FI:P075 Scientific Computing and Visua - Course Information
P075 Scientific Computing and Visualization
Faculty of InformaticsSpring 2000
- Extent and Intensity
- 2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
- Teacher(s)
- doc. RNDr. Stanislav Bartoň, CSc. (lecturer)
- Guaranteed by
- prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Stanislav Bartoň, CSc. - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Informatics (programme FI, B-IN)
- Informatics (programme FI, M-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, M-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
- Information Technology (programme FI, B-IN)
- Syllabus
- The goal of this course is the brief overview of the applications of higher mathematics in the technical and nature sciences. The mathematical basis of the technical problems, technological computations and nontrivial problems of the nature sciences are accented. No special knowledge are necessary to pass throw this course, the necessary theory is explained at the beginning of the problems solution, only the secondary - high school knowledge are required. The knowledge of the differential calculus of more variables and the symbolic algebra ere welcomed, (Maple, Derive).
- The problems, (for example optimization of the heat insulation of the reservoir, the free compression of the metals, the bodies kinematics and dynamics, the optimization of the surfaces illumination, the classical celestial mechanics and others) are selected so, that it is possible to demonstrate how to use the symbolic algebra to solve nontrivial problems. The solving strategy is following: The definition of the problem, its physical model, the possibilities of its simplification, the initial and border conditions, the mathematical model, its symbolic algebra model (Maple, Derive), the possibility of its solution, the analytical solution (Maple, Derive) and its numerical solution (Maple, Matlab), the discussion about the results, the affect of the simplifications onto result, the visualization and animation of the solution (Maple, Matlab).
- Language of instruction
- Czech
- Further Comments
- The course is taught annually.
The course is taught: every week.
- Enrolment Statistics (Spring 2000, recent)
- Permalink: https://is.muni.cz/course/fi/spring2000/P075