401-0675-00L  Statistical and Numerical Methods for Chemical Engineers

SemesterAutumn Semester 2023
LecturersR. Käppeli, P. Müller, C.‑J. Shih
Periodicityyearly recurring course
Language of instructionEnglish


AbstractThis course covers common numerical algorithms and statistical methods used by chemical engineers to solve typical problems arising in industrial and research practice.
Learning 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
Lecture notesFor the numerics part, see http://www.sam.math.ethz.ch/~karoger/numci/2023/

For the statistics part, see http://stat.ethz.ch/lectures/as23/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
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Problem-solvingassessed