Search result: Catalogue data in Autumn Semester 2020
|Mechanical Engineering Master|
| Energy, Flows and Processes|
The courses listed in this category “Core Courses” are recommended. Alternative courses can be chosen in agreement with the tutor.
|151-0951-00L||Process Design and Safety||W||4 credits||2V + 1U||F. Trachsel, C. Hutter|
|Abstract||The lecture Process Design and Saftey deals with the fundamentals of project management, scale-up, dimensioning and safety of chemical process equipment and plants.|
|Objective||The objective of the lecture is to expound the engineering design approach of important elements in chemical plant design.|
|Content||Fundamentals in Chemical engineering Design; |
Materials and Corrosion,
Piping and Armatures,
Reactors and Scale-up,
Safety of chemical processes,
|Lecture notes||The lecture slides will be distributed.|
|Literature||Coulson and Richardson's: Chemical Engineering , Vol 6: Chemical Engineering Design, (1996)|
|Prerequisites / Notice||A 1-day excursion including a visit of a chemical plant will be part of the lecture.|
|151-1116-00L||Introduction to Aircraft and Car Aerodynamics||W||4 credits||3G||J. Wildi|
|Abstract||Aircraft aerodynamics: Atmosphere; aerodynamic forces (lift, drag); thrust.|
Vehicle aerodynamics: Aerodynamic and mass forces, drag, lift, car aerodynamics and performence. Passenger cars, trucks, racing cars.
|Objective||An introduction to the basic principles and interrelationships of aircraft and automotive aerodynamics.|
To understand the basic relations of the origin of aerodynamic forces (ie lift, drag). To quantify the aerodynamic forces for basic configurations of aercraft and car components.
Illustration of the intrinsic problems and results using examples.
Using experimental and theoretical methods to illustrate possibilities and limits.
|Content||Aircraft aerodynamics: atmosphere, aerodynamic forces (ascending force: profile, wings. Resistance, residual resistance, induced resistance); thrust (overview of the propulsion system, aerodynamics of the propellers), introduction to static longitudinal stability.|
Automobile aerodynamics: Basic principles: aerodynamic force and the force of inertia, resistance, drive, aerodynamic and driving performance. Cars commercial vehicles, racing cars.
|Lecture notes||1.) Grundlagen der Flugtechnik (Basics of flight science, script in german language)|
2.) Einführung in die Fahrzeugaerodynamik (Introduction in car aerodynamics, script in german language)
|Literature||English literature covering the content of the course:|
- Anderson Jr, John D: Introduction to Flight, Mc Graw Hill, Ed 06, 2007; ISBN: 9780073529394
- Mc Cormick, B.W.: Aerodynamics, Aeronautics and Flight Mechanics, John Wiley and Sons, 1979
- Hucho, Wolf-Heinrich: Aerodynamics of Road Vehicles, SAE International, 1998
|101-0187-00L||Structural Reliability and Risk Analysis||W||3 credits||2G||S. Marelli|
|Abstract||Structural reliability aims at quantifying the probability of failure of systems due to uncertainties in their design, manufacturing and environmental conditions. Risk analysis combines this information with the consequences of failure in view of optimal decision making. The course presents the underlying probabilistic modelling and computational methods for reliability and risk assessment.|
|Objective||The goal of this course is to provide the students with a thorough understanding of the key concepts behind structural reliability and risk analysis. After this course the students will have refreshed their knowledge of probability theory and statistics to model uncertainties in view of engineering applications. They will be able to analyze the reliability of a structure and to use risk assessment methods for decision making under uncertain conditions. They will be aware of the state-of-the-art computational methods and software in this field.|
|Content||Engineers are confronted every day to decision making under limited amount of information and uncertain conditions. When designing new structures and systems, the design codes such as SIA or Euro- codes usually provide a framework that guarantees safety and reliability. However the level of safety is not quantified explicitly, which does not allow the analyst to properly choose between design variants and evaluate a total cost in case of failure. In contrast, the framework of risk analysis allows one to incorporate the uncertainty in decision making.|
The first part of the course is a reminder on probability theory that is used as a main tool for reliability and risk analysis. Classical concepts such as random variables and vectors, dependence and correlation are recalled. Basic statistical inference methods used for building a probabilistic model from the available data, e.g. the maximum likelihood method, are presented.
