Search result: Catalogue data in Autumn Semester 2023
Computational Science and Engineering Bachelor  | ||||||||||||||||||||||||||||||||||||||||||
 First Year Compulsory Courses | ||||||||||||||||||||||||||||||||||||||||||
| First Year Examination Block 1 | ||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 401-0151-00L | Linear Algebra  | O | 5 credits | 3V + 2U | M. Auer, V. C. Gradinaru | |||||||||||||||||||||||||||||||||||||
| Abstract | Contents: Linear systems - the Gaussian algorithm, matrices - LU decomposition, determinants, vector spaces, least squares - QR decomposition, linear maps, eigenvalue problem, normal forms - singular value decomposition; numerical aspects. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | Einführung in die Lineare Algebra für Ingenieure unter Berücksichtigung numerischer Aspekte | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | eigenes Aufschrieb und K. Nipp / D. Stoffer, Lineare Algebra, vdf Hochschulverlag, 5. Auflage 2002 | |||||||||||||||||||||||||||||||||||||||||
| Literature | K. Nipp / D. Stoffer, Lineare Algebra, vdf Hochschulverlag, 5. Auflage 2002 | |||||||||||||||||||||||||||||||||||||||||
| Competencies |
| |||||||||||||||||||||||||||||||||||||||||
| 252-0025-01L | Discrete Mathematics | O | 7 credits | 4V + 2U | U. Maurer | |||||||||||||||||||||||||||||||||||||
| Abstract | Content: Mathematical reasoning and proofs, abstraction. Sets, relations (e.g. equivalence and order relations), functions, (un-)countability, number theory, algebra (groups, rings, fields, polynomials, subalgebras, morphisms), logic (propositional and predicate logic, proof calculi). | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | The primary goals of this course are (1) to introduce the most important concepts of discrete mathematics, (2) to understand and appreciate the role of abstraction and mathematical proofs, and (3) to discuss a number of applications, e.g. in cryptography, coding theory, and algorithm theory. | |||||||||||||||||||||||||||||||||||||||||
| Content | See course description. | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | available (in english) | |||||||||||||||||||||||||||||||||||||||||
| Competencies |
| |||||||||||||||||||||||||||||||||||||||||
| 252-0856-00L | Computer Science | O | 6 credits | 2V + 2U + 2P | F. Friedrich Wicker, R. Sasse | |||||||||||||||||||||||||||||||||||||
| Abstract | The course covers the fundamental concepts of computer programming with a focus on systematic algorithmic problem solving. Taught language is C++. No programming experience is required. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | Primary educational objective is to learn programming with C++. After having successfully attended the course, students have a good command of the mechanisms to construct a program. They know the fundamental control and data structures and understand how an algorithmic problem is mapped to a computer program. They have an idea of what happens "behind the scenes" when a program is translated and executed. Secondary goals are an algorithmic computational thinking, understanding the possibilities and limits of programming and to impart the way of thinking like a computer scientist. | |||||||||||||||||||||||||||||||||||||||||
| Content | The course covers fundamental data types, expressions and statements, (limits of) computer arithmetic, control statements, functions, arrays, structural types and pointers. The part on object orientation deals with classes, inheritance and polymorphism; simple dynamic data types are introduced as examples. In general, the concepts provided in the course are motivated and illustrated with algorithms and applications. | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture slides and all other material will be made available for download on the course web page. | |||||||||||||||||||||||||||||||||||||||||
| Literature | Bjarne Stroustrup: Einführung in die Programmierung mit C++, Pearson Studium, 2010 Stephen Prata, C++ Primer Plus, Sixth Edition, Addison Wesley, 2012 Andrew Koenig and Barbara E. Moo: Accelerated C++, Addison-Wesley, 2000 | |||||||||||||||||||||||||||||||||||||||||
| Competencies |
| |||||||||||||||||||||||||||||||||||||||||
| First Year Examination Block 2 | ||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
