## Roger Käppeli: Catalogue data in Autumn Semester 2022 |

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 |

roger.kaeppeli@sam.math.ethz.ch | |

URL | https://people.math.ethz.ch/~karoger/ |

Department | Mathematics |

Relationship | Lecturer |

Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|

401-0675-00L | Statistical and Numerical Methods for Chemical Engineers | 3 credits | 2V + 2U | R. Käppeli, P. Müller, C.‑J. Shih | |

Abstract | This course covers common numerical algorithms and statistical methods used by chemical engineers to solve typical problems arising in industrial and research practice. | ||||

Objective | This 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. | ||||

Content | Topics 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 | ||||

Lecture notes | For the numerics part, see http://www.sam.math.ethz.ch/~karoger/numci/2022/ For the statistics part, see http://stat.ethz.ch/lectures/as22/statistical-numerical-methods.php | ||||

Literature | Recommended 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 | ||||

401-2813-00L | Programming Techniques for Scientific Simulations I | 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. | ||||

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. |