The second part is related to structural reliability analysis, i.e. methods that allow one to compute probabilities of failure of a given system with respect to prescribed criteria. The framework of reliability analysis is first set up. Reliability indices are introduced together with the first order-second moment method (FOSM) and the first order reliability method (FORM). Methods based on Monte Carlo simulation are then reviewed and illustrated through various examples. By-products of reliability analysis such as sensitivity measures and partial safety coefficients are derived and their links to structural design codes is shown. The reliability of structural systems is also introduced as well as the methods used to reassess existing structures based on new information.
The third part of the course addresses risk assessment methods. Techniques for the identification of hazard scenarios and their representation by fault trees and event trees are described. Risk is defined with respect to the concept of expected utility in the framework of decision making. Elements of Bayesian decision making, i.e. pre-, post and pre-post risk assessment methods are presented.
The course also includes a tutorial using the UQLab software dedicated to real world structural reliability analysis.
|Lecture notes||Slides of the lectures are available online every week. A printed version of the full set of slides is proposed to the students at the beginning of the semester.|
|Literature||Ang, A. and Tang, W.H, Probability Concepts in Engineering - Emphasis on Applications to Civil and Environmental Engineering, 2nd Edition, John Wiley & Sons, 2007.|
S. Marelli, R. Schöbi, B. Sudret, UQLab user manual - Structural reliability (rare events estimation), Report UQLab-V0.92-107.
|Prerequisites / Notice||Basic course on probability theory and statistics|
|227-0665-00L||Battery Integration Engineering|
Does not take place this semester.
Priority given to Electrical and Mechanical Engineering students
Students are required to have attended one of the following courses: 227-0664-00L Technology and Policy of Electrical Energy Storage
529-0440-00L Physical Electrochemistry and Electrocatalysis
529-0191-01L Renewable Energy Technologies II, Energy Storage and Conversion
529-0659-00L Electrochemistry (Exception for PhD students).
|W||3 credits||2V + 1U|
|Abstract||Batteries enable sustainable mobility, renewable power integration, various power grid services, and residential energy storage. Linked with low cost PV, Li-ion batteries are positioned to shift the 19th-century centralized power grid into a 21st-century distributed one. As with battery integration, this course combines understanding of electrochemistry, heat & mass transfer, device engineering.|
|Objective||The learning objectives are:|
- Apply critical thinking on advancements in battery integration engineering. Assessment reflects this objective and is based on review of a scientific paper, with mark weighting of 10 / 25 / 65 for a proposal / oral presentation / final report, respectively.
- Design battery system concepts for various applications in the modern power system and sustainable mobility, with a deep focus on replacing diesel buses with electric buses combined with charging infrastructure.
- Critically assess progresses in battery integration engineering: from material science of novel battery technologies to battery system design.
- Apply "lessons learned" from the history of batteries to assess progress in battery technology.
- Apply experimental and physical concepts to develop battery models in order to predict lifetime.
|Content||- Battery systems for the modern power grid and sustainable mobility.|
- Battery lifetime modeling by aging, thermal, and electric sub-models.
- Electrical architecture of battery energy storage systems.
- History and review of electrochemistry & batteries, and metrics to assess future developments in electrochemical energy stroage.
- Sustainability and life cycle analysis of battery system innovations.
|Prerequisites / Notice||Limited to 30 Students. Priority given to Electrical and Mechanical Engineering students. |
Mandatory - background knowledge in batteries & electrochemistry acquired in one of the following courses:
227-0664-00L Technology and Policy of Electrical Energy Storage
529-0440-00L Physical Electrochemistry and Electrocatalysis
529-0191-01L Renewable Energy Technologies II, Energy Storage and Conversion
Exception given for PhD students
|252-0834-00L||Information Systems for Engineers||W||4 credits||2V + 1U||G. Fourny|
|Abstract||This course provides the basics of relational databases from the perspective of the user.|
We will discover why tables are so incredibly powerful to express relations, learn the SQL query language, and how to make the most of it. The course also covers support for data cubes (analytics).
|Objective||This lesson is complementary with Big Data for Engineers as they cover different time periods of database history and practices -- you can take them in any order, even though it might be more enjoyable to take this lecture first.|
After visiting this course, you will be capable to:
1. Explain, in the big picture, how a relational database works and what it can do in your own words.
2. Explain the relational data model (tables, rows, attributes, primary keys, foreign keys), formally and informally, including the relational algebra operators (select, project, rename, all kinds of joins, division, cartesian product, union, intersection, etc).
