Suchergebnis: Katalogdaten im Herbstsemester 2016

Maschineningenieurwissenschaften Master Information
Kernfächer
Bioengineering
NummerTitelTypECTSUmfangDozierende
551-0319-00LCellular Biochemistry (Part I) Information W3 KP2VU. Kutay, R. I. Enchev, B. Kornmann, M. Peter, I. Zemp, weitere Dozierende
KurzbeschreibungConcepts and molecular mechanisms underlying the biochemistry of the cell, providing advanced insights into structure, function and regulation of individual cell components. Particular emphasis will be put on the spatial and temporal integration of different molecules and signaling pathways into global cellular processes such as intracellular transport, cell division & growth, and cell migration.
LernzielThe full-year course (551-0319-00 & 551-0320-00) focuses on the molecular mechanisms and concepts underlying the biochemistry of cellular physiology, investigating how these processes are integrated to carry out highly coordinated cellular functions. The molecular characterisation of complex cellular functions requires a combination of approaches such as biochemistry, but also cell biology and genetics. This course is therefore the occasion to discuss these techniques and their integration in modern cellular biochemistry.
The students will be able to describe the structural and functional details of individual cell components, and the spatial and temporal regulation of their interactions. In particular, they will learn to explain the integration of different molecules and signaling pathways into complex and highly dynamic cellular processes such as intracellular transport, cytoskeletal rearrangements, cell motility, cell division and cell growth. In addition, they will be able to illustrate the relevance of particular signaling pathways for cellular pathologies such as cancer.
InhaltStructural and functional details of individual cell components, regulation of their interactions, and various aspects of the regulation and compartmentalisation of biochemical processes.
Topics include: biophysical and electrical properties of membranes; viral membranes; structural and functional insights into intracellular transport and targeting; vesicular trafficking and phagocytosis; post-transcriptional regulation of gene expression.
SkriptScripts and additional material will be provided during the semester. Please contact Dr. Alicia Smith for assistance with the learning materials. (alicia.smith@bc.biol.ethz.ch)
LiteraturRecommended supplementary literature (review articles and selected primary literature) will be provided during the course.
Voraussetzungen / BesonderesTo attend this course the students must have a solid basic knowledge in chemistry, biochemistry and general biology. The course will be taught in English.
Design, Computation, Product Development & Manufacturing
NummerTitelTypECTSUmfangDozierende
151-0104-00LUncertainty Quantification for Engineering & Life Sciences Belegung eingeschränkt - Details anzeigen
Findet dieses Semester nicht statt.
Number of participants limited to 60.
W4 KP3GP. Koumoutsakos
KurzbeschreibungQuantification of uncertainties in computational models pertaining to applications in engineering and life sciences. Exploitation of massively available data to develop computational models with quantifiable predictive capabilities. Applications of Uncertainty Quantification and Propagation to problems in mechanics, control, systems and cell biology.
LernzielThe course will teach fundamental concept of Uncertainty Quantification and Propagation (UQ+P) for computational models of systems in Engineering and Life Sciences. Emphasis will be placed on practical and computational aspects of UQ+P including the implementation of relevant algorithms in multicore architectures.
InhaltTopics that will be covered include: Uncertainty quantification under
parametric and non-parametric modelling uncertainty, Bayesian inference with model class assessment, Markov Chain Monte Carlo simulation, prior and posterior reliability analysis.
SkriptThe class will be largely based on the book: Data Analysis: A Bayesian Tutorial by Devinderjit Sivia as well as on class notes and related literature that will be distributed in class.
Literatur1. Data Analysis: A Bayesian Tutorial by Devinderjit Sivia
2. Probability Theory: The Logic of Science by E. T. Jaynes
3. Class Notes
Voraussetzungen / BesonderesFundamentals of Probability, Fundamentals of Computational Modeling
151-0735-00LDynamic Behavior of Materials and Structures
Findet dieses Semester nicht statt.
W4 KP2V + 2UD. Mohr
KurzbeschreibungLectures 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.
LernzielStudents 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 navel engineering.
InhaltTopics 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;
SkriptSlides of the lectures, relevant journal papers and users manuals will be provided.
LiteraturVarious books will be recommended covering the topics discussed in class
Voraussetzungen / BesonderesCourse in continuum mechanics (mandatory), finite element method (recommended)
151-3205-00LExperimental Ergonomics Belegung eingeschränkt - Details anzeigen
Number of participants limited to 15.
W4 KP2V + 2AJ. Held
KurzbeschreibungYou will learn how to apply the scientific discipline of ergonomics for system analysis and product development "in order to optimise human well-being and overall system performance" (www.iea.cc). The course offers the framework of models, concepts, methods and tools of applied ergonomics. Teaching is combined with learning-by-doing and research-based learning.
LernzielKnowledge of:
- Principles and rules of applied ergonomic system and product design.
- Methods and tools of ergonomic analysis and evaluation.
Practical experiences and hands-on skills in:
- Conducting a study in system and task analysis.
- Analysing human-product interactions.
- Applying ergonomic knowledge for product and system improvements.
Inhalt- Definition and role of applied ergonomics in engineering and design.
- Framework of ergonomic analysis and design.
- Design principles and rules.
- Methods and tools for system and task analysis.
Hands-on experience in team work:
- Experimental study of human-product interaction and usability through eye-tracking
- Field study of system and task analysis, including on-site visits of complex work stations (Hospital OR/ICU or Air traffic/Railway Control Rooms).
SkriptHandout at the start of the course.
LiteraturAhlstrom, V. and Longo, V. (2003). Human Factors Design Standard (HFDS). http://hf.tc.faa.gov/hfds/default.htm
Wiklund M.E., Wilcox, S.B. (2005). Designing Usability into Medical Products. Taylor & Francis.
Rubin, J. and Chisnell, D. (2008). Handbook of Usability Testing: How to Plan, Design and Conduct Effective Tests. Wiley.
Hölscher, U., Laurig, W. & Müller-Arnecke, H.W. (2008). Prinziplösungen zur ergonomischen Gestaltung von Medizingeräten. BAUA Forschung Projekt F1902.
http://www.baua.de/de/Publikationen/Fachbeitraege/F1902.pdf
Niku, S.B. (2009). Creative Design of Products and Systems (Chapter 8). Wiley.
Voraussetzungen / BesonderesMax. number of participants is 15.
Experiments and field studies in teams of 2-3 students are obligatory.
151-3209-00LEngineering Design Optimization Belegung eingeschränkt - Details anzeigen
Number of participants limited to 35.
W4 KP4GK. Shea, T. Stankovic
KurzbeschreibungThe course covers fundamentals of computational optimization methods in the context of engineering design. It develops skills to formally state and model engineering design tasks as optimization problems and select appropriate methods to solve them.
LernzielThe lecture and exercises teach the fundamentals of optimization methods in the context of engineering design. After taking the course students will be able to express engineering design problems as formal optimization problems. Students will also be able to select and apply a suitable optimization method given the nature of the optimization model. They will understand the links between optimization and engineering design in order to design more efficient and performance optimized technical products. The exercises are MATLAB based.
Inhalt1. Optimization modeling and theory 2. Unconstrained optimization methods 2. Constrained optimization methods - linear and non-linear 4. Direct search methods 5. Stochastic and evolutionary search methods 6. Multi-objective optimization
Skriptavailable on Moodle
363-1065-00LDesign Thinking: Human-Centred Solutions to Real World Challenges Belegung eingeschränkt - Details anzeigen
Due to didactic reasons, the number of participants is limited to 30.

