Scientific Computing 1 (IN2005)
Course 0000001358 in WS 2022/3
General Data
| Course Type | lecture |
|---|---|
| Semester Weekly Hours | 2 SWS |
| Organisational Unit | Informatics 5 - Chair of Scientific Computing (Prof. Bungartz) |
| Lecturers |
Michael Georg Bader Kislaya Ravi |
| Dates |
Wed, 10:00–12:00, MI HS2 |
Assignment to Modules
-
IN2005: Scientific Computing I / Scientific Computing I
This module is included in the following catalogs:- Catalogue of non-physics elective courses
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks | The module introduces the steps of the scientific computing simulation pipeline on selected simulation scenarios, focusing especially on aspects of modelling and discretization: - classification of mathematical models (discrete/continuous, deterministic/stochastic, etc.); - discrete models (e.g. Markov chain models) - modeling with ordinary differential equations for the example of population growth; - numerical solution of systems of ordinary differential equations; - modeling with partial differential equations (PDE) for the example of fluid dynamics; - numerical discretization methods for partial differential equations (finite elements, time stepping, grids and adaptivity); - limitations and errors encountered in models and discretized models - adequacy and asymptotic behavior of models (stability, consistency, accuracy, and convergence of numerical methods) An outlook will be given on the impact that further steps of the simulation pipeline can have on the selection of modeling and discretization techniques, such as: - efficient sequential and parallel implementation (architectures, parallel programming, load distribution, domain decomposition, parallel numerical methods); - visualization or results - embedding of simulations in larger simulation environments (coupled models, workflows for parameter studies and uncertainty quantification) Examples are primarily selected from societally and economically relevant simulation scenarios, such as: - Discrete and continuous population models (incl. spreading of diseases, traffic simulation, use of population-type models in economy) - Simulation of hazards (e.g. shallow water models for tsunami simulation) - Computational fluid dynamics (towards weather and climate simulation) |
|---|---|
| Links |
Course documents E-Learning course (e. g. Moodle) TUMonline entry |
Equivalent Courses (e. g. in other semesters)
| Semester | Title | Lecturers | Dates |
|---|---|---|---|
| WS 2023/4 | Scientific Computing 1 (IN2005) |
Datar, C.
Ravi, K.
Responsible/Coordination: Bader, M. |
Wed, 10:00–12:00, MI HS2 and singular or moved dates |
| WS 2021/2 | Scientific Computing 1 (IN2005) |
Ravi, K.
Responsible/Coordination: Bader, M. |
Wed, 10:00–12:00, MI HS2 |
| WS 2020/1 | Scientific Computing 1 (IN2005) |
Jovanovic Buha, I.
Ravi, K.
Sarbu, P.
Responsible/Coordination: Bader, M. |
Wed, 10:00–12:00, MI HS1 |
| WS 2019/20 | Scientific Computing 1 (IN2005) | Bader, M. Jovanovic Buha, I. Menhorn, F. Sarbu, P. |
Wed, 10:00–12:00, MI HS2 |
| WS 2018/9 | Scientific Computing 1 (IN2005) | Bader, M. Jovanovic Buha, I. |
Wed, 10:00–12:00, MI HS2 |
| WS 2017/8 | Scientific Computing 1 (IN2005) |
Responsible/Coordination: Bader, M. |
Wed, 10:00–12:00, MI HS2 and singular or moved dates |
| WS 2016/7 | Scientific Computing 1 (IN2005) |
Responsible/Coordination: Bader, M. |
Wed, 10:00–12:00, MI HS2 and singular or moved dates |
| WS 2014/5 | Introduction to Scientific Computing 1 (IN2005) |
Wed, 10:00–12:00, Interims I 102 and singular or moved dates |
|
| WS 2013/4 | Introduction to Scientific Computing 1 (IN2005) |
Wed, 10:00–12:00, MI 00.13.009A Mon, 16:00–18:00, MI 00.13.009A and singular or moved dates |
|
| WS 2012/3 | Introduction to Scientific Computing 1 (IN2005) |