3. Perform non-trivial reading SQL queries on existing relational databases, as well as insert new data, update and delete existing data.
4. Design new schemas to store data in accordance to the real world's constraints, such as relationship cardinality
5. Explain what bad design is and why it matters.
6. Adapt and improve an existing schema to make it more robust against anomalies, thanks to a very good theoretical knowledge of what is called "normal forms".
7. Understand how indices work (hash indices, B-trees), how they are implemented, and how to use them to make queries faster.
8. Access an existing relational database from a host language such as Java, using bridges such as JDBC.
9. Explain what data independence is all about and didn't age a bit since the 1970s.
10. Explain, in the big picture, how a relational database is physically implemented.
11. Know and deal with the natural syntax for relational data, CSV.
12. Explain the data cube model including slicing and dicing.
13. Store data cubes in a relational database.
14. Map cube queries to SQL.
15. Slice and dice cubes in a UI.
And of course, you will think that tables are the most wonderful object in the world.
|Content||Using a relational database|
2. The relational model
3. Data definition with SQL
4. The relational algebra
5. Queries with SQL
Taking a relational database to the next level
6. Database design theory
7. Databases and host languages
8. Databases and host languages
9. Indices and optimization
10. Database architecture and storage
Analytics on top of a relational database
12. Data cubes
|Literature||- Lecture material (slides).|
- Book: "Database Systems: The Complete Book", H. Garcia-Molina, J.D. Ullman, J. Widom
(It is not required to buy the book, as the library has it)
|Prerequisites / Notice||For non-CS/DS students only, BSc and MSc|
Elementary knowledge of set theory and logics
Knowledge as well as basic experience with a programming language such as Pascal, C, C++, Java, Haskell, Python
|636-0507-00L||Synthetic Biology II |
Does not take place this semester.
Students in the MSc Programme Biotechnology may select Synthetic Biology II instead of the Research Project 1.
|W||8 credits||4A||S. Panke, Y. Benenson, J. Stelling|
|Abstract||7 months biological design project, during which the students are required to give presentations on advanced topics in synthetic biology (specifically genetic circuit design) and then select their own biological system to design. The system is subsequently modeled, analyzed, and experimentally implemented. Results are presented at an international student competition at the MIT (Cambridge).|
|Objective||The students are supposed to acquire a deep understanding of the process of biological design including model representation of a biological system, its thorough analysis, and the subsequent experimental implementation of the system and the related problems.|
|Content||Presentations on advanced synthetic biology topics (eg genetic circuit design, adaptation of systems dynamics, analytical concepts, large scale de novo DNA synthesis), project selection, modeling of selected biological system, design space exploration, sensitivity analysis, conversion into DNA sequence, (DNA synthesis external,) implementation and analysis of design, summary of results in form of scientific presentation and poster, presentation of results at the iGEM international student competition (www.igem.org).|
|Lecture notes||Handouts during course|
|Prerequisites / Notice||The final presentation of the project is typically at the MIT (Cambridge, US). Other competing schools include regularly Imperial College, Cambridge University, Harvard University, UC Berkeley, Princeton Universtiy, CalTech, etc.|
This project takes place between end of Spring Semester and beginning of Autumn Semester. Registration in April.
Please note that the number of ECTS credits and the actual work load are disconnected.
| Mechanics, Materials, Structures|
The courses listed in this category “Core Courses” are recommended. Alternative courses can be chosen in agreement with the tutor.
|151-0107-20L||High Performance Computing for Science and Engineering (HPCSE) I||W||4 credits||4G||P. Koumoutsakos, S. M. Martin|
|Abstract||This course gives an introduction into algorithms and numerical methods for parallel computing on shared and distributed memory architectures. The algorithms and methods are supported with problems that appear frequently in science and engineering.|
|Objective||With manufacturing processes reaching its limits in terms of transistor density on today’s computing architectures, efficient utilization of computing resources must include parallel execution to maintain scaling. The use of computers in academia, industry and society is a fundamental tool for problem solving today while the “think parallel” mind-set of developers is still lagging behind.|
The aim of the course is to introduce the student to the fundamentals of parallel programming using shared and distributed memory programming models. The goal is on learning to apply these techniques with the help of examples frequently found in science and engineering and to deploy them on large scale high performance computing (HPC) architectures.