All interested students are invited to apply for this course by sending a one-page motivation letter until 14.9.16 to Florian Rittiner (frittiner@ethz.ch).

Additionally please enroll via mystudies. Places will be assigned after the first lecture on the basis of your motivation letter and commitment for the class.
W5 KP5GA. Cabello Llamas, F. Rittiner, S. Brusoni, C. Hölscher, M. Meboldt
KurzbeschreibungThe goal of this course is to engage students in a multidisciplinary collaboration to tackle real world problems. Following a design thinking approach, students will work in teams to solve a set of design challenges that are organized as a one-week, a three-week, and a final six-week project in collaboration with an external project partner.

Information and application: www.sparklabs.ch/ethz
LernzielDuring the course, students will learn about different design thinking methods and tools. This will enable them to:
- Generate deep insights through the systematic observation and interaction of key stakeholders.
- Engage in collaborative ideation with a multidisciplinary (student) team.
- Rapidly prototype and iteratively test ideas and concepts by using various materials and techniques.
InhaltThe purpose of this course is to equip the students with methods and tools to tackle a broad range of problems. Following a Design Thinking approach, the students will learn how to observe and interact with key stakeholders in order to develop an in-depth understanding of what is truly important and emotionally meaningful to the people at the center of a problem. Based on these insights, the students ideate on possible solutions and immediately validated them through quick iterations of prototyping and testing using different tools and materials. The students will work in multidisciplinary teams on a set of challenges that are organized as a one-week, a three-week, and a final six-week project with an external project partner. In this course, the students will learn about the different Design Thinking methods and tools that are needed to generate deep insights, to engage in collaborative ideation, rapid prototyping and iterative testing.

