Gonzalo Guillén Gosálbez: Katalogdaten im Herbstsemester 2024 |
| Name | Herr Prof. Dr. Gonzalo Guillén Gosálbez |
| Lehrgebiet | Chemisches System-Engineering |
| Adresse | Chemisches System-Engineering ETH Zürich, HCI G 135 Vladimir-Prelog-Weg 1-5/10 8093 Zürich SWITZERLAND |
| Telefon | +41 44 633 40 84 |
| gonzalo.guillen.gosalbez@chem.ethz.ch | |
| Departement | Chemie und Angewandte Biowissenschaften |
| Beziehung | Ordentlicher Professor |
| Nummer | Titel | ECTS | Umfang | Dozierende | |
|---|---|---|---|---|---|
| 529-0459-01L | Case Studies in Process Design | 3 KP | 3A | G. Guillén Gosálbez | |
| Kurzbeschreibung | The learning objective is to design, simulate and optimize a real (bio-)chemical process from a process systems perspective. Specifically, a commercial process simulation software (Aspen) will be used for the process simulation and optimization. Students have to integrate knowledge and develop engineering thinking and skills acquired in the other courses of the curriculum. | ||||
| Lernziel | Simulate and optimize a chemical production process using commercial process simulation software. | ||||
| Inhalt | Create a model describing the production process - Students will apply a commercial process simulator systematically for process creation and analysis. - Students will create a process simulation flowsheet for steady-state simulation. Evaluate the performance of the production process - Students will analyse and understand the degrees of freedom in modelling process units and flowsheets. - Students will understand the role of process simulators in process creation. - Students will make design specifications and follow the iterations implemented to satisfy them. - Students will judge the role of process simulators in equipment sizing and costing and profitability analysis. - Students will assess the economic performance of the process, including operating costs (OPEX), and capital investment (CAPEX), based on the outcome of the simulation model. - Students will assess the environmental impact of the production process following the Life Cycle Assessment (LCA) methodology. Optimize the design and operating conditions of the production process - Students will carry out sensitivity analyses and optimizations considering technical and economic criteria. - Students will generate process integration alternatives to improve the initial design. - Students will optimize the production process considering economic and environmental criteria. | ||||
| Voraussetzungen / Besonderes | Before the case study week, students are encouraged to participate in the exercises of the course "Process Simulation and Flowsheeting" in order to get familiar with the Aspen Plus simulation software (this is highly recommended, but not mandatory). The problem statement and detailed instructions are provided in the project brief made available at the beginning of the case study week. During the case study week: - Students work in teams of 4-6 people. - Students have to pose and solve process equipment and system design related problems. - Students have to coordinate the activities, the preparation of the written report and the oral presentation. - Students get support from project assistants and the course supervisor. The groups deliver the written report on a predefined date. The students receive the feedback and are asked to implement some changes in their reports. A final presentation takes place summarizing the main findings of the project. | ||||
| 529-0549-01L | Case Studies in Process Design I | 3 KP | 3A | G. Guillén Gosálbez, J. Dolenc, U. Fischer | |
| Kurzbeschreibung | Schwerpunkt von Teil I der Fallstudie ist eine literaturbasierte Gegenüberstellung verschiedener Prozessvarianten. Zu diesem Zweck sollen relevante Daten über einen vorgegebenen Prozess gesammelt und eine vergleichende Prozessbeurteilung erarbeitet werden. Eine vielversprechende Prozessvariante wird in der Folge ausgewählt und ein Blockdiagramm sowie Massen- und Energiebilanzen erstellt. | ||||
| Lernziel | - Kennenlernen verschiedener Informationsträger - Anwendung des Stoffes aus den Vorlesungen - Problemzentriertes Vorgehen (Anwendung verschiedener Methoden auf den selben Gegenstand) - Projektarbeit (Planung, Teamarbeit) - Berichterstattung und Vortragstechnik | ||||
| Inhalt | Schwerpunkt von Teil I der Fallstudie ist eine literaturbasierte Gegenüberstellung verschiedener Prozessvarianten. Zu diesem Zweck sollen relevante Daten über einen vorgegebenen Prozess zusammengetragen und bearbeitet werden. Dies sind zum einen Stoffdaten (physiko-chemische, toxikologische, sicherheits- und umweltrelevante Daten für die beteiligten Stoffe) und zum anderen Informationen über Synthesewege und deren technische Realisierung (Reaktionsmechanismen und Kinetik, benötigte Aufarbeitungs- und Trennverfahren, sowie ökonomische Kenngrössen, Umwelt- und Sicherheitsaspekte). Anhand dieser aus Literatur und Datenbanken zusammengetragenen Informationen und qualitativer und quantitativer Zielgrössen erfolgt eine erste vergleichende Prozessbeurteilung. Eine vielversprechende Prozessvariante wird in der Folge ausgewählt und ein Blockdiagramm sowie Massen- und Energiebilanzen erstellt. | ||||
| 529-0613-01L | Process Simulation and Flowsheeting | 6 KP | 3G | G. Guillén Gosálbez | |
| Kurzbeschreibung | This course encompasses the theoretical principles of chemical process simulation and optimization, as well as its practical application in process analysis. The techniques for simulating stationary and dynamic processes are presented, and illustrated with case studies. Commercial software packages (Aspen) are introduced for solving process flowsheeting and optimization problems. | ||||