|Content||1. Hardware and Architecture: Moore’s Law, Instruction set architectures (MIPS, RISC, CISC), Instruction pipelines, Caches, Flynn’s taxonomy, Vector instructions (for Intel x86)|
2. Shared memory parallelism: Threads, Memory models, Cache coherency, Mutual exclusion, Uniform and Non-Uniform memory access, Open Multi-Processing (OpenMP)
3. Distributed memory parallelism: Message Passing Interface (MPI), Point-to-Point and collective communication, Blocking and non-blocking methods, Parallel file I/O, Hybrid programming models
4. Performance and parallel efficiency analysis: Performance analysis of algorithms, Roofline model, Amdahl’s Law, Strong and weak scaling analysis
5. Applications: HPC Math libraries, Linear Algebra and matrix/vector operations, Singular value decomposition, Neural Networks and linear autoencoders, Solving partial differential equations (PDEs) using grid-based and particle methods
Class notes, handouts
|Literature||• An Introduction to Parallel Programming, P. Pacheco, Morgan Kaufmann|
• Introduction to High Performance Computing for Scientists and Engineers, G. Hager and G. Wellein, CRC Press
• Computer Organization and Design, D.H. Patterson and J.L. Hennessy, Morgan Kaufmann
• Vortex Methods, G.H. Cottet and P. Koumoutsakos, Cambridge University Press
• Lecture notes
|Prerequisites / Notice||Students should be familiar with a compiled programming language (C, C++ or Fortran). Exercises and exams will be designed using C++. The course will not teach basics of programming. Some familiarity using the command line is assumed. Students should also have a basic understanding of diffusion and advection processes, as well as their underlying partial differential equations.|
|151-0215-00L||Engineering Acoustics I||W||4 credits||3G||N. Noiray, B. Van Damme|
|Abstract||This course provides an introduction to acoustics. It focusses on fundamental phenomena of airborne and structure-borne sound waves. The lecture combines theoretical principles with practical insights and interpretations.|
|Objective||This course is proposed for Master and PhD students interested in getting knowledge in acoustics. Students will be able to understand, describe analytically and interpret sound generation, absorption and propagation.|
|Content||First, magnitudes characterizing sound propagation are reviewed and the constitutive equations for acoustics are derived. Then the different types of sources (monopole/dipole/quadrupole, punctual, non-compact) are introduced and linked to the noise generated by turbulent flows, coherent vortical structures or fluctuating heat release. The scattering of sound by rigid bodies is given in basic configurations. Analytical, experimental and numerical methods used to analyze sound in ducts and rooms are presented (Green functions, Galerkin expansions, Helmholtz solvers).|
The second part covers elastic wave phenomena, such as dispersion and vibration modes, in infinite and finite structures.
|Lecture notes||Handouts will be distributed during the class|
|Literature||Books will be recommended for each chapter|
|151-0317-00L||Visualization, Simulation and Interaction - Virtual Reality II||W||4 credits||3G||A. Kunz|
|Abstract||This lecture provides deeper knowledge on the possible applications of virtual reality, its basic technolgy, and future research fields. The goal is to provide a strong knowledge on Virtual Reality for a possible future use in business processes.|
|Objective||Virtual Reality can not only be used for the visualization of 3D objects, but also offers a wide application field for small and medium enterprises (SME). This could be for instance an enabling technolgy for net-based collaboration, the transmission of images and other data, the interaction of the human user with the digital environment, or the use of augmented reality systems.|
The goal of the lecture is to provide a deeper knowledge of today's VR environments that are used in business processes. The technical background, the algorithms, and the applied methods are explained more in detail. Finally, future tasks of VR will be discussed and an outlook on ongoing international research is given.
|Content||Introduction into Virtual Reality; basisc of augmented reality; interaction with digital data, tangible user interfaces (TUI); basics of simulation; compression procedures of image-, audio-, and video signals; new materials for force feedback devices; intorduction into data security; cryptography; definition of free-form surfaces; digital factory; new research fields of virtual reality|
|Lecture notes||The handout is available in German and English.|
|Prerequisites / Notice||Prerequisites:|
"Visualization, Simulation and Interaction - Virtual Reality I" is recommended, but not mandatory.
