Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

Petros Koumoutsakos: Catalogue data in Spring Semester 2015

Name Prof. Dr. Petros Koumoutsakos
FieldComputational Science
Address
Professur f. Computational Science
ETH Zürich, CLT F 12
Clausiusstrasse 33
8092 Zürich
SWITZERLAND
Telephone+41 44 632 52 58
E-mailpetros@ethz.ch
URLhttp://www.cse-lab.ethz.ch/index.php?&option=com_content&view=article&id=100&catid=38
DepartmentMechanical and Process Engineering
RelationshipFull Professor

NumberTitleECTSHoursLecturers
151-0104-00LUncertainty Quantification for Engineering & Life Sciences Restricted registration - show details
Does not take place this semester.
Number of participants limited to 40.
4 credits3GP. Koumoutsakos
AbstractQuantification 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.
ObjectiveThe 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.
ContentTopics 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.
Lecture notesThe 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.
Literature1. Data Analysis: A Bayesian Tutorial by Devinderjit Sivia
2. Probability Theory: The Logic of Science by E. T. Jaynes
3. Class Notes
Prerequisites / NoticeFundamentals of Probability, Fundamentals of Computational Modeling
151-0112-10LEngineering Tool III: Object Oriented Programming with C++
The Engineering Tool course is for MAVT-Bachelor students only.

The enrollment in either this course or in the course "Engineering Tool III: FEM-Programme" (151-0042-01L) is mandatory.

Only one course can be chosen per semester. All Engineering Tool courses are for MAVT-Bachelor students only.
0.4 credits1KG. Tauriello, C. Conti, P. Koumoutsakos
AbstractIntroduction to object oriented programming with C++. Fundamental concepts, simple applications and hands on tutorials.
ObjectiveLearn basic concepts of object oriented programming in C++: classes, inheritance, polymorphism and STL
ContentTutorials, hands on exercises
Lecture notesHandouts
LiteratureProgramming: Principles and Practice using C++ (B. Stroustrup)
Prerequisites / NoticePrerequisites: "Informatik" (2nd semester lecture), laptop (at least one every two students). We will use a VirtualBox linux environment (as in "Informatik", 2nd semester). This Engineering Tool is a prerequisite for the class "Computational Methods for Engineering Applications I"
151-0431-00LComputational Methods for Engineering Applications I4 credits2V + 1UP. Koumoutsakos, G. Tauriello
AbstractFundamental Computational Methods for data analysis, modeling and simulation
relevant to Engineering applications. The course emphasizes the implementation
of these methods using object oriented programming in C++ with application
examples drawn from Engineering applications
ObjectiveThe course aims to introduce Engineering students to fundamentals of
Interpolation, Solution of non-linear equations, Filtering and Numerical
Integration. The course aims to integrate numerical methods with enhancing the
students programming skills in object oriented languages. The course serves as
foundation for Computational Methods in Engineering Applications II (Fall
Semester), that is concerned with Ordinary and Partial Differential Equations.
Content27/02- Lagrange & Least Squares
06/03- Splines
13/03- Multivariate Interpolation, NURBS
20/03- Non-Linear Equations: Polynomials - Orthogonal Functions
27/03- Non-Linear Equations: Radial Basis Functions
17/04- Convolution
24/04- Discrete Fourier Transforms
08/05- Numerical Integration: Rectangle, Trapezoidal, Simpson
15/05- Numerical Integration: Romberg, Richardson Extrapolation
22/05- Numerical Integration: Adaptive and Gauss Quadrature
29/05- Numerical Integration: Monte Carlo
Lecture notesLecture Notes will be distributed in class
Literature1. Introduction to Applied Mathematics, G. Strang
2. Analysis of Numerical Methods, Isaacson and Keller
Prerequisites / Notice- Informatik
- 151-0112-10L Engineering Tool III: Object oriented programming with C++
151-1053-00LThermo- and Fluid Dynamics Information 0 credits2KP. Jenny, R. S. Abhari, K. Boulouchos, P. Koumoutsakos, C. Müller, H. G. Park, D. Poulikakos, H.‑M. Prasser, T. Rösgen, A. Steinfeld
AbstractCurrent advanced research activities in the areas of thermo- and fluid dynamics are presented and discussed, mostly by external speakers.

The talks are public and open also for interested students.
ObjectiveKnowledge of advanced research in the areas of thermo- and fluid dynamics
ContentCurrent advanced research activities in the areas of thermo- and fluid dynamics are presented and discussed, mostly by external speakers.
252-5251-00LComputational Science2 credits2SP. Arbenz, T. Hoefler, P. Koumoutsakos
AbstractClass participants study and make a 40 minute presentation (in English) on fundamental papers of Computational Science. A preliminary discussion of the talk (structure, content, methodology) with the responsible professor is required. The talk has to be given in a way that the other seminar participants can understand it and learn from it. Participation throughout the semester is mandatory.
ObjectiveStudying and presenting fundamental works of Computational Science. Learning how to make a scientific presentation.
ContentClass participants study and make a 40 minute presentation (in English) on fundamental papers of Computational Science. A preliminary discussion of the talk (structure, content, methodology) with the responsible professor is required. The talk has to be given in a way that the other seminar participants can understand it and learn from it. Participation throughout the semester is mandatory.
Lecture notesnone
LiteraturePapers will be distributed in the first seminar in the first week of the semester
401-0686-00LHigh Performance Computing for Science and Engineering (HPCSE) for CSE Information 7 credits4G + 2PP. Koumoutsakos, M. Troyer
Abstract
Objective
401-0686-10LHigh Performance Computing for Science and Engineering (HPCSE) for Engineers II Information 4 credits4GM. Troyer, P. Koumoutsakos
Abstract
Objective