Introduction to Computational Thinking and Programming for CFD
Einführung in das rechnergestützte Denken und Programmieren für CFD
6 LPjedes SemesterENFÜS
Voraussetzungen
Empfohlen, im Wortlaut
Interest in computer simulations and/or numerical methods.
Inhalte
• Fundamentals of Scientific Computing • Data types, conversions, input, and output • Branching and iteration • Root finding, maximization, and minimization • Numerical differentiation and integration • Numerical errors and their quantification • Random sampling, distribution functions, and statistical moments • Computational efficiency • Functional programming and recursion • Object-oriented programming • Plotting and visualization
Lernziele
Students learn to use the higher programming language Python for numerical problem solving, data analysis, and visualization with links to computational fluid dynamics (CFD). After successful completion of the course, participants are able to develop algorithms and computer programs for simple problems on their own. On this basis, students will be put in the position to understand and work themselves into more complex problems. This module provides basic programming experience, which is recommended, but not mandatory, for the sequence of CFD courses (CFD 1, 2, and 3) that is offered by the department.
Prüfungsleistung
The exam can be in written form or as an oral exam. • For a written examination: 90 minutes duration • For an oral exam: 30 min duration Until the end of the first three weeks of lectures it will be announced, if the examination will be offered in written or oral form.
Literatur (4)
- Kong, Siauw & Bayen. Python Programming and Numerical Methods: A Guide for Engineers and Scientists. Academic Press, 2020. URL: https://pythonnumericalmethods.berkeley.edu/notebooks/Index.html
- Guttag. Introduction to Computation and Programming Using Python: With Application to Understanding Data. Second Edition. MIT Press, 2016. ISBN: 9780262529624. URL (code): https://github.com/guttag/Intro-to-Computation-and-Programming
- Chapra & Clough. Applied Numerical Methods with Python for Engineers and Scientists. McGraw-Hill Education, 2021.
- Theis. Einstieg in Python, Galileo Press, 2011.
Bemerkungen
The module aims at students, primarily on the Bachelor level, from all disciplines with no or little programming experience.
Quelle: Modulbeschreibung der BTU · abgerufen 28.09.2026Original