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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 year2021
Period
KW3-KW4  (31/01/2022 to 31/08/2022)
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
  • The student has an overview of a range of techniques to obtain approximate solutions of partial differential equations when analytic methods cannot be applied.
  • The student is familiar with the analysis of numerical schemes, considering convergence, accuracy, stability, and relative efficiency.
  • The student is familiar with approximation methods for initial-value problems, including single step and multi-step methods.
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

Basic knowledge of Multivariable calculus and Ordinary Differential Equations (ODEs). Knowledge of Numerical methods for ODEs is useful. No previous knowledge of PDEs is required.

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 occurrence

Tests
Final Grade
Test weight1
Test typeExam
OpportunitiesBlock KW4, Block KW4

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Kies de Nederlandse taal