| 401-0231-10L | Analysis 1 Students in BSc EEIT may instead register for 401-1261-07L Analysis I: One Variable (for BSc Mathematics, BSc Physics and BSc Interdisciplinary Science (Phys Chem)) and take the performance assessment of the corresponding two-semester course. Students in BSc EEIT who wish to register for 401-1261-07L/401-1262-07L Analysis I: One Variable/Analysis II: Several Variables instead of 401-0231-10L/401-0232-10L Analysis 1/Analysis 2 must get in touch with the Study Administration before the registration. | O | 8 credits | 4V + 3U | T. Rivière | |||||||||||||||||||||||||||||||||||||
| Abstract | Reelle und komplexe Zahlen, Grenzwerte, Folgen, Reihen, Potenzreihen, stetige Abbildungen, Differential- und Integralrechnung einer Variablen, Einführung in gewöhnliche Differentialgleichungen | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | Einführung in die Grundlagen der Analysis | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Christian Blatter: Ingenieur-Analysis (Kapitel 1-4) | |||||||||||||||||||||||||||||||||||||||||
| Literature | Konrad Koenigsberger, Analysis I. Christian Blatter, Analysis I. | |||||||||||||||||||||||||||||||||||||||||
| 402-0043-00L | Physics I | O | 4 credits | 3V + 1U | T. Esslinger | |||||||||||||||||||||||||||||||||||||
| Abstract | Introduction to the concepts and tools in physics with the help of demonstration experiments: mechanics of point-like and ridged bodies, periodic motion and mechanical waves. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | The concepts and tools in physics, as well as the methods of an experimental science are taught. The student should learn to identify, communicate and solve physical problems in his/her own field of science. | |||||||||||||||||||||||||||||||||||||||||
| Content | Mechanics (motion, Newton's laws, work and energy, conservation of momentum, rotation, gravitation, fluids) Periodic Motion and Waves (periodic motion, mechanical waves, acoustics). | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The lecture follows the book "Physics" by Paul A. Tipler. | |||||||||||||||||||||||||||||||||||||||||
| Literature | Paul A. Tipler and Gene P. Mosca, Physics (for Scientists and Engineers), W. H. Freeman and Company | |||||||||||||||||||||||||||||||||||||||||
| Competencies |
| |||||||||||||||||||||||||||||||||||||||||
| Basic Courses | ||||||||||||||||||||||||||||||||||||||||||
| Block G1 | ||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
| 401-0353-00L | Analysis 3 | O | 4 credits | 2V + 2U | M. Iacobelli | |||||||||||||||||||||||||||||||||||||
| Abstract | In this lecture we treat problems in applied analysis. The focus lies on the solution of quasilinear first order PDEs with the method of characteristics, and on the study of three fundamental types of partial differential equations of second order: the Laplace equation, the heat equation, and the wave equation. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | The aim of this class is to provide students with a general overview of first and second order PDEs, and teach them how to solve some of these equations using characteristics and/or separation of variables. | |||||||||||||||||||||||||||||||||||||||||
| Content | 1.) General introduction to PDEs and their classification (linear, quasilinear, semilinear, nonlinear / elliptic, parabolic, hyperbolic) 2.) Quasilinear first order PDEs - Solution with the method of characteristics - COnservation laws 3.) Hyperbolic PDEs - wave equation - d'Alembert formula in (1+1)-dimensions - method of separation of variables 4.) Parabolic PDEs - heat equation - maximum principle - method of separation of variables 5.) Elliptic PDEs - Laplace equation - maximum principle - method of separation of variables - variational method | |||||||||||||||||||||||||||||||||||||||||
| Literature | Y. Pinchover, J. Rubinstein, "An Introduction to Partial Differential Equations", Cambridge University Press (12. Mai 2005) | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Prerequisites: Analysis I and II, Fourier series (Complex Analysis) | |||||||||||||||||||||||||||||||||||||||||
| 401-0647-00L | Introduction to Mathematical Optimization | O | 5 credits | 2V + 1U | D. Adjiashvili | |||||||||||||||||||||||||||||||||||||
| Abstract | Introduction to basic techniques and problems in mathematical optimization, and their applications to a variety of problems in engineering. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | The goal of the course is to obtain a good understanding of some of the most fundamental mathematical optimization techniques used to solve linear programs and basic combinatorial optimization problems. The students will also practice applying the learned models to problems in engineering. | |||||||||||||||||||||||||||||||||||||||||