| Lernziel | This course aims to develop the competency of chemical engineers in process flowsheeting, process simulation and process optimization. Specifically, students will develop the following skills: - Deep understanding of chemical engineering fundamentals: the acquisition of new concepts and the application of previous knowledge in the area of chemical process systems and their mechanisms are crucial to intelligently simulate and evaluate processes. - Modeling of general chemical processes and systems: students should be able to identify the boundaries of the system to be studied and develop the set of relevant mathematical relations, which describe the process behavior. - Mathematical reasoning and computational skills: the familiarization with mathematical algorithms and computational tools is essential to be capable of achieving rapid and reliable solutions to simulation and optimization problems. Hence, students will learn the mathematical principles necessary for process simulation and optimization, as well as the structure and application of process simulation software. Thus, they will be able to develop criteria to correctly use commercial software packages and critically evaluate their results. - Process optimization: the students will learn how to formulate optimization problems in mathematical terms, the main type of optimization problems that exist (i.e., LP, NLP, MILP and MINLP) and the fundamentals of the optimization algorithms implemented in commercial solvers. | ||||
| Inhalt | Overview of process simulation and flowsheeting: - Definition and fundamentals - Fields of application - Case studies Process simulation: - Modeling strategies of process systems - Mass and energy balances and degrees of freedom of process units and process systems Process flowsheeting: - Flowsheet partitioning and tearing - Solution methods for process flowsheeting - Simultaneous methods - Sequential methods Process optimization and analysis: - Classification of optimization problems - Linear programming, LP - Non-linear programming, NLP - Mixed-integer linear programming, MILP - Mixed-integer nonlinear programming, MINLP Commercial software for simulation (Aspen Plus): - Thermodynamic property methods - Reaction and reactors - Separation / columns - Convergence, optimisation & debugging | ||||
| Literatur | An exemplary literature list is provided below: - Biegler, L.T., Grossmann, I.E., Westerberg, A.W. Systematic methods of chemical process design, Prentice Hall International PTR (1997). - Douglas, J.M. Conceptual design of chemical processes, McGraw-Hill (1988). - Edgar, T. F., Himmelblau, D. M. Optimization of chemical process, Mcgraw Hill Chemical Engineering Series (2001). - Haydary, J. Chemical Process Design and Simulation, Wiley (2019). - Seider, W.D., Seader, J.D., Lwin, D.R., Widagdo, S. Product and process design principles: synthesis, analysis, and evaluation, John Wiley & Sons, Inc. (2010). - Sinnot, R.K., Towler, G. Chemical Engineering Design, Butterworth-Heinemann (2009). - Smith, R. Chemical process design and integration, Wiley (2005). - Turton, R., A. Shaeiwitz, Bhattacharyya, D., Whiting, W. Synthesis and Design of Chemical Processes, Prentice Hall (2013). | ||||
| Voraussetzungen / Besonderes | A basic understanding of material and energy balances, thermodynamic property methods and typical unit operations (e.g., reactors, flash separations, distillation/absorption columns etc.) is required. | ||||
| 529-0643-01L | Process Design and Development  | 6 KP | 3G | G. Guillén Gosálbez | |
| Kurzbeschreibung | The course is focused on the design of Chemical Processes, with emphasis on the preliminary stages of the design approach, where process creation and quick selection among many alternatives are important. The main concepts behind more detailed process design and process simulation are also examined. | ||||
| Lernziel | The course is focused on the design of Chemical Processes, with emphasis on the preliminary stage of the design approach, where process creation and quick selection among many alternatives are important. The main concepts behind more detailed process design and process simulation are also examined. | ||||
| Inhalt | Process creation: heuristics vs. mathematical programming. Heuristics for reaction and separation operations, heat transfer and pressure change. Introduction to optimization in process engineering and the modeling software GAMS. Process economic evaluation: equipment sizing and costing, time value of money, cash flow calculations. Process environmental evaluation: Life Cycle Assessment (LCA). Process integration: sequencing of distillation columns using mixed-integer linear programming (MILP), and synthesis of heat exchanger networks using mixed-integer nonlinear programming (MINLP). Batch processes: scheduling, sizing, and inventories. Principles of molecular design using mixed-integer programming. | ||||
| Skript | no script | ||||
| Literatur | Main books 1. Biegler, L.T., Grossmann, I.E., Westerberg, A.W. Systematic methods of chemical process design, Prentice Hall International PTR (1997). 2. Douglas, J.M. Conceptual design of chemical processes, McGraw-Hill (1988). 3. Seider, W.D., Seader, J.D., Lwin, D.R., Widagdo, S. Product and process design principles: synthesis, analysis, and evaluation, John Wiley & Sons, Inc. (2010). 4. Sinnot, R.K., Towler, G. Chemical Engineering Design, Butterworth-Heinemann (2009). 5. Smith, R. Chemical process design and integration, Wiley (2005). Other references 6. Edgar, T. F., Himmelblau, D. M. Optimization of chemical process, Mcgraw Hill Chemical Engineering Series (2001). 7. Haydary, J. Chemical Process Design and Simulation, Wiley (2019). 8. Turton, R., Shaeiwitz, A., Bhattacharyya, D., Whiting, W. Synthesis and Design of Chemical Processes, Prentice Hall (2013). 9. Klöpffer, W., Grahl, B. Life Cycle Assessment (LCA): A Guide to Best Practice, Wiley (2014). | ||||
| Voraussetzungen / Besonderes | Prerequisite: Basic knowledge on unit operations, mainly reaction engineering and distillation. It is recommended that the student takes the module "Process Simulation and Flowsheeting" before "Process Design and Development", but it is not mandatory. | ||||