Computer Aided Analysis and Design

Course Description

The role of computers in analysis and design of technical systems is presented. The course describes error handling in computer calculations, linear system solving algorithms and numerical optimization algorithms, as well as evolutionary algorithms. The transient analysis formulations and methods are presented. The systems behaviour is analysed in regard of system stability and chaotic properties. The presented algorithms are evaluated in regard of their computational efficiency.

Learning Outcomes

  1. identify an optimization problem
  2. apply a nonlinear optimization procedure
  3. compare different optimization algorithms
  4. define floating point precision standard
  5. describe the problem of solving differential equations systems
  6. apply a numerical integration method
  7. compare the precision and stability of numerical integration methods

Forms of Teaching

Lectures

predavanja

Exercises

auditorne vjezbe

Independent assignments

domaca zadaca

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Homeworks 0 % 25 % 0 % 25 %
Mid Term Exam: Written 0 % 35 % 0 %
Final Exam: Written 0 % 40 %
Exam: Written 50 % 50 %
Exam: Oral 25 %

Week by Week Schedule

  1. The Gaussian Elimination Method (GEM); LU Factorization
  2. Pivoting Strategies; PLU Factorization
  3. Optimization in one dimension (golden section search, successive parabolic interpolation, Newton's method)
  4. Nonlinear unconstrained optimzation
  5. Nonlinear constrained optimzation
  6. Direct Search Algorithms (the Hooke-Jeeves method); Gradient Methods (the steepest descent);
  7. Nonlinear Least-Squares Problems; The Gauss-Newton Method; The Levenberg-Marquardt Method
  8. Midterm exam
  9. Stochastic search (simulated annealing, genetic algorithms, Monte Carlo search), Evolutionary algorithms for SOOP
  10. Numerical solving of differential equations; Euler's method; Taylor's method
  11. Multistep Methods; Multivalue Methods
  12. Multistep Methods; Multivalue Methods
  13. Floating point precision and error propagation
  14. Floating point precision and error propagation
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (1. semester)
Communication and Space Technologies (profile)
Free Elective Courses (1. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (1. semester)
Computer Engineering (profile)
Free Elective Courses (1. semester) Specialization Course (1. semester) (3. semester)
Computer Science (profile)
Core-elective courses (1. semester) Specialization Course (3. semester) Theoretical Course (1. semester)
Control Systems and Robotics (profile)
Free Elective Courses (1. semester)
Data Science (profile)
Free Elective Courses (1. semester)
Electrical Power Engineering (profile)
Free Elective Courses (1. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (1. semester)
Electronic and Computer Engineering (profile)
Free Elective Courses (1. semester)
Electronics (profile)
Free Elective Courses (1. semester)
Information and Communication Engineering (profile)
Free Elective Courses (1. semester)
Network Science (profile)
Free Elective Courses (1. semester)
Software Engineering and Information Systems (profile)
Free Elective Courses (1. semester) Specialization Course (1. semester) (3. semester)
Telecommunication and Informatics (profile)
Recommended elective courses (3. semester)

Literature

L. Budin (.), Analiza i projektiranje računalom - skripta, Skriptarnica
S. Turk, L. Budin (1989.), Analiza i projektiranje računalom, Školska knjiga, Zagreb

For students

General

ID 222454
  Winter semester
5 ECTS
L1 English Level
L1 e-Learning
45 Lectures
15 Exercises
15 Laboratory exercises

Grading System

Excellent
Very Good
Good
Acceptable