Concluding Remarks. 5 Model Tuning, Discrimination, and Verification (Katalin M. Hangos and Rozalia Lakner). 5.1 Introduction. 5.2 The Components and Structure of Process Models. 5.3 Model Discrimination: Model Comparison and Model Transformations. 5.4 Model Tuning. 5.5 Model Verification. 6 Multiscale Process Modeling (Ian T. Cameron, Gordon D. Ingram, and Katalin M. Hangos). 6.1 Introduction. 6.2 Multiscale Nature of Process and Product Engineering. 6.3 Modeling in Multiscale Systems. 6.4 Multiscale Model Integration and Solution. 6.5 Future Challenges. 7 Towards Understanding the Role and Function of Regulatory Networks in Microorganisms (Krist V. Gernaey, Morten Lind, and Sten Bay Jorgensen). 7.1 Introduction. 7.2 Central Dogma of Biology. 7.3 Complexity of Regulatory Networks. 7.4 Methods for Mapping the Complexity of Regulatory Networks. 7.5 Towards Understanding the Complexity of Microbial Systems. 7.6 Discussion and Conclusions. Section 2 Computer-aided Process and Product Design. 1 Synthesis of Separation Processes (Petros Proios, Michael C. Georgiadis, and Efstratios N. Pistikopoulos). 1.1 Introduction. 1.2 Synthesis of Simple Distillation Column Sequences. 1.3 Synthesis of Heat-integrated Distillation Column Sequences. 1.4 Synthesis of Complex Distillation Column Sequences. 1.5 Conclusions. 2 Process Intensification (Patrick Linke, Antonis Kokossis, and Alberto Alva-Argaez). 2.1 Introduction. 2.2 Process Intensification Technologies. 2.3 Computer-Aided Methods for Process Intensification. 2.4 Concluding Remarks. 3 Computer-aided Integration of Utility Systems (Francois Marechal and Boris Kalitventzeff). 3.1 Introduction. 3.2 Methodology for Designing Integrated Utility Systems. 3.3 The Energy Conversion Technologies Database. 3.4 Graphical Representations. 3.5 Solving the Energy Conversion Problem Using Mathematical Programming. 3.6 Solving Multiperiod Problems. 3.7 Example. 3.8 Conclusions. 4 Equipment and Process Design (I. David, L. Bogle, and B. Eric Ydstie). 4.1 Introduction. 4.2 The Structure of Process Models. 4.3 Model Development. 4.4 Computer-aided Process Modeling and Design Tools. 4.5 Introduction to the Case Studies. 4.6 Conclusions. 5 Product Development (Andrzej Kraslawski). 5.1 Background. 5.2 Definition Phase. 5.3 Product Design. 5.4 Summary. Volume 2. Section 3 Computer-aided Process Operation. 1 Resource Planning (Michael C. Georgiadis and Panagiotis Tsiakis). 1.1 Introduction. 1.2 Planning in the Process Industries. 1.3 Planning for New Product Development. 1.4 Tactical Planning. 1.5 Resource Planning in the Power Market and Construction Projects. 1.6 Solution Approaches to the Planning Problem. 1.7 Software Tools for the Resource Planning Problem. 1.8 Conclusions. 2 Production Scheduling (Nilay Shah). 2.1 Introduction. 2.2 The Single-Site Production Scheduling Problem. 2.3 Heuristics/Metaheuristics: Specific Processes. 2.4 Heuristics/Metaheuristics: General Processes. 2.5 Mathematical Programming: Specific Processes. 2.6 Mathematical Programming: Multipurpose Plants. 2.7 Hybrid Solution Approaches. 2.8 Combined Scheduling and Process Operation. 2.9 Uncertainty in Planning and Scheduling. 2.10 Industrial Applications of Planning and Scheduling. 2.11 New Application Domains. 2.12 Conclusions and Future Challenges. 3 Process Monitoring and Data Reconciliation (Georges Heyen and Boris Kalitventzeff). 3.1 Introduction. 3.2 Introductory Concepts for Validation of Plant Data. 3.3 Formulation. 3.4 Software Solution. 3.5 Integration in the Process Decision Chain. 3.6 Optimal Design of Measurement System. 3.7 An Example. 3.8 Conclusions. 4 Model-based Control (Sebastian Engell, Gregor Fernholz, Weihua Gao, and Abdelaziz Toumi). 4.1 Introduction. 4.2 NMPC Applied to a Semibatch Reactive Distillation Process. 4.3 Control of Batch Chromatography Using Online Model-based Optimization. 4.4 Control by Measurement-based Online Optimization. 4.5 Nonlinear Model-based Control of a Reactive Simulated Moving Bed (SMB) Process. 4.6 Conclusions. 5 Real Time Optimization (Vivek Dua, John D. Perkins, and Efstratios N. Pistikopoulos). 5.1 Introduction. 5.2 Parametric Programming. 5.3 Parametric Control. 5.4 Hybrid Systems. 5.5 Concluding Remarks. 6 Batch and Hybrid Processes (Luis Puigjaner and Javier Romero). 6.1 Introduction. 6.2 The Flexible Recipe Concept. 6.3 The Flexible Recipe Model. 6.4 Flexible Recipe Model for Recipe Initialization. 6.5 Flexible Recipe Model for Recipe Correction. 6.6 Final Considerations. 7 Supply Chain Management and Optimization (Lazaros G. Papageorgiou). 