401-4671-00L Advanced Numerical Methods for CSE
| Semester | Autumn Semester 2019 |
| Lecturers | S. Mishra |
| Periodicity | yearly recurring course |
| Language of instruction | English |
Courses
| Number | Title | Hours | Lecturers | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 401-4671-00 V | Advanced Numerical Methods for CSE | 4 hrs |
| S. Mishra | ||||||
| 401-4671-00 U | Advanced Numerical Methods for CSE Groups are selected in myStudies. Thu 8-10 or Fri 13-15 | 2 hrs |
| S. Mishra | ||||||
| 401-4671-00 P | Advanced Numerical Methods for CSE | 1 hrs | S. Mishra |
Catalogue data
| Abstract | This course will focus on teaching different advanced topics in numerical methods for science and engineering. The main aim would be introduce novel algorithms and discuss their implementation. |
| Learning objective | --Presentation of state of the art numerical methods in computational fluid dynamics. --Advanced implementation in C++ -- Introduction of the role of data in scientific computing, particularly in the context of uncertainty quantification (UQ) and machine learning (deep learning) |
| Content | A selection of the following topics will be covered: 1. Advanced numerical methods in fluid dynamics: -- Finite volume schemes -- High-resolution schemes on both structured and unstructured grids -- ENO/WENO methods for structured grids. -- DG methods for unstructured grids. 2. Uncertainty quantification in fluid dynamics -- Modeling of uncertainty in terms of random fields. -- Monte Carlo methods -- Multi-level Monte Carlo methods. -- Quasi-Monte Carlo methods. 3. Deep learning in CFD -- Introduction to deep learning --Machine learning and DG methods --Deep learning observables in CFD. -- UQ with deep learning |
| Lecture notes | Lecture material will be created during the course and will be made available. |
| Prerequisites / Notice | - Familiarity with basic numerical methods (as taught in the course "Numerical Methods for CSE"). - Knowledge of numerical methods for differential equations (as covered in the course "Numerical Methods for Partial Differential Equations"). - Some knowledge of HPC. |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 9 credits |
| Examiners | S. Mishra |
| Type | session examination |
| Language of examination | English |
| Repetition | The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit. |
| Admission requirement | The code review mentioned below is regarded as a mandatory performance element that has to be passed in order to be admitted to the main examination. |
| Mode of examination | oral 30 minutes |
| Additional information on mode of examination | Students are expected to give a 10-15-minute oral code review and answer questions concerning selected homework programming assignments at a date announced in the beginning of the term. This will be graded and the grade will contribute 10% to the final grade. The code review is also regarded as a mandatory performance element that has to be passed in order to be admitted to the main examination. |
| This information can be updated until the beginning of the semester; information on the examination timetable is binding. | |
Learning materials
| Main link | Information |
| Only public learning materials are listed. | |
Groups
| 401-4671-00 U | Advanced Numerical Methods for CSE | ||||||
| Groups | G-01 |
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| G-02 |
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Restrictions
| There are no additional restrictions for the registration. |
Offered in
| Programme | Section | Type | |
|---|---|---|---|
| Computational Science and Engineering Master | Core Courses | W |  |