| Content | Topics covered in this course include: - Linear programming (simplex method, duality theory, shadow prices, ...). - Basic combinatorial optimization problems (spanning trees, shortest paths, network flows, ...). - Modelling with mathematical optimization: applications of mathematical programming in engineering. | |||||||||||||||||||||||||||||||||||||||||
| Literature | Information about relevant literature will be given in the lecture. | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course is meant for students who did not already attend the course "Mathematical Optimization", which is a more advance lecture covering similar topics. Compared to "Mathematical Optimization", this course has a stronger focus on modeling and applications. | |||||||||||||||||||||||||||||||||||||||||
| 401-2673-00L | Numerical Methods for CSE | O | 9 credits | 2V + 2U + 4P | V. C. Gradinaru | |||||||||||||||||||||||||||||||||||||
| Abstract | The course gives an introduction into fundamental techniques and algorithms of numerical mathematics which play a central role in numerical simulations in science and technology. The course focuses on fundamental ideas and algorithmic aspects of numerical methods. The exercises involve actual implementation of numerical methods in C++. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | * Knowledge of the fundamental algorithms in numerical mathematics * Knowledge of the essential terms in numerical mathematics and the techniques used for the analysis of numerical algorithms * Ability to choose the appropriate numerical method for concrete problems * Ability to interpret numerical results * Ability to implement numerical algorithms afficiently | |||||||||||||||||||||||||||||||||||||||||
| Content | * Computing with Matrices and Vectors * Direct Methods for linear systems of equations * Least Squares Techniques * Data Interpolation and Fitting * Iterative Methods for non-linear systems of equations * Filtering Algorithms * Approximation of Functions * Numerical Quadrature | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture materials (PDF documents and codes) will be made available to the participants through the course web page, whose address will be announced in the beginning of the course. | |||||||||||||||||||||||||||||||||||||||||
| Literature | U. ASCHER AND C. GREIF, A First Course in Numerical Methods, SIAM, Philadelphia, 2011. A. QUARTERONI, R. SACCO, AND F. SALERI, Numerical mathematics, vol. 37 of Texts in Applied Mathematics, Springer, New York, 2000. W. Dahmen, A. Reusken "Numerik für Ingenieure und Naturwissenschaftler", Springer 2006. W. Gander, M.J. Gander, and F. Kwok "Scientific Computing", Springer 2014. M. Hanke-Bourgeois "Grundlagen der Numerischen Mathematik und des wissenschaftlichen Rechnens", BG Teubner, 2002 P. Deuflhard and A. Hohmann, "Numerische Mathematik I", DeGruyter, 2002 | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The course will be accompanied by programming exercises in C++ relying on the template library EIGEN. Knowledge of C++ is taken for granted. | |||||||||||||||||||||||||||||||||||||||||
| Competencies |
| |||||||||||||||||||||||||||||||||||||||||
| Block G2 | ||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
| 401-2813-00L | Programming Techniques for Scientific Simulations I Students in the Master's Degree Programme in Computational Science and Engineering must enrol only if this course unit is an additional requirement. | O | 5 credits | 4G | R. Käppeli | |||||||||||||||||||||||||||||||||||||
| Abstract | This lecture provides an overview of programming techniques for scientific simulations. The focus is on basic and advanced C++ programming techniques and scientific software libraries. Based on an overview over the hardware components of PCs and supercomputer, optimization methods for scientific simulation codes are explained. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | The goal of the course is that students learn basic and advanced programming techniques and scientific software libraries as used and applied for scientific simulations. | |||||||||||||||||||||||||||||||||||||||||
