19M071AMK - The finite element method algorithms in engineering

Course specification
Course title		The finite element method algorithms in engineering
Acronym		19M071AMK
Study programme		Electrical Engineering and Computing
Module
Type of study		master academic studies
Lecturer (for classes)		professor PhD Slobodan Savić professor PhD Milan Ilić
Lecturer/Associate (for practice)		professor PhD Slobodan Savić professor PhD Milan Ilić asst. MA Darko Ninković, electrical and computer engineer
Lecturer/Associate (for OTC)
ESPB		6.0	Status	elective
Condition		None.
The goal		Familiarization with basic algorithms in analysis of engineering problems using the finite element method.
The outcome		Gain knowledge and understanding of theoretical backgrounds of numerical analysis in engineering. Acquire capability to formulate algorithms and write software for modeling of engineering problems using the finite element method. Acquire proficiency in efficient and competent modeling and simulation of typical engineering problems using the finite element method.
Contents
URL to the subject page		https://mtt.etf.bg.edu.rs/ms/amk.htm
Contents of lectures		Discretization of typical differential equations in engineering problems. Scalar and vector finite elements. Coordinate transformations. Imposing the boundary conditions. Spatial discretization (meshing). Discretization in the time domain. Linear systems solving. Hybridization with other methods. Examples of applications in mechanics, civil engineering, fluid dynamics and heat transfer.
Contents of exercises		Practical computer-based asignements and student projects.
Literature
J. N. Reddy, Introduction to the Finite Element Method 4E, McGraw-Hill, 2018. Z. Chen, The Finite Element Method, Its Fundamentals and Applications in Engineering, World Scientific, 2011. J. M. Jin and D. J. Riley, Finite Element Analysis of Antennas and Arrays, Wiley-IEEE Press, 2009.
Number of hours per week during the semester/trimester/year
Lectures	Exercises	OTC	Study and Research	Other classes
2	2
Methods of teaching		Lectures and practical computational analysis assignments.
Knowledge score (maximum points 100)
Pre obligations		Points	Final exam	Points
Activites during lectures			Test paper
Practical lessons		30	Oral examination	30
Projects		40
Colloquia
Seminars