7.1 Introduction. 7.2 Key Features of Supply Chain Management. 7.3 Supply Chain Design and Planning. 7.4 Analysis of Supply Chain Policies. 7.5 Multienterprise Supply Chains. 7.6 Software Tools for Supply Chain Management. 7.7 Future Challenges. Section 4 Computer-integrated Approaches in CAPE. 1 Integrated Chemical Product-Process Design: CAPE Perspectives (Rafiqul Gani). 1.1 Introduction. 1.2 Design Problem Formulations. 1.3 Issues and Needs. 1.4 Framework for Integrated Approach. 1.5 Conclusion. 2 Modeling in the Process Life Cycle (Ian T. Cameron and Robert B. Newell). 2.1 Cradle-to-the-Grave Process and Product Engineering. 2.2 Industrial Practice and Demands in Life-Cycle Modeling. 2.3 Applications of Modeling in the Process Life Cycle: Some Case Studies. 2.4 Challenges in Modeling Through the Life Cycle. 3 Integration in Supply Chain Management (Luis Puigjaner and Antonio Espuna). 3.1 Introduction. 3.2 Current State of Supply Chain Management Integration. 3.3 Agent-based Supply Chain Management Systems. 3.4 Environmental Module. 3.5 Financial Module. 3.6 Multiagent Architecture Implementation and Demonstration. 3.7 Concluding Remarks. 4 Databases in the Field of Thermophysical Properties in Chemical Engineering (Richard Sass). 4.1 Introduction. 4.2 Overview of the Thermophysical Properties Needed for CAPE Calculations. 4.3 Sources of Thermophysical Data. 4.4 Examples of Databases for Thermophysical Properties. 4.5 Special Case and New Challenge: Data of Electrolyte Solutions. 4.6 Examples of Databases with Properties of Electrolyte Solutions. 4.7 A Glance at the Future of the Properties Databases. 5 Emergent Standards (Jean-Pierre Belaud and Bertrand Braunschweig). 5.1 Introduction. 5.2 Current CAPE Standards. 5.3 Emergent Information Technology Standards. 5.4 Conclusion (Economic, Organizational, Technical, QA). Section 5 Applications. 1 Integrated Computer-aided Methods and Tools as Educational Modules (Rafiqul Gani and Jens Abildskov). 1.1 Introduction. 1.2 Integrated Approach to CAPE. 1.3 Educational Modules. 1.4 Conclusion. 2 Data Validation: a Technology for Intelligent Manufacturing (Boris Kalitventzeff, Georges Heyen, and Miguel Mateus). 2.1 Introduction. 2.2 Basic Aspects of Validation: Data Reconciliation. 2.3 Specific Assets of Information Validation. 2.4 Advanced Features of Validation Technology. 2.5 Applications. 2.6 Conclusion. 3 Facing Uncertainty in Demand by Cost-effective Manufacturing Flexibility (Petra Heijnen and Johan Grievink). 3.1 Introduction. 3.2 The Production Planning Problem. 3.3 Mathematical Description of the Planning Problem. 3.4 Modeling the Profit of the Production Planning. 3.5 Modeling the Objective Functions. 3.6 Solving the Optimization Problem. 3.7 Sensitivity Analysis of the Optimization. 3.8 Implementation of the Optimization of the Production Planning. 3.9 Conclusions and Final Remarks. Authors' Index. Subject Index.

About the Author :
Luis Puigjaner obtained his M.S. (Engineering) degree from the UPC, and a Ph.D. degree from the Polytechnic University of Madrid. He holds also a MS degree from the University of Houston. He became a member of the Higher Scientific Research Council of Spain (1972) and is currently Professor of Chemical Engineering at UPC, Director of the Environmental Center (LCMA) and the Head of a research group of 32 people with several projects in different areas of process systems engineering. He has over 350 refereed publications. His professional experience includes teaching and research positions at several Institutions (Purdue University, Stanford University, Max Planck Institute, and King's College, University of Houston, Imperial College, Cork Technical College, UNAM, UNICAMP and NASA). Georges Heyen is a professor in Chemical Engineering at the University of Liege, Belgium, with teaching, research and consultancy interests in process systems engineering. He teaches courses ranging from applied chemical thermodynamics to modelling and plant design. He took part in several international projects financed by the European Union to carry research and development on process optimisation tools and methods, in collaboration with major European universities and research centres. He is one of the founders of the company Belsim, which is active in software development for process modelling and optimisation, especially using online data validation techniques.

Review :
"This selection serves as a definitive summary of CAPE..." (Electric Review, March/April 2008)