| 252-0061-00L | Systems Programming and Computer Architecture | O | 7 credits | 4V + 2U | T. Roscoe, A. Klimovic | |||||||||||||||||||||||||||||||||||||
| Abstract | Introduction to systems programming. C and assembly language, floating point arithmetic, basic translation of C into assembler, compiler optimizations, manual optimizations. How hardware features like superscalar architecture, exceptions and interrupts, caches, virtual memory, multicore processors, devices, and memory systems function and affect correctness, performance, and optimization. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | The course objectives are for students to: 1. Develop a deep understanding of, and intuition about, the execution of all the layers (compiler, runtime, OS, etc.) between programs in high-level languages and the underlying hardware: the impact of compiler decisions, the role of the operating system, the effects of hardware on code performance and scalability, etc. 2. Be able to write correct, efficient programs on modern hardware, not only in C but high-level languages as well. 3. Understand Systems Programming as a complement to other disciplines within Computer Science and other forms of software development. This course does not cover how to design or build a processor or computer. | |||||||||||||||||||||||||||||||||||||||||
| Content | This course provides an overview of "computers" as a platform for the execution of (compiled) computer programs. This course provides a programmer's view of how computer systems execute programs, store information, and communicate. The course introduces the major computer architecture structures that have direct influence on the execution of programs (processors with registers, caches, other levels of the memory hierarchy, supervisor/kernel mode, and I/O structures) and covers implementation and representation issues only to the extend that they are necessary to understand the structure and operation of a computer system. The course attempts to expose students to the practical issues that affect performance, portability, security, robustness, and extensibility. This course provides a foundation for subsequent courses on operating systems, networks, compilers and many other courses that require an understanding of the system-level issues. Topics covered include: machine-level code and its generation by optimizing compilers, address translation, input and output, trap/event handlers, performance evaluation and optimization (with a focus on the practical aspects of data collection and analysis). | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | - C programmnig - Integers - Pointers and dynamic memory allocation - Basic computer architecture - Compiling C control flow and data structures - Code vulnerabilities - Implementing memory allocation - Linking - Floating point - Optimizing compilers - Architecture and optimization - Caches - Exceptions - Virtual memory - Multicore - Devices | |||||||||||||||||||||||||||||||||||||||||
| Literature | The course is based in part on "Computer Systems: A Programmer's Perspective" (3rd Edition) by R. Bryant and D. O'Hallaron, with additional material. | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | 252-0029-00L Parallel Programming 252-0028-00L Design of Digital Circuits | |||||||||||||||||||||||||||||||||||||||||
| Block G3 All course units within Block G3 are offered in the spring semester. | ||||||||||||||||||||||||||||||||||||||||||
| Block G4 All course units within Block G4 are offered in the spring semester. | ||||||||||||||||||||||||||||||||||||||||||
| Core Courses | ||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
| 252-0232-00L | Software Engineering | W | 6 credits | 2V + 2U | F. Friedrich Wicker, M. Schwerhoff, H. Lehner | |||||||||||||||||||||||||||||||||||||
| Abstract | This course introduces both theoretical and applied aspects of software engineering. It covers: - Software Architecture - Informal and formal Modeling - Design Patterns - Software Engineering Principles - Code Refactoring - Program Testing | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | The course has two main objectives: - Obtain an end-to-end (both, theoretical and practical) understanding of the core techniques used for building quality software. - Be able to apply these techniques in practice. | |||||||||||||||||||||||||||||||||||||||||