The course consists of lectures and exercises.
|151-0353-00L||Mechanics of Composite Materials |
Number of participants limited to 80.
|W||4 credits||2V + 1U||P. Ermanni|
|Abstract||Focus is on laminated fibre reinfoced polymer composites. The courses treats aspects related to micromechanics, elastic behavior of unidirectional and multidirectional laminates, failure and damage analysis, design and analysis of composite structures.|
|Objective||To introduce the underlying concept of composite materials and give a thorough understanding of the mechanical response of materials and structures made from fibre reinforced polymer composites, including elastic behaviour, fracture and damage analysis as well as structural design aspects. The ultimate goal is to provide the necessary skills to address the design and analysis of modern lightweight composite structures.|
|Content||The course is addressing following topics:|
- Elastic anisotropy
- Micromechanics aspects
- Classical Laminate Theory (CLT)
- Failure hypotheses and damage analysis
- Analysis and design of composite structures
- Draping effects
- Special topics
|Lecture notes||Script, handouts, exercises and additional material are available in PDF-format on the CMASLab webpage resp on moodle.|
|Literature||The lecture material is covered by the script and further literature is referenced in there.|
|151-0368-00L||Aeroelasticity||W||4 credits||2V + 1U||M. Righi|
|Abstract||Introduction to the basics and methods of Aeroelasticity. An overview of the main static and dynamic phenomena arising from the interaction between structural and aerodynamic loads.|
|Objective||The course will provide a basic physical understanding of flow-structure interaction. You will get to know the most important phenomena in the static and dynamic aeroelasticity, as well as a presentation of the most relevant analytical and numerical prediction methods.|
|Content||Introduction to steady and unsteady thin airfoil theory, extension to three dimension wing aerodynamics, strip theory, overview of numerical methods available (panel methods, CFD). |
Introduction to unsteady aerodynamics (theory): Theodorsen and Wagner functions. Unsteady aerodynamics observed from numerical experiments (CFD). Generation of simplified mathematical models.
Presentation of steady aeroelasticity: equations of equilibrium for the typical section, aeroelastic deformation, effectiveness of the aeroelastic system, stability (definition), divergence condition, role played by a control surface, control effectiveness, sweep angle, aeroelastic tailoring of bending-torsion coupling. Ritz model to model beams, use of FEM, modal condensation, choice of generalized coordinates.
Presentation of dynamic aeroelasticity: assessment of dynamic aeroelastic response of simple systems. Flutter kinematics (bending-twisting). Dynamic response of a simplified wing.
Numerical aeroelasticity (Test Cases extracted from the latest AIAA Aeroelastic Prediction Workshops).
Aeroelasticity of modern aircraft: assessment of the effects induced by the control surfaces and control systems (Aeroservoelasticity), active controlled aircraft, flutter-suppression systems, certification (EASA, FAA).
Planning and execution of Wind Tunnel experiments with aeroelastic models. Live-execution of an experiment in the WT of the ETH.
Brief presentation of non-linear phenomena like Limit-Cycle Oscillations (LCO)
