Roger Käppeli: Catalogue data in Autumn Semester 2020

Name Dr. Roger Käppeli
Address
Professur für Angew. Mathematik
ETH Zürich, HG G 52.1
Rämistrasse 101
8092 Zürich
SWITZERLAND
Telephone+41 44 632 84 95
E-mailroger.kaeppeli@sam.math.ethz.ch
URLhttps://people.math.ethz.ch/~karoger/
DepartmentMathematics
RelationshipLecturer

NumberTitleECTSHoursLecturers
401-0675-00LStatistical and Numerical Methods for Chemical Engineers3 credits2V + 2UR. Käppeli, P. Müller, C.‑J. Shih, M. Sokolov
AbstractThis course covers common numerical algorithms and statistical methods used by chemical engineers to solve typical problems arising in industrial and research practice.
ObjectiveThis course covers common numerical algorithms and statistical methods used by chemical engineers to solve typical problems arising in industrial and research practice. The focus is on application of these algorithms to real world problems, while the underlying mathematical principles are also explained. The MATLAB environment is adopted to integrate computation, visualization and programming.
ContentTopics covered:

Part I: Numerical Methods:
- Interpolation & Numerical Calculus
- Non-linear Equations
- Ordinary Differential Equations
- Partial Differential Equations
- Linear and Non-linear Least Squares

Part II: Statistical Methods:
- Data analysis and regression methods
- Statistical experimental design
- Multivariate analysis of spectra
Lecture notesFor the numerics part, see http://www.sam.math.ethz.ch/~karoger/numci/2020/

For the statistics part, see http://stat.ethz.ch/lectures/as20/statistical-numerical-methods.php
LiteratureRecommended reading:
1) U. Ascher and C. Greif, A First Course in Numerical Methods, SIAM, Philadelphia, 2011
2) K. J. Beers, Numerical Methods for Chemical Engineering : Applications in MATLAB, Cambridge : Cambridge University Press, 2006
3) W. H. Press, S. A. Teukolsky, W. T. Vetterling, B. P. Flannery, Numerical Recipes, Cambridge University Press
4) W. A. Stahel, Statistische Datenanalyse, Vieweg, 4th edition 2002
402-0811-00LProgramming Techniques for Scientific Simulations I5 credits4GR. Käppeli
AbstractThis 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.
ObjectiveThe goal of the course is that students learn basic and advanced programming techniques and scientific software libraries as used and applied for scientific simulations.