| Content | While the lecture will provide the theoretical foundations for the various aspects of software engineering, the students will apply those techniques in project work that will span over the whole semester - involving all aspects of software engineering, from understanding requirements over design and implementation to deployment and change requests. | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | no lecture notes | |||||||||||||||||||||||||||||||||||||||||
| Literature | Will be announced in the lecture | |||||||||||||||||||||||||||||||||||||||||
| Competencies |
| |||||||||||||||||||||||||||||||||||||||||
| 263-2800-00L | Design of Parallel and High-Performance Computing | W | 9 credits | 2V + 2U + 4A | T. Hoefler | |||||||||||||||||||||||||||||||||||||
| Abstract | Advanced topics in parallel and high-performance computing. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | Understand concurrency paradigms and models from a higher perspective and acquire skills for designing, structuring and developing possibly large parallel high-performance software systems. Become able to distinguish parallelism in problem space and in machine space. Become familiar with important technical concepts and with concurrency folklore. | |||||||||||||||||||||||||||||||||||||||||
| Content | We will cover all aspects of high-performance computing ranging from architecture through programming up to algorithms. We will start with a discussion of caches and cache coherence in practical computer systems. We will dive into parallel programming concepts such as memory models, locks, and lock-free. We will cover performance modeling and parallel design principles as well as basic parallel algorithms. | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This class is intended for the Computer Science Masters curriculum. Students must have basic knowledge in programming in C as well as computer science theory. Students should be familiar with the material covered in the ETH computer science first-year courses "Parallele Programmierung (parallel programming)" and "Algorithmen und Datenstrukturen (algorithm and data structures)" or equivalent courses. | |||||||||||||||||||||||||||||||||||||||||
| Fields of Specialization | ||||||||||||||||||||||||||||||||||||||||||
| Astrophysics | ||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
| 401-7851-00L | Theoretical Astrophysics (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH as an incoming student. UZH Module Code: AST512 Mind the enrolment deadlines at UZH: https://www.uzh.ch/cmsssl/en/studies/application/deadlines.html | W | 10 credits | 4V + 2U | University lecturers | |||||||||||||||||||||||||||||||||||||
| Abstract | This course covers the foundations of astrophysical fluid dynamics, the Boltzmann equation, equilibrium systems and their stability, the structure of stars, astrophysical turbulence, accretion disks and their stability, the foundations of radiative transfer, collisionless systems, the structure and stability of dark matter halos and stellar galactic disks. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | ||||||||||||||||||||||||||||||||||||||||||
| Content | This course covers the foundations of astrophysical fluid dynamics, the theory of collisions and the Boltzmann equation, the notion of equilibrium systems and their stability, the structure of stars, the theory of astrophysical turbulence, the theory of accretion disks and their stability, the foundations of astrophysical radiative transfer, the theory of collisionless system, the structure and stability of dark matter halos and stellar galactic disks. | |||||||||||||||||||||||||||||||||||||||||
| Literature | Course Materials: 1- The Physics of Astrophysics, Volume 1: Radiation by Frank H. Shu 2- The Physics of Astrophysics, Volume 2: Gas Dynamics by Frank H. Shu 3- Foundations of radiation hydrodynamics, Dimitri Mihalas and Barbara Weibel-Mihalas 4- Radiative Processes in Astrophysics, George B. Rybicki and Alan P. Lightman 5- Galactic Dynamics, James Binney and Scott Tremaine | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This is a full black board ad chalk experience for students with a strong background in mathematics and physics. Prerequisites: Introduction to Astrophysics Mathematical Methods for the Physicist Quantum Mechanics (All preferred but not obligatory) Prior Knowledge: Mechanics Quantum Mechanics and atomic physics Thermodynamics Fluid Dynamics Electrodynamics | |||||||||||||||||||||||||||||||||||||||||