Design Thinking is a deeply human process that taps into the creative abilities we all have, but that get often overlooked by more conventional problem solving practices. It relies on our ability to be intuitive, to recognize patterns, to construct ideas that are emotionally meaningful as well as functional, and to express ourselves through means beyond words or symbols. Design Thinking provides an integrated way by incorporating tools, processes and techniques from design, engineering, the humanities and social sciences to identify, define and address diverse challenges. This integration leads to a highly productive collaboration between different disciplines.

For more information and the application visit: http://sparklabs.ch/ethz
Voraussetzungen / BesonderesClass attendance and active participation is crucial as much of the learning occurs through the work in teams during class. Therefore, attendance is obligatory for every session. Please also note that the group work outside class is an essential element of this course, so that students must expect an above-average workload.
Multidisziplinfächer
Den Studierenden steht das gesamte Lehrangebot der ETH Zürich, der ETH Lausanne sowie der Universitäten Zürich und St. Gallen zur individuellen Auswahl offen.
» Gesamtes Lehrangebot der ETH Zürich
Studienarbeit
NummerTitelTypECTSUmfangDozierende
151-1002-00LSemester Project Mechanical Engineering Belegung eingeschränkt - Details anzeigen
Only for Mechanical Engineering MSc.

The subject of the Semester Project and the choice of the supervisor (ETH-professor) are to be approved in advance by the tutor.
O8 KP17AProfessor/innen
KurzbeschreibungDas Ziel der Studienarbeit ist es, dass Master-Studierende unter Anwendung der erworbenen Fach- und Sozialkompetenzen erste Erfahrungen in der selbständigen Lösung eines technischen Problems sammeln. Die Tutoren/Tutorinnen schlagen das Thema der Studienarbeit vor, arbeiten den Projekt- und Fahrplan zusammen mit den Studierenden aus und überwachen die gesamte Durchführung.
LernzielDas Ziel der Studienarbeit ist es, dass Master-Studierende unter Anwendung der erworbenen Fach- und Sozialkompetenzen erste Erfahrungen in der selbständigen Lösung eines technischen Problems sammeln.
Industrie-Praxis
NummerTitelTypECTSUmfangDozierende
151-1003-00LIndustrial Internship Mechanical EngineeringO8 KPexterne Veranstalter
KurzbeschreibungEs ist das Ziel der 12-wöchigen Praxis, Master-Studierenden die industriellen Arbeitsumgebungen näher zu bringen. Während dieser Zeit bietet sich ihnen die Gelegenheit, in aktuelle Projekte der Gastinstitution involviert zu werden.
LernzielEs ist das Ziel der 12-wöchigen Praxis, Master-Studierenden die industriellen Arbeitsumgebungen näher zu bringen.
GESS Wissenschaft im Kontext
» siehe Studiengang GESS Wissenschaft im Kontext: Typ A: Förderung allgemeiner Reflexionsfähigkeiten
» siehe Studiengang GESS Wissenschaft im Kontext: Sprachkurse ETH/UZH
» Empfehlungen aus dem Bereich GESS Wissenschaft im Kontext (Typ B) für das D-MAVT.
Master-Arbeit
NummerTitelTypECTSUmfangDozierende
151-1001-00LMaster's Thesis Mechanical Engineering Belegung eingeschränkt - Details anzeigen
Students who fulfill the following criteria are allowed to begin with their Master's Thesis:
a. successful completion of the bachelor program;
b. fulfilling of any additional requirements necessary to gain admission to the master programme;
c. successful completion of the semester project and industrial internship;
d. achievement of 28 ECTS in the category "Core Courses".

The Master's Thesis must be approved in advance by the tutor and is supervised by a professor of ETH Zurich.
To choose a titular professor as a supervisor, please contact the D-MAVT Student Administration.
O30 KP64DProfessor/innen
KurzbeschreibungDie Master-Arbeit schliesst das Master-Studium ab. Die Master-Arbeit fördert die Fähigkeit der Studierenden zur selbständigen und wissenschaftlich strukturierten Lösung eines theoretischen oder angewandten Problems. Thema und Projektplan werden vom Tutor vorgeschlagen und zusammen mit den Studierenden ausgearbeitet.
LernzielDie Master-Arbeit fördert die Fähigkeit der Studierenden zur selbständigen und wissenschaftlich strukturierten Lösung eines theoretischen oder angewandten Problems.
Auflagen-Lerneinheiten
Das untenstehende Lehrangebot gilt nur für MSc Studierende mit Zulassungsauflagen.
NummerTitelTypECTSUmfangDozierende
406-0173-AALLinear Algebra I and II
Belegung ist NUR erlaubt für MSc Studierende, die diese Lerneinheit als Auflagenfach verfügt haben.