|Lecture notes||A script in English language is available.|
|Literature||Bispilnghoff Ashley, Aeroelasticity|
Abbott, Theory of Wing sections,
Y. C. Fung, An Introduction to the Theory of Aeroelasticity, Dover Phoenix Editions.
|151-0509-00L||Microscale Acoustofluidics||W||4 credits||3G||J. Dual|
|Abstract||In this lecture the basics as well as practical aspects (from modelling to design and fabrication ) are described from a solid and fluid mechanics perspective with applications to microsystems and lab on a chip devices.|
|Objective||Understanding acoustophoresis, the design of devices and potential applications|
|Content||Linear and nonlinear acoustics, foundations of fluid and solid mechanics and piezoelectricity, Gorkov potential, numerical modelling, acoustic streaming, applications from ultrasonic microrobotics to surface acoustic wave devices|
|Lecture notes||Yes, incl. Chapters from the Tutorial: Microscale Acoustofluidics, T. Laurell and A. Lenshof, Ed., Royal Society of Chemistry, 2015|
|Literature||Microscale Acoustofluidics, T. Laurell and A. Lenshof, Ed., Royal Society of Chemistry, 2015|
|Prerequisites / Notice||Solid and fluid continuum mechanics. Notice: The exercise part is a mixture of presentation, lab sessions ( both compulsary) and hand in homework.|
|151-0524-00L||Continuum Mechanics I||W||4 credits||2V + 1U||E. Mazza|
|Abstract||The lecture deals with constitutive models that are relevant for design and calculation of structures. These include anisotropic linear elsticity, linear viscoelasticity, plasticity, viscoplasticity. Homogenization theories and laminate theory are presented. Theoretical models are complemented by examples of engineering applications and eperiments.|
|Objective||Basic theories for solving continuum mechanics problems of engineering applications, with particular attention to material models.|
|Content||Anisotrope Elastizität, Linearelastisches und linearviskoses Stoffverhalten, Viskoelastizität, mikro-makro Modellierung, Laminattheorie, Plastizität, Viscoplastizität, Beispiele aus der Ingenieuranwendung, Vergleich mit Experimenten.|
|151-0525-00L||Dynamic Behavior of Materials|
“Note: previous course title until HS19 "Wave Propagation in Solids".
|W||4 credits||2V + 2U||D. Mohr, C. Roth, T. Tancogne-Dejean|
|Abstract||Lectures and computer labs concerned with the modeling of the deformation response and failure of engineering materials (metals, polymers and composites) subject to extreme loadings during manufacturing, crash, impact and blast events.|
|Objective||Students will learn to apply, understand and develop computational models of a large spectrum of engineering materials to predict their dynamic deformation response and failure in finite element simulations. Students will become familiar with important dynamic testing techniques to identify material model parameters from experiments. The ultimate goal is to provide the students with the knowledge and skills required to engineer modern multi-material solutions for high performance structures in automotive, aerospace and naval engineering.|
|Content||Topics include viscoelasticity, temperature and rate dependent plasticity, dynamic brittle and ductile fracture; impulse transfer, impact and wave propagation in solids; computational aspects of material model implementation into hydrocodes; simulation of dynamic failure of structures;|
|Lecture notes||Slides of the lectures, relevant journal papers and user manuals will be provided.|
|Literature||Various books will be recommended pertaining to the topics covered.|
|Prerequisites / Notice||Course in continuum mechanics (mandatory), finite element method (recommended)|
|151-0529-00L||Computational Mechanics II: Nonlinear FEA||W||4 credits||2V + 2U||L. De Lorenzis|
|Abstract||The course provides an introduction to non-linear finite element analysis. The treated sources of non-linearity are related to material properties (e.g. plasticity), kinematics (large deformations, instability problems) and boundary conditions (contact).|
|Objective||To be able to address all major sources of non-linearity in theory and numerics, and to apply this knowledge to the solution of relevant problems in solid mechanics.|
|Content||1. Introduction: various sources of nonlinearities and implications for FEA. |
2. Non-linear kinematics: large deformations, stability problems.
3. Non-linear material behavior: hyperelasticity, plasticity.
4. Non-linear boundary conditions: contact problems.
|Lecture notes||Lecture notes will be provided. However, students are encouraged to take their own notes.|
|Prerequisites / Notice||Mechanics 1, 2, Dynamics, Continuum Mechanics I and Introduction to FEA. Ideally also Continuum Mechanics II.|
|151-0532-00L||Nonlinear Dynamics and Chaos I||W||4 credits||2V + 2U||G. Haller|
|Abstract||Basic facts about nonlinear systems; stability and near-equilibrium dynamics; bifurcations; dynamical systems on the plane; non-autonomous dynamical systems; chaotic dynamics.|
|Objective||This course is intended for Masters and Ph.D. students in engineering sciences, physics and applied mathematics who are interested in the behavior of nonlinear dynamical systems. It offers an introduction to the qualitative study of nonlinear physical phenomena modeled by differential equations or discrete maps. We discuss applications in classical mechanics, electrical engineering, fluid mechanics, and biology. A more advanced Part II of this class is offered every other year.|
|Content||(1) Basic facts about nonlinear systems: Existence, uniqueness, and dependence on initial data.|
(2) Near equilibrium dynamics: Linear and Lyapunov stability
(3) Bifurcations of equilibria: Center manifolds, normal forms, and elementary bifurcations
(4) Nonlinear dynamical systems on the plane: Phase plane techniques, limit sets, and limit cycles.