| 401-7855-00L | Computational Astrophysics (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH as an incoming student. UZH Module Code: AST245 Mind the enrolment deadlines at UZH: https://www.uzh.ch/cmsssl/en/studies/application/deadlines.html | W | 6 credits | 2V | L. M. Mayer | |||||||||||||||||||||||||||||||||||||
| Abstract | ||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Acquire knowledge of main methodologies for computer-based models of astrophysical systems,the physical equations behind them, and train such knowledge with simple examples of computer programmes | |||||||||||||||||||||||||||||||||||||||||
| Content | 1. Integration of ODE, Hamiltonians and Symplectic integration techniques, time adaptivity, time reversibility 2. Large-N gravity calculation, collisionless N-body systems and their simulation 3. Fast Fourier Transform and spectral methods in general 4. Eulerian Hydrodynamics: Upwinding, Riemann solvers, Limiters 5. Lagrangian Hydrodynamics: The SPH method 6. Resolution and instabilities in Hydrodynamics 7. Initial Conditions: Cosmological Simulations and Astrophysical Disks 8. Physical Approximations and Methods for Radiative Transfer in Astrophysics | |||||||||||||||||||||||||||||||||||||||||
| Literature | Galactic Dynamics (Binney & Tremaine, Princeton University Press), Computer Simulation using Particles (Hockney & Eastwood CRC press), Targeted journal reviews on computational methods for astrophysical fluids (SPH, AMR, moving mesh) | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Some knowledge of UNIX, scripting languages (see www.physik.uzh.ch/lectures/informatik/python/ as an example), some prior experience programming, knowledge of C, C++ beneficial | |||||||||||||||||||||||||||||||||||||||||
| Physics of the Atmosphere | ||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
| 701-0023-00L | Atmosphere | W | 3 credits | 2V | E. Fischer, T. Peter | |||||||||||||||||||||||||||||||||||||
| Abstract | Basic principles of the atmosphere, physical structure and chemical composition, trace gases, atmospheric cycles, circulation, stability, radiation, condensation, clouds, oxidation capacity and ozone layer. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | Understanding of basic physical and chemical processes in the atmosphere. Understanding of mechanisms of and interactions between: weather - climate, atmosphere - ocean - continents, troposhere - stratosphere. Understanding of environmentally relevant structures and processes on vastly differing scales. Basis for the modelling of complex interrelations in the atmospehre. | |||||||||||||||||||||||||||||||||||||||||
| Content | Basic principles of the atmosphere, physical structure and chemical composition, trace gases, atmospheric cycles, circulation, stability, radiation, condensation, clouds, oxidation capacity and ozone layer. | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Written information will be supplied. | |||||||||||||||||||||||||||||||||||||||||
| Literature | - John H. Seinfeld and Spyros N. Pandis, Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, Wiley, New York, 1998. - Gösta H. Liljequist, Allgemeine Meteorologie, Vieweg, Braunschweig, 1974. | |||||||||||||||||||||||||||||||||||||||||
| Chemistry | ||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
| 529-0004-01L | Classical Simulation of (Bio)Molecular Systems | W | 6 credits | 4G | P. H. Hünenberger, J. Dolenc, S. Riniker | |||||||||||||||||||||||||||||||||||||
| Abstract | Molecular models, classical force fields, configuration sampling, molecular dynamics simulation, boundary conditions, electrostatic interactions, analysis of trajectories, free-energy calculations, structure refinement, applications in chemistry and biology. Exercises: hands-on computer exercises for learning progressively how to perform an analyze classical simulations (using the package GROMOS). | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | Introduction to classical (atomistic) computer simulation of (bio)molecular systems, development of skills to carry out and interpret these simulations. | |||||||||||||||||||||||||||||||||||||||||
