Process Systems Engineering, 9. Domain Engineering

Abstract

The article contains sections titled: 1. Molecular Modeling and Simulation for Chemical Product and Process Design 1.1. Introduction 1.2. Elementary Statistical Mechanics 1.3. Major Molecular Simulation Methods 1.3.1. Molecular Dynamics (MD) 1.3.2. Metropolis Monte Carlo Simulation 1.4. Applications 1.4.1. Pharmaceuticals 1.4.2. Polymer Membranes for Gas Separation 1.4.3. Ionic Liquids for Sustainable Chemical Processes 1.5. Conclusions 2. Energy Systems Engineering 2.1. Introduction 2.2. Methods/Tools/Algorithm 2.2.1. Superstructure‐Based Modeling 2.2.2. Mixed‐Integer Programming (MIP) 2.2.3. Multiobjective Optimization 2.2.4. Optimization under Uncertainty 2.2.5. Life‐Cycle Assessment 2.3. Energy Systems Examples 2.3.1. Example 1–Polygeneration Energy Systems 2.3.2. Example 2–Hydrogen Infrastructure Planning 2.3.3. Example 3–Energy Systems in Commercial Buildings 2.4. Conclusions and Future Directions 3. Pharmaceutical Processes 3.1. Introduction 3.2. Pharmaceutical Process Development and Operation 3.2.1. Crystallization 3.2.2. Chromatography 3.3. Conclusion 4. Biochemical Engineering 4.1. Introduction 4.2. Industrial Biotechnology Processes 4.2.1. Fermentation Processes 4.2.2. Microbial Catalysis 4.2.3. Enzyme Processes 4.3. Modeling of Bioprocesses 4.3.1. Modeling of Bioprocesses–Mechanistic Models 4.3.2. Modeling of Bioprocesses–Data‐Driven Models 4.4. The Role of Process Systems Engineering 4.4.1. Evaluation of Process Options 4.4.2. Evaluation of Platform Chemicals 4.4.3. Process Integration 4.4.4. Biorefinery Design 4.4.5. Biocatalyst Design 4.5. Assessing the Sustainability of Bioprocesses 4.5.1. Life‐Cycle Inventory and Assessment 4.6. Future Outlook and Perspectives 5. Policies and Policy Making 5.1. Introduction 5.2. Policies and Policy Measures 5.3. Policy Making and the Systems Approach 5.4. Similarities between Policy Formulation and Conceptual Process Design 5.5. The Nature of Policy Formulation 5.6. The Nature of Sociotechnical Systems 5.7. Challenges for Modelers of Sociotechnical Systems 5.7.1. Multiple Stakeholders 5.7.2. Incommensurable Values 5.7.3. Externalities 5.7.4. Uncertainty 5.7.5. Emergent Behavior 5.7.6. Complexity of Causation 5.7.7. Objectivity in Policy Analysis 5.8. Types of Models used in the Analysis of Policies 5.8.1. Macroeconomic Models (Mainstream, Descriptive, Aggregated, Mechanistic) 5.8.2. Optimization Models (Mainstream, Normative, Aggregated, Mechanistic) 5.8.3. Control Models (Mainstream, Normative, Aggregated, Mechanistic) 5.8.4. Data‐Based Models 5.8.5. Game Theory (Descriptive) 5.8.6. System Dynamics (Aggregated, Mechanistic) 5.8.7. Network Theory (Descriptive) 5.8.8. Agent‐Based Approaches 5.8.9. Some Conclusions on Models for the Analysis of Policies 5.9. Synthesis of Policies 5.10. Future Directions 6. Acknowledgments