Applied Tensor Analysis (MAE543)

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General

School

School of Science

Academic Unit

Department of Mathematics

Level of Studies

Undergraduate

Course Code

ΜΑΕ543

Semester

5

Course Title

Applied Tensor Analysis

Independent Teaching Activities

Lectures (Weekly Teaching Hours: 3, Credits: 6)

Course Type

Special Background

Prerequisite Courses -
Language of Instruction and Examinations

Greek

Is the Course Offered to Erasmus Students

Yes (in English)

Course Website (URL) -

Learning Outcomes

Learning outcomes

The course is an introduction to the concepts of Tensor Analysis. The objectives of the course are:

  • Development of the theoretical background in matters relating to Tensor Analysis.
  • Ability of the student to apply the basic concepts of Tensor Analysis.
  • Upon completion of this course the student will be able to solve with analytical methods simple problems of Tensor Analysis and deepen further understanding of such methods.
General Competences

The course aims to enable the undergraduate students to develop basic knowledge of Applied Tensor Analysis and in general of Applied Mathematics. The student will be able to cope with problems of Applied Mathematics giving the opportunity to work in an international multidisciplinary environment.

Syllabus

The tensor concept, Invariance of tensor equations, Curvilinear coordinates, Tensors in generalized curvilinear coordinates, Gauss, Green and Stokes theorems, Scalar and vector fields, Nabla operator and differential operators, Covariant differentiation, Integral theorems, Applications to Fluid Dynamics.

Teaching and Learning Methods - Evaluation

Delivery

In class

Use of Information and Communications Technology -
Teaching Methods
Activity Semester Workload
Lectures 39
Study of theory 78
Home exercises 33
Course total 150
Student Performance Evaluation
  • Weekly assignments
  • Final project
  • Written examination at the end of the semester

Attached Bibliography

  • A. I. Borisenko and I. E. Taparov, Vector and Tensor Analysis, Edition: 2/2017, Editor: G. C. FOYNTAS (in Greek).
  • H. Lass, Vector and Tensor Analysis, Edition: 2/2017, Editor: G. C. FOYNTAS (in Greek).