| Content | Molecular models, classical force fields, configuration sampling, molecular dynamics simulation, boundary conditions, electrostatic interactions, analysis of trajectories, free-energy calculations, structure refinement, applications in chemistry and biology. Exercises: hands-on computer exercises for learning progressively how to perform an analyze classical simulations (using the package GROMOS). | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The powerpoint slides of the lectures will be made available weekly on the website in pdf format (on the day preceding each lecture). | |||||||||||||||||||||||||||||||||||||||||
| Literature | See: www.csms.ethz.ch/education/CSBMS | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Since the exercises on the computer do convey and test essentially different skills than those being conveyed during the lectures and tested at the oral exam, the results of the exercises are taken into account when evaluating the results of the exam (learning component, possible bonus of up to 0.25 points on the exam mark). For more information about the lecture: www.csms.ethz.ch/education/CSBMS | |||||||||||||||||||||||||||||||||||||||||
| Competencies |
| |||||||||||||||||||||||||||||||||||||||||
| Fluid Dynamics | ||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
| 151-0103-00L | Fluid Dynamics II | W | 3 credits | 2V + 1U | P. Jenny | |||||||||||||||||||||||||||||||||||||
| Abstract | Two-dimensional irrotational (potential) flows: stream function and potential, singularity method, unsteady flow, aerodynamic concepts. Vorticity dynamics: vorticity and circulation, vorticity equation, vortex theorems of Helmholtz and Kelvin. Compressible flows: isentropic flow along stream tube, normal and oblique shocks, Laval nozzle, Prandtl-Meyer expansion, viscous effects. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | Expand basic knowledge of fluid dynamics. Concepts, phenomena and quantitative description of irrotational (potential), rotational, and one-dimensional compressible flows. | |||||||||||||||||||||||||||||||||||||||||
| Content | Two-dimensional irrotational (potential) flows: stream function and potential, complex notation, singularity method, unsteady flow, aerodynamic concepts. Vorticity dynamics: vorticity and circulation, vorticity equation, vortex theorems of Helmholtz and Kelvin. Compressible flows: isentropic flow along stream tube, normal and oblique shocks, Laval nozzle, Prandtl-Meyer expansion, viscous effects. | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture notes are available (in German). (See also info on literature below.) | |||||||||||||||||||||||||||||||||||||||||
| Literature | Relevant chapters (corresponding to lecture notes) from the textbook P.K. Kundu, I.M. Cohen, D.R. Dowling: Fluid Mechanics, Academic Press, 5th ed., 2011 (includes a free copy of the DVD "Multimedia Fluid Mechanics") P.K. Kundu, I.M. Cohen, D.R. Dowling: Fluid Mechanics, Academic Press, 6th ed., 2015 (does NOT include a free copy of the DVD "Multimedia Fluid Mechanics") | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Analysis I/II, Knowledge of Fluid Dynamics I, thermodynamics of ideal gas | |||||||||||||||||||||||||||||||||||||||||
| 151-0709-00L | Stochastic Methods for Engineers and Natural Scientists | W | 4 credits | 4G | D. W. Meyer-Massetti | |||||||||||||||||||||||||||||||||||||
| Abstract | The course provides an introduction into stochastic methods that are applicable for example for the description and modeling of turbulent and subsurface flows. Moreover, mathematical techniques are presented that are used to quantify uncertainty in various engineering applications. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | By the end of the course you should be able to mathematically describe random quantities and their effect on physical systems. Moreover, you should be able to develop basic stochastic models of such systems. | |||||||||||||||||||||||||||||||||||||||||
| Content | - Probability theory, single and multiple random variables, mappings of random variables - Estimation of statistical moments and probability densities based on data - Stochastic differential equations, Ito calculus, PDF evolution equations - Monte Carlo integration with importance and stratified sampling - Markov-chain Monte Carlo sampling - Control-variate and multi-level Monte Carlo estimation - Statistical tests for means and goodness-of-fit All topics are illustrated with engineering applications. | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Detailed lecture notes will be provided. | |||||||||||||||||||||||||||||||||||||||||