Alle andere Studierenden (u.a. auch Mobilitätsstudierende, Doktorierende) können diese Lerneinheit NICHT belegen.
E-6 KP13RN. Hungerbühler
KurzbeschreibungLinear algebra is an indispensable tool of engineering mathematics. The course is an introduction to basic methods and fundamental concepts of linear algebra and its applications to engineering sciences.
LernzielAfter completion of this course, students are able to recognize linear structures and to apply adequate tools from linear algebra in order to solve corresponding problems from theory and applications. In addition, students have a basic knowledge of the software package Matlab.
InhaltSystems of linear equations, Gaussian elimination, solution space, matrices, LR decomposition, determinants, structure of linear spaces, normed vector spaces, inner products, method of least squares, QR decomposition, introduction to MATLAB, applications.
Linear maps, kernel and image, coordinates and matrices, coordinate transformations, norm of a matrix, orthogonal matrices, eigenvalues and eigenvectors, algebraic and geometric multiplicity, eigenbasis, diagonalizable matrices, symmetric matrices, orthonormal basis, condition number, linear differential equations, Jordan decomposition, singular value decomposition, examples in MATLAB, applications.

Reading:

Gilbert Strang "Introduction to linear algebra", Wellesley-Cambridge Press: Chapters 1-6, 7.1-7.3, 8.1, 8.2, 8.6

A Practical Introduction to MATLAB: http://www.math.ethz.ch/~grsam/Numerik_MAVT_WS0203/docs/intro.pdf

Matlab Primer: http://www.math.ethz.ch/~grsam/Numerik_MAVT_WS0203/docs/primer.pdf
Literatur- Gilbert Strang: Introduction to linear algebra. Wellesley-Cambridge Press

- A Practical Introduction to MATLAB: http://www.math.ethz.ch/~grsam/Numerik_MAVT_WS0203/docs/intro.pdf

- Matlab Primer: http://www.math.ethz.ch/~grsam/Numerik_MAVT_WS0203/docs/primer.pdf
406-0353-AALAnalysis III Information
Belegung ist NUR erlaubt für MSc Studierende, die diese Lerneinheit als Auflagenfach verfügt haben.

Alle andere Studierenden (u.a. auch Mobilitätsstudierende, Doktorierende) können diese Lerneinheit NICHT belegen.
E-4 KP9RM. Soner
KurzbeschreibungEinführung in die partiellen Differentialgleichungen. Klassifizieren und Lösen von in der Praxis wichtigen Differentialgleichungen. Es werden elliptische, parabolische und hyperbolische Differentialgleichungen behandelt. Folgende mathematischen Techniken werden vorgestellt: Laplacetransformation, Fourierreihen, Separation der Variablen, Methode der Charakteristiken.
LernzielMathematische Behandlung naturwissenschaftlicher Probleme lernen. Verstehen der Eigenschaften der verschiedenen Typen von partiellen Differentialgleichungen.
InhaltLaplace Transforms:
- Laplace Transform, Inverse Laplace Transform, Linearity, s-Shifting
- Transforms of Derivatives and Integrals, ODEs
- Unit Step Function, t-Shifting
- Short Impulses, Dirac's Delta Function, Partial Fractions
- Convolution, Integral Equations
- Differentiation and Integration of Transforms

Fourier Series, Integrals and Transforms:
- Fourier Series
- Functions of Any Period p=2L
- Even and Odd Functions, Half-Range Expansions
- Forced Oscillations
- Approximation by Trigonometric Polynomials
- Fourier Integral
- Fourier Cosine and Sine Transform

Partial Differential Equations:
- Basic Concepts
- Modeling: Vibrating String, Wave Equation
- Solution by separation of variables; use of Fourier series
- D'Alembert Solution of Wave Equation, Characteristics
- Heat Equation: Solution by Fourier Series
- Heat Equation: Solutions by Fourier Integrals and Transforms
- Modeling Membrane: Two Dimensional Wave Equation
- Laplacian in Polar Coordinates: Circular Membrane, Fourier-Bessel Series
- Solution of PDEs by Laplace Transform
LiteraturE. Kreyszig, Advanced Engineering Mathematics, John Wiley & Sons, 10. Auflage, 2011

C. R. Wylie & L. Barrett, Advanced Engineering Mathematics, McGraw-Hill, 6th ed.

G. Felder, Partielle Differenzialgleichungen für Ingenieurinnen und Ingenieure, hypertextuelle Notizen zur Vorlesung Analysis III im WS 2002/2003.

Y. Pinchover, J. Rubinstein, An Introduction to Partial Differential Equations, Cambridge University Press, 2005

For reference/complement of the Analysis I/II courses:

Christian Blatter: Ingenieur-Analysis (Download PDF)
Voraussetzungen / BesonderesWeitere Informationen unter:
http://www.math.ethz.ch/education/bachelor/lectures/hs2013/other/analysis3_itet
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