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Course module: NWI-WB109
NWI-WB109
Numerical Methods for PDEs
Course infoSchedule
Course moduleNWI-WB109
Credits (ECTS)6
CategoryBA (Bachelor)
Language of instructionEnglish
Offered byRadboud University; Faculty of Science; Wiskunde, Natuur- en Sterrenkunde;
Lecturer(s)
Coordinator
dr. V. Nikolic
Other course modules lecturer
Lecturer
dr. V. Nikolic
Other course modules lecturer
Contactperson for the course
dr. V. Nikolic
Other course modules lecturer
Examiner
dr. V. Nikolic
Other course modules lecturer
Academic year2022
Period
KW3-KW4  (30/01/2023 to 31/08/2023)
Starting block
KW3
Course mode
full-time
Remarks-
Registration using OSIRISYes
Course open to students from other facultiesNo
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
At the end of the course,  
  • You will be able to employ a range of techniques to approximately solve partial differential equations when exact methods cannot be applied.
  • You will be able to analyze finite difference schemes for linear partial differential equations and determine their convergence, accuracy, stability, and relative efficiency.
  • You will be able to convert a finite difference algorithm into a well-designed code in Python. You will know how to test (verify) a numerical simulation code.
        
Content
This numerical analysis course is concerned with the approximate solutions of partial differential equations (PDEs), which are important in mathematical modeling in all fields of science and engineering. In the real world (i.e., outside university), analytic methods can rarely be applied to give quantitative results, so numerical methods are essential. We will focus mainly on the Finite difference methods for solving PDEs and combine learning about their mathematical aspects, such as accuracy and stability, with their practical implementation using Python.
Level

Presumed foreknowledge

Previous knowledge of PDEs and Numerical Methods for ODEs is helpful. The course can be followed without having this background knowledge, but additional self-study is recommended for a deeper understanding of the material.

Test information
Exam, which carries 80% of the final grade and will be written or oral depending on the number of participants, and a coding project, which carries 20% of the final grade.

 
Specifics

Recommended materials
Course material
Lecture notes will be posted on Brightspace.
Instructional modes
Course

Tests
Exam
Test weight1
Test typeExam
OpportunitiesBlock KW4

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Kies de Nederlandse taal