| Literature | Some textbooks related to the material covered in the course: Stochastic Methods: A Handbook for the Natural and Social Sciences, Crispin Gardiner, Springer, 2010 The Fokker-Planck Equation: Methods of Solutions and Applications, Hannes Risken, Springer, 1996 Turbulent Flows, S.B. Pope, Cambridge University Press, 2000 Spectral Methods for Uncertainty Quantification, O.P. Le Maitre and O.M. Knio, Springer, 2010 | |||||||||||||||||||||||||||||||||||||||||
| Competencies |
| |||||||||||||||||||||||||||||||||||||||||
| 151-0125-00L | Hydrodynamics and Cavitation Does not take place this semester. | W | 4 credits | 3G | O. Supponen | |||||||||||||||||||||||||||||||||||||
| Abstract | This course builds on the foundations of fluid dynamics to describe hydrodynamic flows and provides an introduction to cavitation. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | The main learning objectives of this course are: 1. Identify and describe dominant effects in liquid fluid flows through physical modelling. 2. Identify hydrodynamic instabilities and discuss the stability region 3. Describe fragmentation of liquids 4. Explain tension, nucleation and phase-change in liquids. 5. Describe hydrodynamic cavitation and its consequences in physical terms. 6. Recognise experimental techniques and industrial and medical applications for cavitation. | |||||||||||||||||||||||||||||||||||||||||
| Content | The course gives an overview on the following topics: hydrostatics, capillarity, hydrodynamic instabilities, fragmentation. Tension in liquids, phase change. Cavitation: single bubbles (nucleation, dynamics, collapse), cavitating flows (attached, cloud, vortex cavitation). Industrial applications and measurement techniques. | |||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Class notes and handouts | |||||||||||||||||||||||||||||||||||||||||
| Literature | Literature will be provided in the course material. | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Fluid dynamics I & II or equivalent | |||||||||||||||||||||||||||||||||||||||||
| Systems and Control | ||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
| 227-0103-00L | Control Systems | W | 6 credits | 2V + 2U | F. Dörfler | |||||||||||||||||||||||||||||||||||||
| Abstract | Study of concepts and methods for the mathematical description and analysis of dynamical systems. The concept of feedback. Design of control systems for single input - single output and multivariable systems. | |||||||||||||||||||||||||||||||||||||||||
| Learning objective | Study of concepts and methods for the mathematical description and analysis of dynamical systems. The concept of feedback. Design of control systems for single input - single output and multivariable systems. | |||||||||||||||||||||||||||||||||||||||||
| Content | Process automation, concept of control. Modelling of dynamical systems - examples, state space description, linearisation, analytical/numerical solution. Laplace transform, system response for first and second order systems - effect of additional poles and zeros. Closed-loop control - idea of feedback. PID control, Ziegler - Nichols tuning. Stability, Routh-Hurwitz criterion, root locus, frequency response, Bode diagram, Bode gain/phase relationship, controller design via "loop shaping", Nyquist criterion. Feedforward compensation, cascade control. Multivariable systems (transfer matrix, state space representation), multi-loop control, problem of coupling, Relative Gain Array, decoupling, sensitivity to model uncertainty. State space representation (modal description, controllability, control canonical form, observer canonical form), state feedback, pole placement - choice of poles. Observer, observability, duality, separation principle. LQ Regulator, optimal state estimation. | |||||||||||||||||||||||||||||||||||||||||
| Literature | K. J. Aström & R. Murray. Feedback Systems: An Introduction for Scientists and Engineers. Princeton University Press, 2010. R. C. Dorf and R. H. Bishop. Modern Control Systems. Prentice Hall, New Jersey, 2007. G. F. Franklin, J. D. Powell, and A. Emami-Naeini. Feedback Control of Dynamic Systems. Addison-Wesley, 2010. J. Lunze. Regelungstechnik 1. Springer, Berlin, 2014. J. Lunze. Regelungstechnik 2. Springer, Berlin, 2014. | |||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Prerequisites: Signal and Systems Theory II. MATLAB is used for system analysis and simulation. | |||||||||||||||||||||||||||||||||||||||||
Page
1
of
4
All