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Høst 2023

DTE-3801 Partial differential equations - 5 stp

The course is administrated by

Institutt for datateknologi og beregningsorienterte ingeniørfag

Type of course

The course can be taken as a single subject.

Course contents

The course covers classical topics devoted to Partial differential equations, in addition to an introduction to weak formulations of such equations using Sobolev spaces.

Admission requirements

A relevant undergraduate Bachelor degree in Engineering program in computer science or equivalent.

In addition, the following requirements must be met:

- minimum 25 credits in mathematics (equivalent to Mathematical Methods 1, 2 og 3), 5 credits in statistics and 7,5 ects i physics on a higher level is required.

Recommended prerequisites: Linear Algebra and Numerical Methods

Application code: 9371

Objective of the course

After completing the course, the student should have obtained the following learning outcome:

The students will have some knowledge within the academic field of partial differential equations, and some of their applications in physics and engineering.

The students will be able to formulate and analyze the problems in terms of weak formulations suitable for solving problems numerically via the Finite Element Method.

Language of instruction


Teaching methods

All lectures are pre-recorded on video, and students will be able to follow them via their computer (or laptop /smartphone if you use my Youtube channel).

It is recommended that the students start watching video lectures at 8.15. Those who like, may also meet in the classroom at. 09.15. (to be announced in Canvas)

Here, the teacher will answer questions from the students concerning the topics considered the previous day. Afterwards, the students continue watching video lectures, assisted by the teacher. Normally, students work with this until noon. After lunch, i.e. at. 1 PM, they start with today's exercise and work with this until 4 PM, assisted by the teacher.

All information concerning the course, videos, lecture notes, exercises with solutions, project etc. can be found in Canvas when the course starts.