(5) Time-dependent dynamical systems: Floquet theory, Poincare maps, averaging methods, resonance
|Lecture notes||The class lecture notes will be posted electronically after each lecture. Students should not rely on these but prepare their own notes during the lecture.|
|Prerequisites / Notice||- Prerequisites: Analysis, linear algebra and a basic course in differential equations.|
- Exam: two-hour written exam in English.
- Homework: A homework assignment will be due roughly every other week. Hints to solutions will be posted after the homework due dates.
|151-0535-00L||Optical Methods in Experimental Mechanics||W||4 credits||3G||E. Hack, R. Brönnimann|
|Abstract||The lecture introduces optical methods to assess the mechanical behaviour of a structure, to determine material parameters, and to validate results from numerical simulations. Focus is on camera-based techniques for deformation, strain and stress analysis. Applications, strengths and limitations are discussed. The lecture includes two afternoons of hands-on experience at Empa in Dübendorf.|
|Objective||The students are enabled to design basic esperiments based on optical methods and to describe the process of image acquisition. They understand the working principle of the optical techniques for shape, deformation and strain measurement. Most notably, they can explain how the measurand is transformed into an interference signal, a change of the polarization state or a change of surface temperature. They know the main application fields of the individual techniques. They are able to choose the most appropriate technique for solving a measurement task and to estimate its expected resolution. Through the hands-on experience the students gain a deeper and sustained understanding by applying the theoretical foundations to tangible measurement tasks.|
|Content||After an introduction into optics and image acquisition the lecture explains how to transform mechanical quantities such as shape, deformation, strain or stress into an image content. The measurement techniques make use of a variety of basic principles such as |
- Infrared radiation
The techniques are based on cameras, most notably CCD and CMOS sensors as well as micro-bolometers, and make use of incoherent white light and coherent light sources such as lasers.
The lecture includes:
- Introduction to optics and imaging
- Digital Image Correlation in 2D and 3D
- Fringe Projection and structured light techniques
- Diffraction and holography
- Speckle pattern interferometry
- Thermoelastic Stress Analysis
- Validation of numerical models
- Fibre based methods
We show that the methods can be applied to microsystems as well as large engineering structures. In addition, time-resolved measurements in the context of modal analysis and dynamic events are explained.
The lecture includes two afternoons at Empa, where the student will gain first-hand experience with optical methods in the laboratory. These hands-on classes may include e.g. Digital Image Correlation, Speckle pattern interferometry, Thermal Stress Analysis, Fibre optic sensors, Fringe projection - depending on availability of the equipment and the interest of the students.
|Lecture notes||Copies of the presented slides will be made available on-line through ILIAS. Each lecture includes a set of exercises. You will be invited to a private blog which shall stimulate the discussion of the lecture content and the exercises. Standard solutions for the exercises will be posted with a time shift.|
|Literature||A good overview on the optical methods is presented in the following text books:|
Toru Yoshizawa, Ed., Handbook of Optical Metrology, 2nd edition, 2015, CRC Press, Boca Raton
Pramod Rastogi, Erwin Hack, Eds., Optical Methods for Solid Mechanics: A Full-Field Approach
2012, Wiley-VCH, Berlin
W. N. Sharpe Jr., Ed., Handbook of Experimental Solid Mechanics
2009, Springer, New York
|Prerequisites / Notice||Basic knowledge of optics and interferometry as taught in basic physics courses are advantageous.|
|151-0550-00L||Adaptive Materials for Structural Applications||W||4 credits||3G||A. Bergamini|
|Abstract||Adaptive materials offer appealing ways to extend the design space of structures by introducing time-variable properties into them. In this course, the physical working principles of selected adaptive materials are analyzed and simple models for describing their behavior are presented. Some applications are illustrated, also with laboratory experiments where possible.|
|Objective||The study of adaptive materials covers topics that range from chemistry to theoretical mechanics.|
The aim of this course is to convey knowledge about adaptive materials, their properties and the physical mechanisms that govern their function, so as to develop the skills to deal with this interdisciplinary subject.
|Content||This course will provide the students with an insight into the properties and physical phenomena which lead to the features of adaptive materials. Starting from chemomechanical (skeletal muscles), the physical behavior of a wide range of adaptive materials, thermo- and photo-mechanical, electro-mechanical, magneto-mechanical and meta-materials will be thoroughly discussed and analyzed. Up-to-date results on their performance and their implementation in mechanical structures will be detailed and studied in laboratory sessions. Analytical tools and energy based considerations will provide the students with effective instruments for understanding adaptive materials and assess their performance when integrated in structures or when arranged in particular fashions.|
Basic concepts: Power conjugated variables, dissipative effects, geometry- and materials-based energy conversion
Chemo-mechanical coupling: Energy conversion in skeletal muscle and other chemomechanical systems,optional: and photo-mechanical coupling, azopolymers.
Thermo-mechanical coupling: Shape memory alloys / polymers
Electromechanical coupling(1): DEA, EBL, electrorheological fluids
Shape control / morphing: Use, requirements, challenges
Morphing applications of variable stiffness structures: Lab work
Electromechanical coupling (2): Piezoelectric, electrostrictive effect
Vibration Reduction: Measurement, passive, semi-active (active) damping methods
Vibration reduction applications of piezoelectric materials: Lab work
Metamaterials: Definition of metamaterials - electromagnetic, acoustical and other metamaterials
Magneto-mechanical coupling: Magnetostrictive effect, mSMA, magnetorheological fluids, ferrofluids
Energy harvesting and sensing: Energy harvesting with EAP and piezoelectric materials, transducers as sensors: Piezo, resistive,...
|Lecture notes||Lecture notes (manuscript and handouts) will be provided|
|151-0573-00L||System Modeling||W||4 credits||2V + 1U||L. Guzzella|
|Abstract||Introduction to system modeling for control. Generic modeling approaches based on first principles, Lagrangian formalism, energy approaches and experimental data. Model parametrization and parameter estimation. Basic analysis of linear and nonlinear systems.|
|Objective||Learn how to mathematically describe a physical system or a process in the form of a model usable for analysis and control purposes.|
|Content||This class introduces generic system-modeling approaches for control-oriented models based on first principles and experimental data. The class will span numerous examples related to mechatronic, thermodynamic, chemistry, fluid dynamic, energy, and process engineering systems. Model scaling, linearization, order reduction, and balancing. Parameter estimation with least-squares methods. Various case studies: loud-speaker, turbines, water-propelled rocket, geostationary satellites, etc. The exercises address practical examples.|
|Lecture notes||The handouts in English will be sold in the first lecture.|
|Literature||A list of references is included in the handouts.|
|151-0655-00L||Skills for Creativity and Innovation||W||4 credits||3G||I. Goller, C. Kobe|
|Abstract||This lecture aims to enhance the knowledge and competency of students regarding their innovation capability. An overview on prerequisites of and different skills for creativity and innovation in individual & team settings is given. The focus of this lecture is clearly on building competencies - not just acquiring knowledge.|
|Objective||- Basic knowledge about creativity and skills|
- Knowledge about individual prerequisites for creativity
- Development of individual skills for creativity
- Knowledge about teams
- Development of team-oriented skills for creativity
- Knowledge and know-how about transfer to idea generation teams
|Content||Basic knowledge about creativity and skills:|
- Introduction into creativity & innovation: definitions and models
Knowledge about individual prerequisites for creativity:
- Personality, motivation, intelligence
Development of individual skills for creativity:
- Focus on creativity as problem analysis & solving
- Individual skills in theoretical models
- Individual competencies: exercises and reflection
Knowledge about teams:
- Definitions and models
- Roles in innovation processes
Development of team-oriented skills for creativity:
- Idea generation and development in teams
- Cooperation & communication in innovation teams
Knowledge and know-how about transfer to idea generation teams:
- Self-reflection & development planning
- Methods of knowledge transfer
|Lecture notes||Slides, script and other documents will be distributed via moodle.ethz.ch|
(access only for students registered to this course)
|Literature||Goller, I. & Bessant, J. (2017). Creativity for Innovation Management. Routledge. (ISBN-13: 978-1138641327)|
As well as material handed out in the lecture
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